Courses

Flexible and Stretchable Electronics

This course focuses on development of in-depth foundation on this emerging area of future electronics. Traditionally electronic devices and systems have been physically rigid and bulky. However, back in the eighties Prof. Eli Yablonovich of UCB predicted flexible electronic materials by lift-off process and in 2000 Nobel Prize in Chemistry was awarded to Berkeley Alumni Prof. Alan Heeger of UCSB for discovery of conductive polymers. These two events propelled a surge in innovative materials, processes, and applications in the exciting area of flexible and stretchable electronics. Nonetheless, the area itself is vast and topics vary significantly. Therefore, in this course, a comprehensive view about the past, present and future of flexible and stretchable electronics is categorically discussed in an unbiased manner. Lessons and discussions will include but not limited to physics and mechanics of flexible and stretchable electronics, traditional and emerging materials, novel processes, integration strategies, device performance and reliability, system integration complexity, manufacturing aspects and wide ranging applications. A key objective of overall learning would be to bridge the gap between status-quo and technology transfer requirement for ubiquitous deployment of flexible and stretchable electronics in our daily life.

Integrated Circuit/MEMS Fabrication

Pre-requisite: Knowledge of semiconductor devices

Principles and Methods of Safe Aerospace System Design

CMOS Analog IC Design

Data Analytics

Radio Frequency Integrated Circuits

CSE Seminar

Digital Systems Design Automation

This course will provide an introduction to the tools used to design and analyze circuits at the logic level of abstraction (where circuits are composed of gates and flip-flops). Most digital chips used in computing and electronic systems (including microprocessors, graphics processors, chips used in network routers, cell phones, digital audio/video appliances, automotive electronics) are entirely or largely designed using EDA tools. This course will focus on the foundations of logic-level EDA tools, including the design of exact and heuristic algorithms that form the basis for VLSI Computer-Aided Design. Topics covered include an overview of the IC design flow and levels of abstraction, synthesis of two-level (AND-OR / PLA) circuits, multi-level logic synthesis and technology mapping, sequential circuit synthesis, Logic-level verification using Boolean Satisfiability and BDDs, Timing Analysis, Power analysis and Reduction, and design techniques for emerging nanoscale technologies.

Numerical Electromagnetics

Machine Learning for Bioinformatics and Healthcare

Powder Storage and Flow

Combustions of Energetic Materials

Intelligent Systems

Quantum Circuits and Systems

Through five decades of continued transistor scaling, the size of unit computing has almost reached its fundamental size limit, thus creating a plateau in performance for traditional CMOS based circuits. While the speed of CMOS technology is relatively saturated, quantum computation seems to be the next landmark technology in computing. By relying on quantum principles and properties - most importantly superposition and entanglement - Quantum Computers demonstrate an almost miraculous capacity to solve seemingly insurmountable problems. However, the interfacing, readout and electronic control circuitry around the Quantum Computing Core still uses CMOS technologies at room temperature, and there is a strong need to place the electronic circuitry near the Quantum Core (at a few milli-Kelvins) for scalability and performance, which leads to an entirely new paradigm of CMOS-based circuits, which is celled Cryo-CMOS. Research and development in Quantum computing as well as Cryo-CMOS are currently flourishing, with possible implementation of quantum algorithms, circuits and systems in the foreseeable future. The purpose of this course is to prepare potential circuit and systems engineers for that future by introducing them to the sate-of-the-art Cryo-CMOS circuits. This course will build basic understanding of cryogenic CMOS circuits, and highlight their use in Quantum System Applications (Computing, Sensing, Communication), which has become increasingly important in quantum research in the last few years. Two design examples will be a key component of the course.

Computational Combustion & Propulsion

Fundamentals of thermochemistry Chemical equilibrium and its calculation Chemical kinetics and auto-ignition Laminar non-premixed flames and computation of an opposed jet flame Models for turbulent combustion (the flamelet model and the transported probability density function model) Turbulent non-premixed combustion and the modeling and simulation of a turbulent free jet flame Turbulent partial premixed combustion and the modeling and simulation of a turbulent lifted jet flame Computational propulsion and the modeling of a model rocket combustor [Tentative] Advanced topics on data-driven modeling and machine learning

Subsurface Hydrology

Part 1: Groundwater Cycle Groundwater is the single largest reservoir of available freshwater on Earth. Part 1 explores the essential processes and properties that affect underground water. Part 2: Wells Hydraulics To use the water from the ground, we first have to extract it! Part 2 introduces wells hydraulics. Part 3: Groundwater Contamination Part 3 describes the principles of transport in aquifers so that engineers can predict and plan the safe extraction of groundwater for private and public use.

Computational Methods for Power System Analysis

System modeling of power networks. Description of modern electricity markets. Analysis of the economic dispatch problem using optimality conditions. Planning of distributed energy resources. Smart grid applications. Machine learning applications to power systems (forecasting, demand-side management, and fault detection). Assigned projects will involve implementing some of the methods using realistic power system models.

High-Speed Mixed-Signal IC

Through five decades of continued transistor scaling, the size of unit computing has gone to virtually zero. In the foreseeable future, Computing will be all around us, in mostly invisible forms, leading to 50+ billions of connected devices to the Internet (Internet of Things or IoT). Increasingly, connectivity has become an indispensable part of modern computing devices. By some estimates, IoT devices will generate 3+ exabytes (one billion gigabytes) of data per day by 2018. The various communication fabrics that will handle this enormous amount of data needs to be extremely energy-efficient. The advance and prosperity of CMOS technology has enabled design of these communication fabrics using mixed-signal and digital-heavy techniques, which allows for lower power, reconfigurability and faster time-to-market. This course will build basic understanding of such mixed-signal circuits and systems and highlight their use in communication systems (wireline IO, wireless), which are becoming increasingly important in the data-driven world. A design project will be a key component of the course. The students will conduct a group design project that will help them obtain practical design knowledge and skills and exposure to Process Design Kit (PDK) and EDA tools like Cadence Schematic Editor, Layout Editor, and Simulator (Hspice or SpectreRF).