Graduate Program

The MS concentration in Machine Learning and Artificial Intelligence is designed to equip students with the expertise needed to thrive in one of the most rapidly advancing fields in technology. Machine Learning (ML) and Artificial Intelligence (AI) are transforming industries by enabling computers to learn from data and perform tasks that typically require human intelligence, such as recognizing patterns, making decisions, designing circuits, and understanding natural language. These technologies are integral to innovations across sectors including healthcare, engineering, finance, transportation, and entertainment, driving efficiencies, uncovering new insights, and creating opportunities for enhanced user experiences and improved quality of life.

In this concentration, students will gain a deep understanding of the foundations and practical applications of ML and AI. They will develop proficiency in programming languages such as Python, learn to implement various ML algorithms, and gain experience with AI frameworks like TensorFlow and PyTorch. The curriculum also emphasizes critical skills in data analysis, statistical modeling, and the ethical considerations of AI deployment. Our faculty's unique expertise in audio and music, medical imaging, robotics, networks and graphs, AR/VR, directly translates to an exciting curriculum for students with an electrical engineering background. Through hands-on projects and real-world case studies, students will learn to design, evaluate, and deploy intelligent systems, preparing them to become leaders and innovators in the dynamic field of ML and AI.

Concentration Requirements

One of the following courses:

• ECE 408: The Art of Machine Learning
• ECE 409: Machine Learning

Two of the following courses:

• ECE 403: Advanced Computer Architecture for Machine Learning
• ECE 412: Optimization for Machine Learning
• ECE 477: Computer Audition
• ECE 440: Introduction to Random Processes
• ECE 484: Machine Learning for Medical Imaging
• ECE 442: Network Science Analytics
• ECE 449: Machine Vision

In this program, students can earn their master’s with a concentration in musical acoustics and signal processing in one calendar year. Program instructors include faculty from both the ECE department and the Eastman School of Music.

Non-EE majors would need the following courses which can be found at a Community College:

• Calculus including linear algebra and multi-variable calculus.
• Calculus based Physics including Mechanics and Electricity and Magnetism
• Circuits and Systems (typical sophomore EE course)
• A course in Signals
• A programming course in C/C++ or other formal

Students enrolled in this program are encouraged to participate in one of the many ongoing research projects in the Music Research Laboratory, including projects on:

• Internet-enabled music telepresence and immersive audio environments
• Musical source separation and automated music transcription
• Physical modeling musical sound synthesis
• Music representations
• Audio watermarking
• Quantitative studies of musical timbre
• Audio embedded music metadata

Students can also participate in research in music perception and cognition, and music and language being done in other allied laboratories.

Concentration Requirements

Three of the following:

• ECE 429: Audio Electronics
• ECE 433: Musical Acoustics
• ECE 439: Spatial Audio
• ECE 470: Digital Audio Effects
• ECE 472: Audio Signal Processing
• ECE 475: Audio Software Design I
• ECE 476: Audio Software Design II
• ECE 477: Computer Audition
• ECE 478: Revolutions in Sound
• ECE 480: Advanced Audio Amplifier Design

Students in this program can participate in a wide range of research including:

• Signal research on:
  • Wide-band radar and sonar systems design
  • Digital image and video processing
  • Very low bitrate video compression
  • Medical image processing
• Communications research on:
  • Frequency hopping codes for multiple-access-spread-spectrum communications, designed to minimize interference in radar and sonar systems
• Digital image processing research on:
  • Image enhancement and restoration
  • Image segmentation/recognition
  • Processing of magnetic resonance images
• Digital video processing research on:
  • 2-D and 3-D motion estimation techniques
  • Deformable motion analysis
  • Stereoscopic image analysis
  • Standards conversion and high-resolution image reconstruction
  • Object-based methods for very low bitrate video compression
• Biomedical signal processing research on:
  • Spectral analysis in one-, two-, and three-dimensional spaces
  • Analysis and algorithms for computed tomography
  • Inverse scattering techniques for imaging tissue characterization

Signal and Image Processing Concentration Requirements

• ECE 446: Digital Signal Processing

Two of the following courses:

• ECE 408: The Art of Machine Learning
• ECE 410: Introduction to Augmented and Virtual Reality
• ECE 411: Special Topics in Agumented and Virtual Reality
• ECE 412: Optimization for Machine Learning
• ECE 433: Probabilistic Models for Inference and Estimation
• ECE 440: Random Processes
• ECE 441: Detection and Estimation Theory
• ECE 447: Digital Image Processing
• ECE 449: Machine Vision
• ECE 450: Information Theory
• ECE 457: Digital Video Processing
• ECE 477: Computer Audition
• ECE 484: Machine Learning in Imaging
• ECE 485: Inverse Problems in Imaging

Communications Concentration Requirements

• ECE 445: Wireless Communications

Three of the following courses:

• ECE 440: Random Processes
• ECE 441: Detection and Estimation Theory
• ECE 444: Digital Communications
• ECE 446: Digital Signal Processing
• ECE 448: Wireless Sensor Networks
• ECE 450: Information Theory
• CSC 457: Computer Networks

High-frequency sound (ultrasound) is used in many areas of medicine to obtain images of soft organs in the body. High-intensity ultrasound is used to destroy kidney and gallstones without surgery (lithotripsy).

Students in this program will conduct scientific investigations that focus on the interactions of ultrasonic energy with biological materials ranging from heart and liver tissues, to bones and gallstones. Students may also conduct research on the applications of ultrasonic contrast-producing agents similar to radiological contrast and tracer techniques.

The results from these efforts are used to improve or extend clinical applications of ultrasonic techniques, both in diagnosing diseases of the heart and liver, and in therapeutic users such as lithotripsy. This work is also used to set standards for exposure of patients during examination and to improve the application of high-intensity sound for therapy.

Concentration Requirements

Three of the following courses:

• ECE 432: Acoustic Waves
• ECE 452: Medical Imaging
• ECE 446: Digital Signal Processing
• ECE 447: Digital Image Processing
• BME 451: Biomedical Ultrasound
• ECE 453/BME 453: Ultrasound Imaging

VLSI/IC Microelectronics and Computer Design

Students in this program work in a variety of VLSI/IC microelectronics and computer design research areas. Some of the current research being conducted here at Rochester includes:

• Research in VLSI and CAE to address topics in integrated circuit design methodologies and automation.
• Specific system-oriented research including an analytical model for multi-access protocols with prioritized messages and distributed control architecture.
• Testability studies that explore operational parallelism in any testing process to determine the set of automated test procedures which minimizes the silicon area consumed by the built-in self-test structures.
• Applying VLSI design and analysis techniques to develop ultrafast superconducting digital integrated circuits.
• Designing and analyzing high performance VLSI-based digital and analog integrated circuits and their systems. Specifically, speed, area, and power dissipation tradeoffs are investigated in terms of application-specific constraints and their fundamental circuit level limitations.

VLSI/IC Microelectronics Design Concentration Requirements

Three of the following courses:

• ECE 429: Audio Electronics
• ECE 460: Digital Radio Engineering
• ECE 461: Introduction to VLSI
• ECE 466: RF and Microwave Integrated Circuits
• ECE 468: Advanced Analog CMOS Circuits and Systems
• ECE 469: High Speed Integrated Electronics

Computer Design and Computer Engineering Concentration Requirements

Three of the following courses:

• ECE 400: Computer Organization
• ECE 401: Advanced Computer Architecture
• ECE 403: Advanced Computer Architecture for Machine Learning
• ECE 404: Multiprocessor Architecture
• ECE 405: Ising Machines: Principles and Practices
• ECE 408: The Art of Machine Learning
• ECE 409: Machine Learning
• ECE 413: Introduction to Hardware Security
• CSC 455: Software Analysis and Improvement
• CSC 456: Operating Systems
• CSC 458: Parallel and Distributed Systems
• ECE 461: Introduction to VLSI

The fields of future petascale engineering and quantum information science are at the center of the XXI century “beyond CMOS technological transformation, expected to have an impossible to overestimate impact on society and national security. They reside at the core of enabling technologies ranging from generative artificial intelligence, massive data storage centers to networks of quantum computers for multi-party processing.

The primary goal of the “Novel Computing” MS concentration is parallel to the DISCoVER: Design and Integration of Superconducting Computation for Ventures beyond Exascale Realization (a 7-year Expedition Project funded by NSF), i.e., to explore novel ways to harness superconductivity for petascale computing. DISCoVER will accomplish these objectives through a compelling combination of technological advances, novel circuits, and innovative architectures, resulting in the demonstration of a superconductor system of cryogenic computing cores. This system will consist of a 32-bit superconducting CPU integrated with a superconductor neural network accelerator and a superconductor Ising machine solver. Our goal is to achieve a performance-energy efficiency gain of more than 100x at the complete system level as compared to deeply-scaled CMOS–a remarkable leap forward in technological, energy-efficient computing.

The concentration is aimed at the best undergraduate students in such areas as electrical and computer engineering, physics, materials science, computer science, and more. Students in the program will graduate with the unique skills and knowledge needed to become leaders in the emerging future engineering hardware development. The degree will open wide-range perspectives for employment in high-tech industry and/or will be a steppingstone to further graduate education. Summer internships at participating DISCoVER research groups are part of the program.

Concentration Requirements

These three courses:

• ECE 423: Semiconductor Devices
• ECE 425: Superconductivity and the Josephson Effect (new course)
• ECE 427: Superconductor Electronics (new course)

Plus, any of others below

• ECE 420: Introduction to Quantum Engineering Science and Engineering E
• ECE 422: Nanoelectronic Devices
• ECE 461: Intro to VLSI
• ECE 469: High-Speed Integrated Electronics
• ECE 520: Spin-Based Electronics

Nanoscale Devices

In a new and ever-changing landscape of electronics needs, there has been a strong focus to work with deeply scaled nanoelectronic transistors and to go beyond conventional Si-based transistors entirely. New technologies such as spintronics, 2D electronics, phase-change electronics, neuromorphic electronics, superconducting electronics and topological electronics are becoming more important in defining what the next 50 years of electronics looks like from the device level up. 

Students in this program work in a variety of next generation nanoelectronic device research areas. Some of the current research being conducted here at Rochester includes:

• Nanoelectronic devices with 2D van der Waals-bonded materials (graphene, transition metal dichalcogenides, phosphorene, etc…).
• Heteroepitaxial growth of new electronic materials, or heteroepitaxial assembly of 2D vdW electronic materials. 
• Novel spintronic and magnetic devices with unconventional magnetic materials or unconventional device constructs. 
• Topological electronic devices implemented with quantum electronic materials.
• Implementing new superconducting devices, along with the design/fabrication/testing of superconducting digital integrated circuits. Applications may include quantum computing or ultra high speed digital electronics. 
• Using picosecond electrical and optical pulses to probe the transient response of semiconducting and superconducting devices, such as Metal-Semiconductor-Metal (MSM) photodiodes and tunnel junctions.

Nanoelectronic Devices Concentration Requirements

• ECE 423: Semiconductor Devices

Plus two of the following courses:

• ECE 422: Nanoelectronic Devices
• ECE 436: Nanophotonic and Nanomechanical Devices
• ECE 469: High Speed Electronics

Photonics

Information processing with optical pulses allows for higher data rates than electronic signals. Optoelectronics research is focused on obtaining a detailed understanding of ultrafast phenomena and ultrafast nonlinearities in semiconductors and high-temperature superconductors, and at using silicon quantum dots and nanometer-size objects in optoelectronics and biosensing.

Students in this program work in a variety of optoelectronic research areas. Some of the current research being conducted here at Rochester includes:

• Using laser technology, solid-state physics, materials science, and device physics and engineering to design novel optoelectronic devices.
• Studying electron and hole thermalization and recombination in semiconductors and semiconductor quantum wells, and the optoelectronic properties of porous silicon, which unlike crystalline silicon emits light efficiently at room temperature.
• Determining response times using laser processing of Y-Ba-Cu-O epitaxial thin films into oxygen-rich (superconducting) and oxygen-poor (semiconducting) regions, together with pump-probe femtosecond reflectivity measurements.

Photonics Concentration Requirements

Three of the following courses:

• ECE 421 (OPT 421): Optical Properties of Materials
• ECE 422: Nanoelectronic Devices
• ECE 423: Semiconductor Devices
• ECE 426 (OPT 428): Waveguides and Optoelectronic Devices
• ECE 436: Nanophotonic and Nanomechanical Devices

The fields of quantum engineering and quantum information science are on the verge of disruptive breakthroughs, with a potential for having an impossible to overestimate impact on society and national security. They reside at the core of all these breakthroughs as an enabling technology by connecting networks of quantum computers for multi-party processing or enabling communications with absolute security rooted in the laws of physics.

The concentration brings together an interdisciplinary team to solve important technological problems related to quantum information processing with a focus on:

• Socially important issues such as rapidly growing presence and overall importance of computers and computing in our present daily lives
• Data/information security
• Economic and social impact of seemingly unlimited capabilities of data (often personal) processing and storage, as well as how the latter is going to change our perception as human beings, when augmented reality and virtual reality will become our “daily” reality.

Concentration Requirements

Three of the following:

• ECE 420: Introduction to Quantum Engineering Science and Engineering
• ECE 423: Semiconductor Devices
• ECE 436: Nanophotonics
• ECE 454: Quantum Information Processing
• ECE 461: Intro to VLSI
• ECE 469: High-Speed Integrated Electronics
• ECE 520: Spin-Based Electronics

Robotics is a field of engineering that covers many different topics from mechanism design and embedded systems to artificial intelligence and machine learning. Roboticists draw their talents from and from many fields including electrical engineering, computer engineering, computer science, mechanical engineering and other adjacent fields and often work closely with engineers and researchers from these disciplines. The development and deployment of intelligent robots have the promise to transform how we transport materials and people, grow food and manufacture goods, diagnose and treat illnesses, and explore this and other planets. 

Students in this program will develop an understanding of systems, models, and algorithms for how robots make decisions about how to interact with the physical world from sensor information and prior knowledge. Students may also conduct fundamental research in theoretical or experimental robotics to improve the performance of such systems in a wide range of applications. Students will additionally develop practical skills such as robotics software development and physical experimentation techniques through hands-on laboratory exercises and research activities.

Students in this program may participate in a wide range of research including

• Guidance, navigation, and control of unmanned ground vehicles
• Symbol grounding for human-robot interaction and teaming
• Reinforcement learning for underactuated robot control
• Perception for robot intelligence
• Control systems for robotically assisted medical imaging

Concentration Requirements

One of the following courses:

• ECE 417: Robot Motion Planning and Manipulation
• ECE 418: Mobile Robot Estimation, Mapping, Navigation, and Interaction

Two of the following courses:

• ECE 409: Machine Learning
• ECE 440: Intro to Random Processes
• ECE 443: Probabilistic Models for Inference and Estimation
• ECE 449: Machine Vision