Graduate Program

Spring Term Schedule

Spring 2026

Number	Title	Instructor	Time
ECE 400-01 Computer Organization Hanan Dery TR 2:00PM - 3:15PM
Instruction set principles; processor design, pipelining, data and control hazards; datapath and computer arithmetic; memory systems; I/O and peripheral devices; internetworking. Students learn the challenges, opportunities, and tradeoffs involved in modern microprocessor design. Assignments and labs involve processor and memory subsystem design using hardware description languages (HDL). Prerequisites: ECE 114, ECE 112 or CSC 171, or permission of Instructor Location (TR 2:00PM - 3:15PM)
ECE 405-01 Ising Machines: Principles and Practices Michael Huang MW 2:00PM - 3:15PM
This course provides a systematic treatment of a number of related concepts in computing that are outside mainstream (von Neumann) approach. The primary goal is to help students understand the foundation of the on-going research of a particular type of von Neumann architecture: Ising machines. Topics include a basic review of thermodynamics (such as Gibbs-Boltzmann distribution, Langevin dynamics), computational methods inspired by it (such as Markov chain Monte Carlo methods, energy-based models: a subset of machine learning algorithms), and hardware design of Ising machines. Pre-requisite: ECE 200 or equivalent Location (MW 2:00PM - 3:15PM)
ECE 406-01 Intro to multi-objective machine learning Lisha Chen MW 4:50PM - 6:05PM
Machine learning is central to modern AI, and real systems rarely optimize a single objective: we routinely balance accuracy and fairness, robustness and efficiency, or multiple tasks at once. This course introduces the theory, algorithms, and applications of multi-objective machine learning, combining mathematical rigor with hands-on practice. We cover optimization foundations, and the statistical toolkit that explains when and why the algorithms generalize. In this course, you will first learn the foundations of multi-objective / vector optimization – optimality and dominance concept, optimization algorithms and their convergence guarantee. You will be required to implement some classical algorithms and apply them to machine learning problems. Later on, the statistical aspects for multi-objective learning -- vector risk, and generalization / stability will be covered. Finally, you will be required to complete a course project in which you implement a multi-objective learning algorithm, analyze its optimization and/or statistical properties, and apply it to a real machine-learning task. Prerequisites: ECE 412 (or equivalent) Location (MW 4:50PM - 6:05PM)
ECE 408-01 The Art of Machine Learning Zhiyao Duan WF 10:25AM - 11:40AM
Machine Learning (ML) is the branch of Artificial Intelligence dedicated to teaching computers how to solve tasks by learning from data. This class introduces basic concepts of machine learning through various real-world ECE applications. It will cover various learning paradigms such as supervised learning, semi-supervised learning, unsupervised learning, and reinforcement learning. It will also cover classical and state-of-the-art techniques such as linear models, support vector machines, Gaussian mixture models, hidden Markov models, matrix factorization, ensemble learning, principal component analysis, and various kinds of deep neural networks. Students will learn the pros and cons of different methods and their suited application scenarios. This course is hands-on with multiple programming assignments and a final project to solve real ECE problems. Prerequisites: General programming such as ECE-114; MATH 165 linear algebra. Probability and statistics such as ECE 270 is recommended. Location (WF 10:25AM - 11:40AM)
ECE 409-01 Machine Learning Daniel Gildea TR 11:05AM - 12:20PM
Mathematical foundations of classification, regression, and decision making. Supervised algorithms covered include perceptrons, logistic regression, support vector machines, and neural networks. Directed and undirected graphical models. Numerical parameter optimization, including gradient descent, expectation maximization, and other methods. Introduction to reinforcement learning. Proofs covered as appropriate. Significant programming projects will be assigned. This course involves a lot of math and algorithms. You should know multivariable calculus, linear algebra, and some algorithms. No formal prerequisites but MATH 165, MATH 164, and CSC 242 strongly recommended. Location (TR 11:05AM - 12:20PM)
ECE 417-01 Robot Motion Planning and Manipulation Thomas Howard TR 12:30PM - 1:45PM
This course covers control and planning algorithms with applications in robotics. Topics include forward and inverse kinematics, dynamics, joint space control, operational space control, robot trajectory planning, search spaces, search algorithms, grasping, manipulation, and applications of such topics on mobile robots and robotic manipulators. It is expected by the end of the course that students will be able to demonstrate an understanding of how robots plan paths and trajectories in the context of their perceived environment in simulation and on physical robots through laboratory exercises. Performance is evaluated through homework assignments, coding assessments, exams, and a course project. PREREQUISITE: ECE 216 Location (TR 12:30PM - 1:45PM)
ECE 417-02 Robot Motion Planning and Manipulation Thomas Howard F 12:30PM - 1:35PM
This course covers control and planning algorithms with applications in robotics. Topics include forward and inverse kinematics, dynamics, joint space control, operational space control, robot trajectory planning, search spaces, search algorithms, grasping, manipulation, and applications of such topics on mobile robots and robotic manipulators. It is expected by the end of the course that students will be able to demonstrate an understanding of how robots plan paths and trajectories in the context of their perceived environment in simulation and on physical robots through laboratory exercises. Performance is evaluated through homework assignments, coding assessments, exams, and a course project. PREREQUISITE: ECE 216 Location (F 12:30PM - 1:35PM)
ECE 421-01 Opt Properties of Materials Gary Wicks TR 11:05AM - 12:20PM
Interaction of light with materials electrons, phonons, plasmons, and polaritons. Optical reflection, refraction, absorption, scattering, Raman scattering (spontaneous and stimulated), light emission (spontaneous and stimulated). Electrooptic effects and optical nonlinearities in solids. Plasmonics. Semiconductors and their nanostructures are emphasized; metals and insulators also discussed. Location (TR 11:05AM - 12:20PM)
ECE 426-01 Integrated Photonics Jaime Cardenas TR 3:25PM - 4:40PM
Propagation and interactions in optical waveguides. Topics include the Goos-Haenchen effect, coupled-mode theory, pulse broadening in optical fibers, coupling between guided-wave structures and wave-guide devices such as semiconductor lasers, fiber lasers and opto-electric devices. Location (TR 3:25PM - 4:40PM)
ECE 433-01 Musical Acoustics Michael Heilemann TR 11:05AM - 12:20PM
Aspects of acoustics. Review of oscillators, vibratory motion, the acoustic wave equation, reflection, transmission and absorption of sound, radiation and diffraction of acoustic waves. Resonators, hearing and speech, architectural and environmental acoustics. Location (TR 11:05AM - 12:20PM)
ECE 433-02 Musical Acoustics Michael Heilemann M 3:25PM - 4:15PM
Aspects of acoustics. Review of oscillators, vibratory motion, the acoustic wave equation, reflection, transmission and absorption of sound, radiation and diffraction of acoustic waves. Resonators, hearing and speech, architectural and environmental acoustics. Location (M 3:25PM - 4:15PM)
ECE 433-03 Musical Acoustics – W 1:05PM - 1:55PM
Aspects of acoustics. Review of oscillators, vibratory motion, the acoustic wave equation, reflection, transmission and absorption of sound, radiation and diffraction of acoustic waves. Resonators, hearing and speech, architectural and environmental acoustics. Location (W 1:05PM - 1:55PM)
ECE 441-01 Detection & Estimation Theory Mujdat Cetin TR 9:40AM - 10:55AM
Bayesian and non-Bayesian inference in signal processing, data science, communications, control, and machine learning. Principles of detection, estimation, and time series analysis. Detection: binary and M-ary hypothesis testing; receiver operating characteristics; minimax, randomized, and Neyman-Pearson tests. Estimation: random and nonrandom parameter estimation; Bayes least squares, maximum a posteriori, and maximum likelihood estimation; Cramer-Rao lower bound. Time series analysis: Wiener and Kalman filtering. Location (TR 9:40AM - 10:55AM)
ECE 442-01 Network Science Analytics Gonzalo Mateos Buckstein MW 3:25PM - 4:40PM
The science of networks is an emerging discipline of great importance that combines graph theory, probability and statistics, and facets of engineering and the social sciences. This course will provide students with the mathematical tools and computational training to understand large-scale networks in the current era of Big Data. It will introduce basic network models and structural descriptors, network dynamics and prediction of processes evolving on graphs, modern algorithms for topology inference, community and anomaly detection, as well as fundamentals of social network analysis. All concepts and theories will be illustrated with numerous applications and case studies from technological, social, biological, and information networks. Prerequisites: Some mathematical maturity, comfortable with linear algebra, probability, and analysis (e.g., MTH164-165). Exposure to programming and Matlab useful, but not required. For more information, please visit the class website: https://www.hajim.rochester.edu/ece/sites/gmateos/ECE442.html Location (MW 3:25PM - 4:40PM)
ECE 445-01 Wireless Communications Irving Barron Martinez TR 2:00PM - 3:15PM
This course teaches the underlying concepts behind traditional cellular radio and wireless data networks as well as design trade-offs among RF bandwidth, transmitter and receiver power and cost, and system performance. Topics include channel modeling, digital modulation, channel coding, network architectures, medium access control, routing, cellular networks, WiFi/IEEE 802.11 networks, mobile ad hoc networks, sensor networks and smart grids. Issues such as quality of service (QoS), energy conservation, reliability and mobility management are discussed. Students are required to complete a semester-long research project in order to obtain in-depth experience with a specific area of wireless communication and networking. Location (TR 2:00PM - 3:15PM)
ECE 449-01 Machine Vision Jiebo Luo TR 9:40AM - 10:55AM
Introduction to computer vision, including camera models, basic image processing, pattern and object recognition, and elements of human vision. Specific topics include geometric issues, statistical models, Hough transforms, color theory, texture, and optic flow. Graduate-level course requires additional readings and assignments. Location (TR 9:40AM - 10:55AM)
ECE 451-01 Biomedical Ultrasound Diane Dalecki TR 11:05AM - 12:20PM
The course presents the physical basis for the use of high-frequency sound in medicine. Topics include acoustic properties of tissue, sound propagation (both linear and nonlinear) in tissues, interaction of ultrasound with gas bodies (acoustic cavitation and contrast agents), thermal and non-thermal biological effects of ultrasound, ultrasonography, dosimetry, hyperthermia and lithotripsy. Prerequisites: Math 164, Math 165, Physics 122, at least junior standing, or permission of instructor. Location (TR 11:05AM - 12:20PM)
ECE 456-01 Introduction to Quantum Theory of Materials Sobhit Kumar Singh MW 10:25AM - 11:40AM
An introduction to the fascinating world of quantum materials in bulk and 2D. This course aims to unveil the quantum origin of materials-specific properties from the atomic level. Topics covered include: crystal structure and symmetries, fundamentals of electronic structure, phonons and vibrational spectroscopies, optical properties of materials, electronic and thermal transport elastic and mechanical properties of solids, superconductivity, magnetism and a brief discussion of ab-initio prediction of materials properties and molecular dynamics. Location (MW 10:25AM - 11:40AM)
ECE 465-02 Introduction to Statistical Machine Learning Cantay Caliskan TR 2:00PM - 3:15PM
The course provides an introduction to modern machine learning concepts, techniques, and algorithms. Topics discussed include regression, clustering and classification, kernels, support vector machines, feature selection, goodness of fit, neural networks. Programming assignments emphasize taking theory into practice, through applications on real-world data sets. Students will be expected to work with Python programming environment to complete the assignments. PRE-REQUISITES: DSCC 462, STAT 190 or equivalent introductory statistics background AND DSCC 440 (or equivalent data mining course) or permission of instructor. Location (TR 2:00PM - 3:15PM)
ECE 472-01 Audio Dig Signal Processing Sarah Smith MW 2:00PM - 3:15PM
This course is a survey of audio digital signal processing fundamentals and applications. Topics include sampling and quantization, analog to digital converters, time and frequency domains, spectral analysis, vocoding, digital filters, audio effects, music audio analysis and synthesis, and other advanced topics in audio signal processing. Implementation of algorithms using Matlab and on dedicated DSP platforms is emphasized. PREREQUISITES: ECE 114 and basic Matlab programming, ECE 241 or other equivalent signals and systems courses. Location (MW 2:00PM - 3:15PM)
ECE 472-03 Audio Dig Signal Processing Sarah Smith F 2:15PM - 3:15PM
This course is a survey of audio digital signal processing fundamentals and applications. Topics include sampling and quantization, analog to digital converters, time and frequency domains, spectral analysis, vocoding, digital filters, audio effects, music audio analysis and synthesis, and other advanced topics in audio signal processing. Implementation of algorithms using Matlab and on dedicated DSP platforms is emphasized. PREREQUISITES: ECE 114 and basic Matlab programming, ECE 241 or other equivalent signals and systems courses. Location (F 2:15PM - 3:15PM)
ECE 474-01 Biomedical Sensors, Circuits & Instruments Scott Seidman TR 9:40AM - 10:55AM
Course will cover circuits and sensors used to measure physiological systems at an advanced level. Both signal conditioning and sensor characteristics will be addressed. Topics will include measurement of strain, pressure, flow, temperature, biopotentials, and physical circuit construction. The co-requisite laboratory will focus on the practical implementation of electronic devices for biomedical measurements. Location (TR 9:40AM - 10:55AM)
ECE 474-02 Biomedical Sensors, Circuits & Instruments Scott Seidman F 8:00AM - 11:00AM
Circuits and sensors used to measure physiological systems at an advanced level. Measurement of strain, pressure, flow, temperature, biopotentials, and physical circuit construction. Location (F 8:00AM - 11:00AM)
ECE 475-01 Audio Software Design Ming Lun Lee TR 12:30PM - 1:45PM
In this course, students will develop skills for designing audio/music applications and creating computer music in C and Max. We will begin with the history of computer music, a survey of audio programming languages, and a review of C. Libsndfile, a C library for reading and writing sound files, will be used to explore topics in sound synthesis, analysis, and digital signal processing. Students will use PortAudio, a C library for real-time audio input/output, to design DSP applications. Max is a visual programming language for interactive audio/music and multimedia. Students are required to watch pre-recorded lectures to learn Max and attend recitations for reviews. They will also practice their programming techniques through a series of programming assignments, a midterm drum machine project in Max, and a final research/design project. Prerequisite: ECE114 or instructor permission Location (TR 12:30PM - 1:45PM)
ECE 475-02 Audio Software Design Ming Lun Lee F 10:25AM - 11:40AM
In this course, students will develop skills for designing audio/music applications and creating computer music in C and Max. We will begin with the history of computer music, a survey of audio programming languages, and a review of C. Libsndfile, a C library for reading and writing sound files, will be used to explore topics in sound synthesis, analysis, and digital signal processing. Students will use PortAudio, a C library for real-time audio input/output, to design DSP applications. Max is a visual programming language for interactive audio/music and multimedia. Students are required to watch pre-recorded lectures to learn Max and attend recitations for reviews. They will also practice their programming techniques through a series of programming assignments, a midterm drum machine project in Max, and a final research/design project. Prerequisite: ECE114 or instructor permission Location (F 10:25AM - 11:40AM)
ECE 478-01 Revolutions in Sound Ming Lun Lee MW 10:25AM - 11:40AM
Revolutions in Sound: Artistic and Technical Evolution of Sound Recording provides a multifaceted account of the evolution of sound technologies, starting with Edison's invention of the phonograph in 1877 through the development of microphones, the radio, magnetic tape recording, vinyl records, multi-track recording, stereo, digital audio, surround sound, online music streaming, and 3D audio. We will discuss how technology has shaped the musical experience, and, conversely, how various genres of music have influenced the development of audio technologies. We will also delve into the secrets behind several legendary recordings, including those of Enrico Caruso, Bessie Smith, Les Paul, Louis Armstrong, the Beach Boys, the Beatles, ABBA, Michael Jackson, Justin Bieber, and Taylor Swift. Special topics include spatial audio for VR/AR, object-based audio, binaural recording, Ambisonics, K-pop, and artificial intelligence (AI) in music. Location (MW 10:25AM - 11:40AM)
ECE 480-01 Advanced Audio Amplifier Design Daniel Phinney T 9:00AM - 10:15AM
Audio amplification concepts and design techniques focused on the use of vacuum tubes. Will cover some concepts related to MOSFET amplifiers as well. A mixture of lab based projects and LTSpice simulation. Shall cover concepts related to impedance matching, preamps, class A and class AB power amplifiers, power supplies and grounding techniques. Prerequisites: AME 295 or Instructor permission Location (T 9:00AM - 10:15AM)
ECE 480-02 Advanced Audio Amplifier Design Daniel Phinney W 10:25AM - 1:45PM
Audio amplification concepts and design techniques focused on the use of vacuum tubes. Will cover some concepts related to MOSFET amplifiers as well. A mixture of lab based projects and LTSpice simulation. Shall cover concepts related to impedance matching, preamps, class A and class AB power amplifiers, power supplies and grounding techniques. Prerequisites: AME 295 or Instructor permission Location (W 10:25AM - 1:45PM)
ECE 482-01 Clinical Imaging II Susan Hobbs 7:00PM - 7:00PM
Students will be required to take two courses that cover all major clinical imaging methods. The following clinical courses will be offered, broken down by imaging modality and target organs. The corresponding credit hours are shown. These two courses will give each student an understanding of how each modality functions in a clinical setting, the application of such imaging to specific body parts, and what image characteristics are relevant to specific diseases. material. Prequisites: Bachelor’s degree in physics/engineering and/or a medical degree. Location ( 7:00PM - 7:00PM)
ECE 484-01 Deep Learning in Imaging Marvin Doyley MW 10:25AM - 11:40AM
Researchers are actively developing artificial intelligence (AI) techniques to improve the accuracy and efficiency of some of the most challenging components of medical imaging. These components include computer-aided diagnosis, automatic segmentation of anatomical regions, automatic lesion detection, data fusion, and image-guided surgical intervention, to name a few. This course aims to develop imaging scientists who understand the fundamentals of machine learning, how to implement different machine learning algorithms, how to select and extract features from medical images, and how to evaluate different AI learning strategies (supervised vs. non-supervised). The course will cover classical machine learning techniques and deep learning techniques. Specifically, students will learn how to evaluate and implement different deep learning architectures, convolution neural networks, recurrent neural networks, object detection networks, U-Net (segmentation networks), multi-modal architectures, and generative adversarial networks. This course will also teach students how to train neural networks for medical images, data augmentation, and domain adaptation. Students will learn how to use PyTorch, a flexible machine learning framework, to implement and evaluate these concepts. Location (MW 10:25AM - 11:40AM)
ECE 485-01 Inverse Problems in Imaging Nebojsa Duric; Rehman Ali TR 11:30AM - 1:00PM
This course teaches students the mathematical principles and computations that underpin modern imaging systems. The course will cover deconvolution, regularization methods, statistical methods, linear inverse imaging problems, singular value decomposition, and Fourier-based methods used in image reconstruction. Clinical examples of inverse problems and their solutions will be provided to the students during the lectures. Students will be assigned homework and administered tests to gauge their understanding of the material. Prerequisties: Bachelor’s degree in physics/engineering and/or a medical degree. Location (TR 11:30AM - 1:00PM)
ECE 486-01 Clinical Imaging Lab Susan Hobbs WF 11:50AM - 1:05PM
This course covers the same modalities and target sites as Clinical Imaging 1 and 2. Students are expected to shadow practicing radiologists who will demonstrate real-time image reads and diagnoses. This course will give each student a practical understanding of how radiologists read images and what imaging characteristics are essential inputs in the diagnostic process. Prerequisites: Bachelor’s degree in physics/engineering and/or a medical degree. Instructor: Susan Hobbs Location (WF 11:50AM - 1:05PM)
ECE 491-01 Master's Reading Gonzalo Mateos Buckstein 7:00PM - 7:00PM
This course is for master's students that have made arrangements with a faculty member to complete readings and discussion in a particular subject in their field of study. Location ( 7:00PM - 7:00PM)
ECE 494-04 Master’s Research Internship Roman Sobolewski 7:00PM - 7:00PM
This course provides master's students with the opportunity to gain practical experience in a professional setting related to their field of study. Students must register for one credit of internship during the semester in which they participate. Must have approval of the Graduate Education and Postdoctoral Affairs Office for SAS and Hajim. Location ( 7:00PM - 7:00PM)
ECE 495-02 Master's Research Cristiano Tapparello 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-03 Master's Research Stephen Wu 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-04 Master's Research Hui Wu 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-05 Master's Research Roman Sobolewski 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-06 Master's Research Gaurav Sharma 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-07 Master's Research – 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-08 Master's Research Gonzalo Mateos Buckstein 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-09 Master's Research Qiang Lin 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-10 Master's Research Selcuk Kose 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-11 Master's Research Zeljko Ignjatovic 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-12 Master's Research Michael Huang 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-13 Master's Research Thomas Howard 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-14 Master's Research Wendi Heinzelman 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-15 Master's Research Eby Friedman 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-16 Master's Research Marvin Doyley 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-17 Master's Research Hanan Dery 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-18 Master's Research Mujdat Cetin 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-19 Master's Research Mark Bocko 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-20 Master's Research Yuhao Zhu 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-21 Master's Research Ming Lun Lee 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-22 Master's Research Michael Heilemann 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-23 Master's Research Sarah Smith 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-24 Master's Research Daniel Phinney 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-25 Master's Research Stephen Roessner 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-26 Master's Research Zhiyao Duan 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-27 Master's Research Sreepathi Pai 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-28 Master's Research Tre Dipassio 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-29 Master's Research John Nichol 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 495-30 Master's Research Jim Zavislan 7:00PM - 7:00PM
This course provides master’s students with the opportunity to conduct, develop, and refine their research projects. Students will engage in research relevant to their field of study and make progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 496-01 Special Projects in ECE Ming Lun Lee 7:00PM - 7:00PM
No description Location ( 7:00PM - 7:00PM)
ECE 595-02 PhD Research Thomas Howard 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-03 PhD Research Laurel Carney 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-04 PhD Research Sarah Smith 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-05 PhD Research Roman Sobolewski 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-06 PhD Research Stephen Wu 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-07 PhD Research Zhiyao Duan 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-08 PhD Research Tong Geng 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-09 PhD Research Michael Huang 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-10 PhD Research Jaime Cardenas 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-12 PhD Research Axel Wismueller 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-13 PhD Research Sreepathi Pai 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-14 PhD Research William Donaldson 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-15 PhD Research Mark Bocko 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-16 PhD Research Ehsan Hoque 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-17 PhD Research Stephen McAleavey 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-18 PhD Research Mujdat Cetin 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-19 PhD Research Hanan Dery 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-20 PhD Research Michael Huang 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-21 PhD Research Marvin Doyley 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-22 PhD Research Eby Friedman 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-23 PhD Research – 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-24 PhD Research Zeljko Ignjatovic 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-25 PhD Research Wendi Heinzelman 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-26 PhD Research Qiang Lin 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-27 PhD Research Gaurav Sharma 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-28 PhD Research Selcuk Kose 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-29 PhD Research Hui Wu 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-30 PhD Research Gonzalo Mateos Buckstein 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-31 PhD Research Michael Heilemann 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-32 PhD Research Ming Lun Lee 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-33 PhD Research Stephen Roessner 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-34 PhD Research Mohammad Mehrmohammadi 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-35 PhD Research Nebojsa Duric 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-36 PhD Research Tolulope Olugboji 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-37 PhD Research Jiaming Liang 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 595-38 PhD Research Lisha Chen 7:00PM - 7:00PM
This course provides PhD students with fewer than 90 credits the opportunity to conduct, develop, and refine their doctoral research projects. Students will engage in research relevant to their field of study and make progress toward completing their dissertations. Location ( 7:00PM - 7:00PM)
ECE 597-01 ECE Colloquium Michele Foster W 11:50AM - 1:05PM
No description Location (W 11:50AM - 1:05PM)
ECE 895-01 Continuation of Master’s Enrollment – 7:00PM - 7:00PM
This course is designed for master's degree students who have completed all required coursework but still need to finalize specific degree requirements under less than half-time enrollment. Location ( 7:00PM - 7:00PM)
ECE 897-02 Masters Dissertation Gonzalo Mateos Buckstein 7:00PM - 7:00PM
This course provides master's students who are currently completing their final required coursework, or with special circumstances like an approved reduced courseload, with the opportunity to work full-time on their degrees. Students will make significant progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 899-02 Masters Dissertation Gonzalo Mateos Buckstein 7:00PM - 7:00PM
This course provides master’s students who have completed or are currently completing all course requirements with the opportunity to work full-time on their thesis. Students will make significant progress toward completing their degrees. Location ( 7:00PM - 7:00PM)
ECE 986V-01 Full-Time Visiting Student – 7:00PM - 7:00PM
This course affords graduate students visiting the University of Rochester full-time student status. Visiting students will engage in research, discussion, and/or professional training in partnership with an academic department or faculty member. Location ( 7:00PM - 7:00PM)
ECE 987V-01 Part Time Visiting Student – 7:00PM - 7:00PM
This course affords graduate students visiting the University of Rochester part-time student status. Visiting students will engage in research, discussion, and/or professional training in partnership with an academic department or faculty member. Location ( 7:00PM - 7:00PM)
ECE 999-01 Doctoral Dissertation Gonzalo Mateos Buckstein 7:00PM - 7:00PM
This course provides PhD students who have completed or are currently completing 90 credits of coursework and have fulfilled all degree requirements (except for the dissertation) with the opportunity to work full-time on their dissertation. Students will make significant progress toward completing their degrees. Location ( 7:00PM - 7:00PM)

Number	Title	Instructor	Time
Monday
ECE 433-02 Musical Acoustics Michael Heilemann
Aspects of acoustics. Review of oscillators, vibratory motion, the acoustic wave equation, reflection, transmission and absorption of sound, radiation and diffraction of acoustic waves. Resonators, hearing and speech, architectural and environmental acoustics.
Monday and Wednesday
ECE 456-01 Introduction to Quantum Theory of Materials Sobhit Kumar Singh
An introduction to the fascinating world of quantum materials in bulk and 2D. This course aims to unveil the quantum origin of materials-specific properties from the atomic level. Topics covered include: crystal structure and symmetries, fundamentals of electronic structure, phonons and vibrational spectroscopies, optical properties of materials, electronic and thermal transport elastic and mechanical properties of solids, superconductivity, magnetism and a brief discussion of ab-initio prediction of materials properties and molecular dynamics.
ECE 478-01 Revolutions in Sound Ming Lun Lee
Revolutions in Sound: Artistic and Technical Evolution of Sound Recording provides a multifaceted account of the evolution of sound technologies, starting with Edison's invention of the phonograph in 1877 through the development of microphones, the radio, magnetic tape recording, vinyl records, multi-track recording, stereo, digital audio, surround sound, online music streaming, and 3D audio. We will discuss how technology has shaped the musical experience, and, conversely, how various genres of music have influenced the development of audio technologies. We will also delve into the secrets behind several legendary recordings, including those of Enrico Caruso, Bessie Smith, Les Paul, Louis Armstrong, the Beach Boys, the Beatles, ABBA, Michael Jackson, Justin Bieber, and Taylor Swift. Special topics include spatial audio for VR/AR, object-based audio, binaural recording, Ambisonics, K-pop, and artificial intelligence (AI) in music.
ECE 484-01 Deep Learning in Imaging Marvin Doyley
Researchers are actively developing artificial intelligence (AI) techniques to improve the accuracy and efficiency of some of the most challenging components of medical imaging. These components include computer-aided diagnosis, automatic segmentation of anatomical regions, automatic lesion detection, data fusion, and image-guided surgical intervention, to name a few. This course aims to develop imaging scientists who understand the fundamentals of machine learning, how to implement different machine learning algorithms, how to select and extract features from medical images, and how to evaluate different AI learning strategies (supervised vs. non-supervised). The course will cover classical machine learning techniques and deep learning techniques. Specifically, students will learn how to evaluate and implement different deep learning architectures, convolution neural networks, recurrent neural networks, object detection networks, U-Net (segmentation networks), multi-modal architectures, and generative adversarial networks. This course will also teach students how to train neural networks for medical images, data augmentation, and domain adaptation. Students will learn how to use PyTorch, a flexible machine learning framework, to implement and evaluate these concepts.
ECE 405-01 Ising Machines: Principles and Practices Michael Huang
This course provides a systematic treatment of a number of related concepts in computing that are outside mainstream (von Neumann) approach. The primary goal is to help students understand the foundation of the on-going research of a particular type of von Neumann architecture: Ising machines. Topics include a basic review of thermodynamics (such as Gibbs-Boltzmann distribution, Langevin dynamics), computational methods inspired by it (such as Markov chain Monte Carlo methods, energy-based models: a subset of machine learning algorithms), and hardware design of Ising machines. Pre-requisite: ECE 200 or equivalent
ECE 472-01 Audio Dig Signal Processing Sarah Smith
This course is a survey of audio digital signal processing fundamentals and applications. Topics include sampling and quantization, analog to digital converters, time and frequency domains, spectral analysis, vocoding, digital filters, audio effects, music audio analysis and synthesis, and other advanced topics in audio signal processing. Implementation of algorithms using Matlab and on dedicated DSP platforms is emphasized.
ECE 442-01 Network Science Analytics Gonzalo Mateos Buckstein
The science of networks is an emerging discipline of great importance that combines graph theory, probability and statistics, and facets of engineering and the social sciences. This course will provide students with the mathematical tools and computational training to understand large-scale networks in the current era of Big Data. It will introduce basic network models and structural descriptors, network dynamics and prediction of processes evolving on graphs, modern algorithms for topology inference, community and anomaly detection, as well as fundamentals of social network analysis. All concepts and theories will be illustrated with numerous applications and case studies from technological, social, biological, and information networks.
ECE 406-01 Intro to multi-objective machine learning Lisha Chen
Machine learning is central to modern AI, and real systems rarely optimize a single objective: we routinely balance accuracy and fairness, robustness and efficiency, or multiple tasks at once. This course introduces the theory, algorithms, and applications of multi-objective machine learning, combining mathematical rigor with hands-on practice. We cover optimization foundations, and the statistical toolkit that explains when and why the algorithms generalize. In this course, you will first learn the foundations of multi-objective / vector optimization – optimality and dominance concept, optimization algorithms and their convergence guarantee. You will be required to implement some classical algorithms and apply them to machine learning problems. Later on, the statistical aspects for multi-objective learning -- vector risk, and generalization / stability will be covered. Finally, you will be required to complete a course project in which you implement a multi-objective learning algorithm, analyze its optimization and/or statistical properties, and apply it to a real machine-learning task.
Monday, Wednesday, and Friday
Tuesday
ECE 480-01 Advanced Audio Amplifier Design Daniel Phinney
Audio amplification concepts and design techniques focused on the use of vacuum tubes. Will cover some concepts related to MOSFET amplifiers as well. A mixture of lab based projects and LTSpice simulation. Shall cover concepts related to impedance matching, preamps, class A and class AB power amplifiers, power supplies and grounding techniques.
Tuesday and Thursday
ECE 441-01 Detection & Estimation Theory Mujdat Cetin
Bayesian and non-Bayesian inference in signal processing, data science, communications, control, and machine learning. Principles of detection, estimation, and time series analysis. Detection: binary and M-ary hypothesis testing; receiver operating characteristics; minimax, randomized, and Neyman-Pearson tests. Estimation: random and nonrandom parameter estimation; Bayes least squares, maximum a posteriori, and maximum likelihood estimation; Cramer-Rao lower bound. Time series analysis: Wiener and Kalman filtering.
ECE 449-01 Machine Vision Jiebo Luo
Introduction to computer vision, including camera models, basic image processing, pattern and object recognition, and elements of human vision. Specific topics include geometric issues, statistical models, Hough transforms, color theory, texture, and optic flow. Graduate-level course requires additional readings and assignments.
ECE 474-01 Biomedical Sensors, Circuits & Instruments Scott Seidman
Course will cover circuits and sensors used to measure physiological systems at an advanced level. Both signal conditioning and sensor characteristics will be addressed. Topics will include measurement of strain, pressure, flow, temperature, biopotentials, and physical circuit construction. The co-requisite laboratory will focus on the practical implementation of electronic devices for biomedical measurements.
ECE 409-01 Machine Learning Daniel Gildea
Mathematical foundations of classification, regression, and decision making. Supervised algorithms covered include perceptrons, logistic regression, support vector machines, and neural networks. Directed and undirected graphical models. Numerical parameter optimization, including gradient descent, expectation maximization, and other methods. Introduction to reinforcement learning. Proofs covered as appropriate. Significant programming projects will be assigned. This course involves a lot of math and algorithms. You should know multivariable calculus, linear algebra, and some algorithms.
ECE 421-01 Opt Properties of Materials Gary Wicks
Interaction of light with materials electrons, phonons, plasmons, and polaritons. Optical reflection, refraction, absorption, scattering, Raman scattering (spontaneous and stimulated), light emission (spontaneous and stimulated). Electrooptic effects and optical nonlinearities in solids. Plasmonics. Semiconductors and their nanostructures are emphasized; metals and insulators also discussed.
ECE 433-01 Musical Acoustics Michael Heilemann
Aspects of acoustics. Review of oscillators, vibratory motion, the acoustic wave equation, reflection, transmission and absorption of sound, radiation and diffraction of acoustic waves. Resonators, hearing and speech, architectural and environmental acoustics.
ECE 451-01 Biomedical Ultrasound Diane Dalecki
The course presents the physical basis for the use of high-frequency sound in medicine. Topics include acoustic properties of tissue, sound propagation (both linear and nonlinear) in tissues, interaction of ultrasound with gas bodies (acoustic cavitation and contrast agents), thermal and non-thermal biological effects of ultrasound, ultrasonography, dosimetry, hyperthermia and lithotripsy.
ECE 485-01 Inverse Problems in Imaging Nebojsa Duric; Rehman Ali
This course teaches students the mathematical principles and computations that underpin modern imaging systems. The course will cover deconvolution, regularization methods, statistical methods, linear inverse imaging problems, singular value decomposition, and Fourier-based methods used in image reconstruction. Clinical examples of inverse problems and their solutions will be provided to the students during the lectures. Students will be assigned homework and administered tests to gauge their understanding of the material.
ECE 417-01 Robot Motion Planning and Manipulation Thomas Howard
This course covers control and planning algorithms with applications in robotics. Topics include forward and inverse kinematics, dynamics, joint space control, operational space control, robot trajectory planning, search spaces, search algorithms, grasping, manipulation, and applications of such topics on mobile robots and robotic manipulators. It is expected by the end of the course that students will be able to demonstrate an understanding of how robots plan paths and trajectories in the context of their perceived environment in simulation and on physical robots through laboratory exercises. Performance is evaluated through homework assignments, coding assessments, exams, and a course project.
ECE 475-01 Audio Software Design Ming Lun Lee
In this course, students will develop skills for designing audio/music applications and creating computer music in C and Max. We will begin with the history of computer music, a survey of audio programming languages, and a review of C. Libsndfile, a C library for reading and writing sound files, will be used to explore topics in sound synthesis, analysis, and digital signal processing. Students will use PortAudio, a C library for real-time audio input/output, to design DSP applications. Max is a visual programming language for interactive audio/music and multimedia. Students are required to watch pre-recorded lectures to learn Max and attend recitations for reviews. They will also practice their programming techniques through a series of programming assignments, a midterm drum machine project in Max, and a final research/design project.
ECE 400-01 Computer Organization Hanan Dery
Instruction set principles; processor design, pipelining, data and control hazards; datapath and computer arithmetic; memory systems; I/O and peripheral devices; internetworking. Students learn the challenges, opportunities, and tradeoffs involved in modern microprocessor design. Assignments and labs involve processor and memory subsystem design using hardware description languages (HDL).
ECE 445-01 Wireless Communications Irving Barron Martinez
This course teaches the underlying concepts behind traditional cellular radio and wireless data networks as well as design trade-offs among RF bandwidth, transmitter and receiver power and cost, and system performance. Topics include channel modeling, digital modulation, channel coding, network architectures, medium access control, routing, cellular networks, WiFi/IEEE 802.11 networks, mobile ad hoc networks, sensor networks and smart grids. Issues such as quality of service (QoS), energy conservation, reliability and mobility management are discussed. Students are required to complete a semester-long research project in order to obtain in-depth experience with a specific area of wireless communication and networking.
ECE 465-02 Introduction to Statistical Machine Learning Cantay Caliskan
The course provides an introduction to modern machine learning concepts, techniques, and algorithms. Topics discussed include regression, clustering and classification, kernels, support vector machines, feature selection, goodness of fit, neural networks. Programming assignments emphasize taking theory into practice, through applications on real-world data sets. Students will be expected to work with Python programming environment to complete the assignments.
ECE 426-01 Integrated Photonics Jaime Cardenas
Propagation and interactions in optical waveguides. Topics include the Goos-Haenchen effect, coupled-mode theory, pulse broadening in optical fibers, coupling between guided-wave structures and wave-guide devices such as semiconductor lasers, fiber lasers and opto-electric devices.
Wednesday
ECE 480-02 Advanced Audio Amplifier Design Daniel Phinney
Audio amplification concepts and design techniques focused on the use of vacuum tubes. Will cover some concepts related to MOSFET amplifiers as well. A mixture of lab based projects and LTSpice simulation. Shall cover concepts related to impedance matching, preamps, class A and class AB power amplifiers, power supplies and grounding techniques.
ECE 597-01 ECE Colloquium Michele Foster
No description
ECE 433-03 Musical Acoustics –
Aspects of acoustics. Review of oscillators, vibratory motion, the acoustic wave equation, reflection, transmission and absorption of sound, radiation and diffraction of acoustic waves. Resonators, hearing and speech, architectural and environmental acoustics.
Wednesday and Friday
ECE 408-01 The Art of Machine Learning Zhiyao Duan
Machine Learning (ML) is the branch of Artificial Intelligence dedicated to teaching computers how to solve tasks by learning from data. This class introduces basic concepts of machine learning through various real-world ECE applications. It will cover various learning paradigms such as supervised learning, semi-supervised learning, unsupervised learning, and reinforcement learning. It will also cover classical and state-of-the-art techniques such as linear models, support vector machines, Gaussian mixture models, hidden Markov models, matrix factorization, ensemble learning, principal component analysis, and various kinds of deep neural networks. Students will learn the pros and cons of different methods and their suited application scenarios. This course is hands-on with multiple programming assignments and a final project to solve real ECE problems.
ECE 486-01 Clinical Imaging Lab Susan Hobbs
This course covers the same modalities and target sites as Clinical Imaging 1 and 2. Students are expected to shadow practicing radiologists who will demonstrate real-time image reads and diagnoses. This course will give each student a practical understanding of how radiologists read images and what imaging characteristics are essential inputs in the diagnostic process.
Thursday
Friday
ECE 474-02 Biomedical Sensors, Circuits & Instruments Scott Seidman
Circuits and sensors used to measure physiological systems at an advanced level. Measurement of strain, pressure, flow, temperature, biopotentials, and physical circuit construction.
ECE 475-02 Audio Software Design Ming Lun Lee
In this course, students will develop skills for designing audio/music applications and creating computer music in C and Max. We will begin with the history of computer music, a survey of audio programming languages, and a review of C. Libsndfile, a C library for reading and writing sound files, will be used to explore topics in sound synthesis, analysis, and digital signal processing. Students will use PortAudio, a C library for real-time audio input/output, to design DSP applications. Max is a visual programming language for interactive audio/music and multimedia. Students are required to watch pre-recorded lectures to learn Max and attend recitations for reviews. They will also practice their programming techniques through a series of programming assignments, a midterm drum machine project in Max, and a final research/design project.
ECE 417-02 Robot Motion Planning and Manipulation Thomas Howard
This course covers control and planning algorithms with applications in robotics. Topics include forward and inverse kinematics, dynamics, joint space control, operational space control, robot trajectory planning, search spaces, search algorithms, grasping, manipulation, and applications of such topics on mobile robots and robotic manipulators. It is expected by the end of the course that students will be able to demonstrate an understanding of how robots plan paths and trajectories in the context of their perceived environment in simulation and on physical robots through laboratory exercises. Performance is evaluated through homework assignments, coding assessments, exams, and a course project.
ECE 472-03 Audio Dig Signal Processing Sarah Smith
This course is a survey of audio digital signal processing fundamentals and applications. Topics include sampling and quantization, analog to digital converters, time and frequency domains, spectral analysis, vocoding, digital filters, audio effects, music audio analysis and synthesis, and other advanced topics in audio signal processing. Implementation of algorithms using Matlab and on dedicated DSP platforms is emphasized.