New Course Announcements
Fall 2023: Quantum Computing Systems & Architecture
Description: With a number of quantum machines already available to researchers and scientists, the big question is when and how these machines will find their way into the mainstream. The challenge lies in improving these systems to be large enough, fast enough, and accurate enough to solve problems that are intractable for classical computers. This course will primarily focus on architectural and microarchitectural advancements that pertain to quantum error correction and control. In that regard, we will review recent literature on these topics, identify challenges that remain unsolved, and investigate potential solutions.More info (pdf)
Fall 2023: Solution Processed Optoelectronics
This is a multidisciplinary class that covers the optical and electronic properties of a wide range of solution-processed semiconductors, including inorganic nanomaterials, hybrid organicinorganic metal halide perovskite, conjugated polymer, etc.More info (pdf)
Fall 2023: Causality and Machine Learning
This course introduces the fundamental concepts of causality, and causal inference using machine learning models. Topics will include:counterfactuals (potential outcomes and graphs), identification and estimation of conditional average treatment effects from randomized control trials and observational data, as well as causal inference under hidden confounding and limited overlap.More info (pdf)
Fall 2023: Theory of Network Design
This is a proof-based course that lies at the intersection of algorithms and graph theory. We will tour through some classic algorithms and cutting-edge work in the area of network design. Topics will include distance oracles, spanners, emulators, preservers, shortcut sets, hopsets, algorithmic applications of these objects, and methods for making these objects tolerant to temporary failures in a network.More info (pdf)
Fall 2023: Quantum Computing, Information and Probability
The aim of the course is to develop the key concepts of quantum computing and information as well provide hands-on quantum programming skills (Qiskit platform). A basic working knowledge of linear algebra is a prerequisite, but no prior knowledge of quantum mechanics, classical computing or information theory is assumed. Graduate students in all areas of engineering, computer science, system theory, the physical sciences and mathematics should find this material of interest.More info (pdf)
Fall 2023: Machine Learning Basics for Optics & Photonics
AI is transforming many industries and has caused an explosion of applications. Areas that have been affected by ML and deep learning include self-driving cars, speech and image recognition, effective web searching, fraud detection, human genome analysis, and many other advances. Knowledge of AI, ML and Deep Learning is becoming a must for any engineer or scientist. This course is intended to give you exposure to the underlying theory and language. This is an introduction for non-experts, and it will enable you to go onto other AI, ML and deep learning courses offered in various departments.More info (pdf)
Fall 2023: Extended Reality and Society
Fall 2023: From 51 Billion to Zero: Challenges and Opportunities in Reducing Greenhouse Gas Emissions
EECS 298-051, Fall 2023, will be a seminar-type course with presentations by the instructor and invited speakers. The goal of this course is two-fold. First, the understanding of how human activities, from electricity generation to transportation, construction, agriculture, and heating/cooling, contribute to the release of greenhouse gases (GHG) in the Earth’s atmosphere. Second, the study of current and prospective engineering solutions for reducing and potentially eliminating GHG emissions, with several presentations by UM experts.More info (pdf)
Winter 2023: Machine Learning Theory
When do machine learning algorithms work and why? How do we formally characterize what it means to learn from data? This course will study the theoretical foundations of machine learning. Tentative topics include generalization, optimization, deep learning, online learning and bandits, and unsupervised learning.
Winter 2023: Applied Machine Learning for Modeling Human Behavior
Machine learning, with a focus on human behavior, across multiple modalities including speech and text. Teams complete projects based primarily on their individual interests centered on modeling an aspect of human behavior. Prior experience with speech/language or other data modeling is not needed.
Winter 2023: CSE Seminar
Winter 2023: Data Centric Systems
Winter 2023: Human-AI Interaction & Systems
Human intelligence and artificial intelligence (AI) are intertwined, co-evolving and complementary. This course explores how to combine the complementary strengths of humans and AI to design intelligent interactive systems that are ethical, usable, and useful. We will discuss topics including ways to facilitate humans to interact with AI, systems that combine human and AI to solve complex challenges, crowdsourcing and human computation, explainable AI, and AI fairness and auditing.
Winter 2023: Introduction to the Social Consequences of Computing
Computing is now used in every facet of life affecting countless people, including making policy decisions about people in lending, policing, criminal justice, admissions, advertising, and hiring. In doing so, the process of computing and algorithm design now involves understanding the role of computing in society.
This class will introduce you to the ways in which applications of computing affect societal institutions and how these social consequences produce questions about how to conceptualize, critique, and ensure our all-too-human values in computing. To accomplish this, we will explore computing, particularly artificial intelligence (AI) and machine learning, including exploring the role of AI in everything from personalization to surveillance to online speech. We will critically examine the philosophical and sociological underpinnings of these values and the strategies commonly used to promote them, and seek to connect these conceptualizations to the emerging algorithmic tools proposed for promoting those values. In order to practice reasoning through these problems, this class will feature programming in Python. No previous programming experience in Python is needed.
Winter 2023: Action and Perception
In this graduate-level seminar course, we will study research papers on the development of visual, audio, and tactile perception and body control in humans, in comparison with the latest machine learning methods in computer vision and robotics, on tasks such as ocular motor control, reaching, grasping, manipulation, locomotion etc.More info
Winter 2023: Extended Reality and Society
From pediatric medical care, advanced manufacturing, and commerce to film analysis, first-responder training, and unconscious bias training, the fledgling, immersive field of extended reality may take us far beyond the realm of traditional video games and entertainment, and into the realm of diverse social impact.
“EECS 498 : Extended Reality and Society” is a programming-intensive senior capstone / MDE course that empowers students with the knowledge and experience to…
– Implement medium-sized virtual and augmented reality experiences using industry-standard techniques and technologies (unity / unreal).
– Design socially-conscious, empowering user experiences that engage diverse audiences.
– Contribute to cultural discourse on the hopes, concerns, and implications of an XR-oriented future.
– Carry out user testing and employ feedback in an iterative design / development process.
– Work efficiently in teams of 2-4 using agile production methods and software (Jira)
Students will conclude the course with at least three significant, socially-focused XR projects in their public portfolios.
Winter 2023: Privacy Enhancing Technologies (PETS)
This course explores the latest advances in privacy-enhancing technologies (PETs).More info (pdf)
Winter 2023: Data Centric Systems
This special topics course will discuss recent advances and new directions that are being pursued to design data-centric computing systems.More info (pdf)
Winter 2023: Quantum Electromagnetics
This course will introduce students to the quantum theory of electromagnetic radiation, matter and their interactions, which underpins all new quantum technologies.More info (pdf)
Winter 2023: Algorithms for Data Science
This course will introduce algorithmic and theoretical aspects of data science. With the emergence of machine learning and data science, as well as the ever-increasing data sizes, providing theoretical foundations for these areas will become increasingly important. The course will cover several important algorithms in data science and see how their performances can be analyzed. While fundamental ideas covered in EECS 376 (e.g., design and analysis of algorithms) will be still important, some topics will introduce new concepts and ideas, including randomized dimensionality reduction, sketching algorithms, and algorithms for continuous optimization.More info
Winter 2023: Formal Verification of Hardware and Software
This course explores the latest advances in automated proof methods for checking whether or not certain properties hold under all possible executions of a complex hardware or software system. Specifically, we focus on the class of “control-centric” properties, namely those properties that are weakly-dependent on the data state of the system.More info (pdf)
Fall 2022: Machine Learning Basics for Optics and Photonics
Please see flyer.More info (pdf)