Program Requirements

All EECS MEng students should expect to complete four (4) technical courses within the EECS department at the graduate level, the Fung Institute’s engineering leadership curriculum, as well as a capstone project that will be hosted by the EECS department. You must select a project from the list below.

2019-2020 Capstone Projects

For the capstone projects for Master of Engineering in Electrical Engineering and Computer Science (EECS) our department believes that the students are going to have a significantly better experience if the projects are followed closely by an EECS professor throughout the academic year. To ensure this, we have asked the faculty in each area for which the Master of Engineering is offered in our department to formulate one or more project ideas that the incoming students will have to choose from.

Project 1

Title – Machine learning meets wireless communication: spectrum collaboration (advisors Prof. Anant Sahai)

Description – Machine learning ideas have continued to revolutionize field after field — in this project we will explore how this plays out for wireless communication. This project will put together an intellectually diverse team to accomplish this and touches on machine learning, signal processing, data science, game theory, computer networking, and wireless communication.

Project 2

Title – Evaluating the Impacts of Selfish Routing on Congestion in Urban Networks (advisor Prof. Alex Bayen)

Description – The rise of congestion across the United States and the increasing adoption of mobile routing services have enabled drivers with the ability to find the fastest routes available in urban road networks. Arterial roads and side streets originally designed for local traffic are impacted by the influx of selfishly routed drivers, garnering much recent media attention and civic debate. This project will use flow-based game theoretic models as a framework for simulating the behavior of routed and non-routed drivers on a road network. Students will use state-of-the-art traffic modeling tools to identify structural and spatiotemporal factors of transportation networks that lead to the adverse impacts of selfish routing. In addition, students will continue development of an interactive dashboard that displays the results of their experiments. The dashboard is envisioned as a tool to demonstrate the impacts of routing apps under varying scenarios so that policymakers and practitioners can hone in on areas most impacted by selfish routing and assess potential actions to mitigate the effects of cut-through traffic at the local and regional scales.

Project 3

Title – Retina Tracking and Stimulation for Color Perception Beyond Human Vision (advisor Prof. Ren Ng)

Description – The goal of this project is to prototype next-generation color display technology, based on laser-writing directly to the retina surface. In principle, the system would have new capabilities that include displaying colors that cannot be seen in the real world, or treating color blindness. This underlying research is in collaboration with the School of Optometry. The scope of the project can be adjusted based on the expertise of the project members. Helpful background includes some of: software engineering, embedded programming, computer graphics, computer vision, computational imaging, signal processing, machine learning, optical engineering, physical electronics, exposure to biomedical devices, and precision engineering.

Project 4

Title – Vision Correcting Displays (advisor Prof. Brian A. Barsky)

Description – Vision problems such as near-sightedness, far-sightedness, as well as others, are due to optical aberrations in the human eye. These conditions are prevalent, and the number of people who have these hardships is growing rapidly. Correcting optical aberrations in the human eye is traditionally done optically using eyeglasses, contact lenses, or refractive surgeries; these are sometime not convenient or not always available to everyone. Furthermore, higher order aberrations are not correctable with eyeglasses. This research is investigating a novel approach which involves a new computation based aberration-correcting light field display: by incorporating the person’’s own optical aberrations into the computation, content shown on the display is modified such that the viewer will be able to see the display in sharp focus without using corrective eyewear.

Our research involves the analysis of image formation models; through the retinal light field projection, it is possible to compensate for the optical blurring on the target image by a process of prefiltering with the inverse blur. As part of this project, we are building a light field display prototype that supports our desired inverse light field prefiltering. We are working towards extending the capability to correct for higher order aberrations. This latter aspect is particularly exciting since it would enable people for whom it is not possible to see displays in sharp focus using eyeglasses to be able to do so using no corrective eyewear. This is a broad project that incorporates many different aspects. A variety of different backgrounds for students is welcome. Students are free to choose what is the most interesting part for them.

Project 5

Title -Adversarially robust neural networks (advisors Profs. Kurt Keutzer/Michael Mahoney)

Description – There has been multiple attempts to design robust neural networks, but each apparent successful design, has been broken by a new adversarial attack. This empirical approach to robust design has not been successful. A new paradigm is to design certifiably robust neural networks by constraining the training to guarantee no adversarial attack is possible.

Projects 6 & 7

Title – Flexible Data Plane for Networks (advisor Prof. Shyam Parekh)

Description – In recent years, Software Defined Networking (SDN) has proven to be a highly impactful technology for the network control plane. To complement SDN, there has also been much effort in making the network data plane flexible. Specifically, flexibility for network devices in terms of both protocol and hardware platform independence while allowing field programmability is deemed to be highly desirable. A high level language called P4 has been developed for this data plane programming. In-band telemetry, congestion control, network load balancing, etc. are applications of much interest for a network of P4 capable nodes. This project will focus on demonstrating the benefits for one or more of such applications using emulation/simulation.

Title – Simulation of 5G Scenarios (advisor Prof. Shyam Parekh)

Description – 5G is expected to be a milestone for technological progress. The vision for 5G includes support for low-latency and high-reliability human-centric as well as machine-centric communication, high user density, high mobility, enhanced multimedia services, and energy-efficient communication required for Internet-of-Things (IoT) applications. This project is targeted towards demonstrating one or more of such capabilities using a discrete event simulator. This can be done by using an existing simulation platform for this purpose (e.g., the one based on the simmer package for R), or by developing one using the contributed modules for your favorite language (e.g., Python). The project would require you to develop a good understanding of the key 5G principles, and to develop an ability to capture the key aspects of the physical system in a model for investigating the premise under investigation.

Project 7


Technical Courses

At least THREE of your four technical courses should be chosen from the list below. The remaining technical courses should be chosen from your own or another MEng area of concentration within the EECS Department.

Fall 2019 (Updated: 7/10/19)

Spring 2020 (Updated: 10/7/2019)

Note: The courses listed here are not guaranteed to be offered, and the course schedule may change without notice. Refer to the UC Berkeley Course Schedule for further enrollment information.