M.S. Degree - Plan II (Exam)
Thank you for your interest in the graduate programs in Electrical and Computer Engineering, or ECE, at UC Davis!
Our ECE program is well-known for its outstanding education and pioneering research. Our faculty and researchers lead the way in creating innovative engineering methods and advancing a range of disciplines. Being situated near Silicon Valley keeps us informed about the latest trends in innovation, allowing us to offer cutting-edge education and numerous collaboration opportunities that facilitate the transformation of ideas into real-world products.
Have questions? For more information about the application process, requirements, and deadlines, please visit the Graduate Admissions page.
Degree Requirements
- General Requirements and Information
- Students should note that ECE program requirements are more stringent than those stated by Graduate Studies. The ECE program requirements, therefore, take precedence. Plan II requires thirty-six (36) units of upper-division and graduate coursework (see course requirements below), satisfactory performance on a comprehensive final examination, and a minimum of three-quarters of academic residence. A comprehensive final examination in the major subject is required of each candidate. No thesis is required. The capstone requirement is fulfilled by a capstone written report, and oral examination, on an appropriately comprehensive topic at the end of year two. All courses listed on the Program of Study must be passed with a “B-“ or higher. A course in which a student receives a “C+” or lower cannot be used to satisfy the unit requirement for the M.S. degree but will count in determining the grade point average.
Full-time students must enroll for 12 units per quarter including research, academic and seminar units. Courses may not be taken with the S/U option to fulfill course requirements, unless the course is normally graded as S/U. A student who elects Plan II can register for 299 research units and should do so while preparing for the Comprehensive Examination. The number of 299 units taken should reflect the amount of time and effort devoted to the preparation. Once course requirements are completed, students can take additional classes as needed, although the 12 units per quarter are generally fulfilled with a research course (299) and perhaps seminars. Per UC regulations students cannot enroll in more than 12 units of graduate level courses (200) or more than 16 units of combined undergraduate and graduate level (100, 200, 300) courses per quarter. - Course Requirements
- Thirty-six (36) units of upper-division and graduate coursework, satisfactory performance on a comprehensive final examination, and a minimum of three quarters of academic residence are required. At least 24 units must be letter-graded graduate Electrical and Computer Engineering 200 series courses (excluding EEC200, 29X seminar series, and EEC299). Not more than 1 unit of graduate seminar and 3 units of research (299 or equivalent) may be used to satisfy the 36-unit requirement. The remaining units must either be upper division technical or graduate courses. All courses listed on the Program of Study must be passed with a “B-“ or higher. A course in which a student receives a “C+” or lower cannot be used to satisfy the unit requirement for the M.S. degree but will count in determining the grade point average.
Courses required for the ECE undergraduate degree, or the following courses: EEC100, EEC110A/B, EEC130A/B, EEC140A/B, EEC150, EEC151, EEC161, EEC170, EEC172, and EEC180A/B, may not be used to satisfy the requirements of the ECE M.S. degree.
The summary requirements of Plan II are
♦ Course Requirements: 36 units minimum (100 and 200 series only)
♦ 24 units of letter-graded ECE graduate courses (200 series)
♦ Not more than 1 unit of graduate seminar may be used
♦ Not more than 3 units of EEC 299 research units may be used
♦ Courses with grades B- or better
Suggested Courses:
♦ Courses in Computer Engineering
♦ Courses in Information Systems
♦ Courses in Integrated Circuits and Systems
♦ Courses in Quantum, Photonics, and Electronic Devices
♦ Courses in RF-to-Terahertz
♦ Courses in Bio, Ag, and Healthy Technologies - Special Requirements
- All graduate students are required to take EEC290, Seminar in Electrical and Computer Engineering, each Quarter that it is offered. An S grade in EEC390, the Teaching of Electrical and Computer Engineering, is required to be eligible to hold a Teaching Assistantship in ECE, but may not be used to satisfy graduate coursework requirements. International students may need to take LIN25, LIN26, LIN391 or a combination thereof, to meet university language proficiency requirements.
- Committees
♦ Admission Committee
Once the completed application, all supporting materials, and the application fee have been received, the application will be submitted to the admissions committee. The admissions committee consists of the faculty members of ECE’s Graduate Study Committee (GSC) and the GSC Admissions Chair. Applicants who apply by the space available deadline (but after the general deadline) are not guaranteed to have their application reviewed by the graduate program. Their application will be reviewed only if the graduate program determines that they have additional space available. Based on a review of the entire application, a recommendation is made to accept or decline an applicant’s request for admission. The recommendation to accept or decline an applicant’s request for admission is forwarded to the Dean of Graduate Studies for final approval of admission. Notification of admissions decisions will be sent by Graduate Studies. Applications are accepted from the date the admission system opens (typically in September) through the space available deadline for the next fall-entering class♦ Course Guidance or Advising Committee
The MS Program Director and MS Graduate Advisors will provide general guidance to MS students and administer the MS program in consultation with the Graduate Program Chair.♦ Comprehensive Examination Committee for M.S. Plan II
Before advancement to candidacy, the student will declare an MS Comprehensive Examination committee. The MS Director will nominate the committee based on consultations with the student and the Major Professor. This committee is chaired by the Major Professor and made up of another ECE Graduate Program faculty member or the MS Program Director. The responsibility of this committee is to assist in the guidance of the student and to give the comprehensive exam and approve the final report.- Advising and Mentoring
The Major Professor is the primary mentor during the student’s career at UC Davis and will assist with developing the student’s Program of Study. One of the Graduate Advisors (also referred to as MS Graduate Advisors), will serve as the interim advisor to new students during the process of selecting a major professor. The Major Professor serves as the chair of the Comprehensive Exam Committee (for Plan II). The student must select a major professor from the members of the ECE Graduate Program as soon as possible, but no later than the beginning of the third quarter of enrollment. Changing a major professor, requires the signatures of the previous and new major professor, acknowledging the change.
Graduate advisors are appointed in compliance with the policies and procedures of the
Graduate Council and the Office of Graduate Studies, as described under the Graduate
Advisors Appointment section of the Graduate Program Roles and Responsibilities
webpage. The Graduate Program Chair in consultation with the Department Chair will
recommend graduate advisors to the Office of Graduate Studies for review and
appointment for a two-year term.The MS Program Director, who is nominated by the Graduate Program Chair in
consultation with the Department Chair and appointed by the Dean of Graduate Studies,
is a resource for information on academic requirements, policies and procedures, and
registration information until a Major Professor is selected. The MS Program Director is
responsible for reviewing programs of study for each student and acting on student
petitions.
The MS Program Director and MS Graduate Advisors will provide general guidance to
MS students and administer the MS program in consultation with the Graduate Program
Chair:a. Define their MS plan (I or II).
b. Review and approve the program of study for every MS student.
c. Review and action on each petition submitted by a MS student to drop or add
courses or to take courses on an S/U basis. Make recommendations on petitions of
graduate students to drop or add courses beyond the fifth week of classes.
d. Review and approve petitions for advancement to candidacy for the master’s degree
and recommendations for the composition of committees for master’s theses or
comprehensive examinations.
e. Periodic review of MS students’ progress towards degree objectives, and, in
particular, file an annual report with Graduate Studies concerning each student’s
progress toward completion of degree requirements. If necessary, initiate an interim
student progress assessment.
f. Recommend to the Graduate Program chair action on applications for admission of
MS students.
g. To arrange and chair at least four meetings per year of the MS Program Committee.
h. To provide orientation for all new MS students entering the program- Advancement to Candidacy
Every student must file an official application for Candidacy for the Degree of Master of Science and pay the Candidacy Fee after completing one-half of their course requirements and at least one quarter before completing all degree requirements; this is typically the third quarter. The Candidacy for the Degree of Master of Science form can be found online at: https://grad.ucdavis.edu/gradsphere. A completed form includes a list of courses the student will take to complete degree requirements. If changes must be made to the student’s course plan after they have advanced to candidacy, the MS Program Director must recommend these changes to Graduate Studies. Students must have the MS Program Director and Major Professor, if applicable, sign the candidacy form before it can be submitted to Graduate Studies. If the candidacy is approved, the Office of Graduate Studies will send a copy to the Graduate Program Coordinator, the student, and the Plan II Committee Chair. If the Office of Graduate Studies determines that a student is not eligible for advancement, the program and the student will be told the reasons for the application’s deferral. Some reasons for deferring an application include:
1. Grade point average below 3.0
2. Outstanding “I” grades in required courses
3. Or insufficient units.
- Exam Requirements
Comprehensive Examination (Plan II): Fulfillment of the Comprehensive Examination is the last requirement of the MS Plan II. The examination may be taken once the student has completed required courses and advanced to candidacy. The purpose of the exam is to demonstrate the student's ability to initiate and carry to completion a short
engineering project. The examination has two parts: an oral presentation and a written report.
The oral presentation consists of a seminar attended by the Comprehensive Examination Committee. After a formal presentation on the subject of the investigation, the Committee questions the student on that subject and on related topics. The topic of the written report is chosen by the Major Professor in consultation with the student. It can be a literature search, an in-depth study of a particular topic, theoretical and numerical studies, or a brief experimental investigation. The report is concise and follows the style of an IEEE paper. The report should be submitted to the exam committee at least two weeks prior to the exam. The Exam committee’s unanimous vote is required to pass a student on the exam. If a
student does not pass the exam, the committee may recommend that the student be reexamined a second time, but only if the MS Program Director concurs with the committee. The second exam must take place within one quarter of the first exam. The format of the second exam is the same as that of the first exam and may include the submission of an amended version of the report. The examination may not be repeated more than once. A student who does not pass on the second attempt is subject to disqualification from further graduate work in the program.
After passing the examination, a copy of the MS Plan II report must be submitted to the ECE Graduate Program Coordinator. The Master’s Report Form is signed by the MS Program Director and then forwarded to the Office of Graduate Studies. The deadlines for completing this requirement are listed each quarter in the campus General Catalog
(available online at the website of the Office of the Registrar). A candidate must be a registered student or in Filing Fee status at the time the program submits the form, with the exception of the summer period between the end of the Spring Quarter and the beginning of Fall Quarter. The program must file the report with Graduate Studies within one week of the end of the quarter in which the student’s degree will be conferred.- Normative Timeline
Careful adherence to the program guidelines presented above make it possible for a
student to complete all degree requirements in three quarters of graduate study. Some
students may take additional time to complete the master’s degree.
Typical Timeline and Sequence of Events: In order to make satisfactory progress, the
expectation is that full-time students in the MS Program will follow the timeline below.
The number in each column is the consecutive quarter of graduate enrollment. Students
not holding an ECE degree may require additional quarters of study to complete their
MS degree requirements depending on the number of remedial courses needed.
- Sources of Funding
- Sources of funding in the ECE Graduate Program include: ECE Graduate Program
fellowships, Graduate Student Researcher appointments and Teaching Assistantships.
Funding decisions related to fellowships are generally made by the graduate program or
Graduate Studies, depending on the source of funding for the fellowship. Not all
fellowship funding decisions are made by either the graduate program or Graduate
Studies; as examples, graduate students often seek fellowship funding directly from the
National Science Foundation, National Institutes of Health, foundations, and a range of
other agencies and organizations. Funding decisions related to Graduate Student
Researchers are made by the Principal Investigator of the source of funding. Teaching
Assistant appointment decisions are made by the Undergraduate Program Chair
approximately four weeks prior to the start of each quarter and are based, in part, on a
graduate student’s educational background, grade point average, academic standing,
degree objective, feedback from instructors, and recruitment status at the time of
entering the graduate program. Master’s students in Electrical and Computer
Engineering at UC Davis are typically self-funded or apply for graduate financial aid,
such as student loans. U.S. Citizens and Permanent Residents must file a FAFSA
annually in order to be eligible for graduate financial aid. Master’s students are welcome
to apply for fellowships, Teaching Assistant and Graduate Student Researcher
appointments. - PELP, In Absentia and Filing Fee Status
Information about PELP (Planned Educational Leave), In Absentia (reduced fees when
researching out of state), and Filing Fee status can be found in the Graduate Student
Guide: https://grad.ucdavis.edu/gradsphere.M.S. students are eligible for Filing Fee status after completing their coursework (Program of Study) and a working draft of their thesis or comprehensive examination report. In order to be approved for filing fee status, a student must submit the filing fee request along with signatures of all three members of the thesis committee or
Comprehensive Examination Committee stating they have received an acceptable
working draft of the thesis or comprehensive examination report. This application must
be routed through the ECE Graduate Program Coordinator for the ECE Graduate for the
MS Program Director’s approval and then must be filed with Graduate Studies. Filing
Fee is available for one quarter only, but extensions may be approved on a case-by-
case basis. In the event that filing fee status expires, the student must file a readmission
application Capstone Projects- Project: CeDP: Electrophysiological Recording System Fabrication
Sponsor: Professor Erkin Şeker
Description: Electrical activity of neural cells are commonly used in neuroscience to study behavior of neural circuits and individual neurons. In these applications, neural cells are grown on photolithographically patterned gold electrode traces over glass substrate (called microelectrode arrays, MEAs), where small voltage fluctuations of the cells are amplified, digitized, and recorded for subsequent analysis. This project involves the construction of the board on which MEAs can be reversibly mounted and interfaced with Intan amplifier/DAQ electronics (https://intantech.com/). The student(s) will collaborate with other graduate students working on the neuroengineering aspects of this project.
Requirements: PCB board lay-out, soldering, electrical testing, and interfacing with data acquisition instrumentation are required.
- Project: Characterization of Silicon Photodiodes for Precision Sensing Applications
Sponsor: Professor Soheil Ghiasi
Description: A large number of light-based precision sensing systems rely on silicon photodiodes (PD) as their sensors for which, accurate circuit model characterization is not available via commercial vendors. The goal of this project is to measure the output of a specific silicon PD under a number of known input conditions, and use the data to infer the parameters of the PD’s circuit model, such as dark current, shunt resistance, shunt capacitance, etc.
Requirements: Solid background in electrical circuit, and interest in data-driven analytics
- Project: Implementation of All Digital Phase-Locked Loops (PLL) on FPGAs
Sponsor: Professor Soheil Ghiasi
Description: Phase-Locked Loops (PLL) is a control system that generates an output signal whose phase is related to the phase of an input signal. PLLs are a key component of networking (and some precision sensing) applications. The goal of this project is explore FPGA IP blocks for implementation of All digital PLLs, and explore the tradeoffs involved in their implementation on FPGAs.
Requirements: Solid background in digital design with FPGAs; understanding of PLL operation will be helpful.
- Project: Model-Based Design of Signal Processing Blocks Targeting FPGAs and Microcontrollers
Sponsor: Professor Soheil Ghiasi
Description: The objective of this project is to explore model-based design of several signal processing blocks, such as standard filters and signal transformation modules, and their automated synthesis from Simulink and/or Matlab models targeting FPGAs and/or microcontrollers.
Requirements: Solid background in digital design with FPGAs, and digital signal processing
- Project: Complete Diode Characterization
Sponsor: Professor Anh-Vu Pham
Description: In this project, a student will fully characterize and model aspects of a diode. The student will measure the diode’s behavior when changing conditions such as bias voltage and frequency. The student will then analyze this data in order to extract the intrinsic and parasitic characteristics of the diode. Lastly, the student will validate these characteristics by modeling the diode in a circuit simulation software and comparing the model’s simulated results with the measured results.
Requirements: Basic circuit knowledge; basic programming skills; basic circuit simulation software skills
- Project: Voltage-Controlled Oscillator Design
- Sponsor: Professor Anh-Vu Pham
Description: A voltage-controlled oscillator (VCO) is a critical component in communications circuits. Often, a VCO’s performance is limited by its phase noise. For this project, a student will use computer-aided-design tool to design a VCO at microwave frequencies to achieve low phase noise. The student will design and analyze a variety of circuits and study trade-off in phase noise.
Requirements: Basic circuit knowledge; knowledge in circuit design software - Project: Educational Computer Game Development
- Sponsor: Professor Erkin Şeker
Description: There is a need for educational tools that can reach to a growing number of students and the general public with minimal resources to access laboratory courses that require expensive research infrastructure, such as a microfabrication facility. In order to address this need, we have developed an educational computer game that simulates a microfabrication laboratory and teaches the essential techniques such as wet chemistry and photolithography, in an interactive manner. The goal of this project is to continue improving this game and/or start other educational games for teaching different laboratory techniques (e.g., analytical chemistry, biology, etc.).
Requirements: Programming with Unity3D or willingness to learn how to program in Unity3D - Project: On Chip Leaky-Wave Antennas
- Sponsors: Professors J. Sebastian Gomez-Diaz and Omeed Momeni
Description: This project deals with the analysis, design, fabrication and characterization of broadband composite right/left-handed leaky-wave antennas operating from 50 GHz to 100 GHz. The first step will be to analyze and design a unit-cell of this type of antennas using numerical simulations. Then, the response of an entire antenna composed of dozens of unit-cells will be investigated in terms of efficiency and tunable radiation patterns. After fabrication, the device will be measured and characterized. Finally, the leaky-wave antenna will be combined with non-Foster circuits to significantly enhance its operational bandwidth and enable its use in radar systems and future communication networks.
Requirements: Basic knowledge of electromagnetic waves and electronic circuits. Experience with full-wave simulation software (such as HFSS/CST) would be great but it is not required. It is a project for 1~2 students. - Project: Implementation of tunable coherent sources for fast multi-spectral time resolved fluorescence spectroscopy and imaging
Sponsor: Professor Diego R. Yankelevich
Description: Fluorescence spectroscopy is a powerful technique for in vivo tissue diagnosis. Of particular interest for clinical applications, time and wavelength-resolved fluorescence spectroscopy has proven to be a reliable technique for tissue characterization since it is capable of determining multiple parameters including fluorescence intensity, spectrum, and lifetime. We propose the development of compact sources of tunable radiation between 400 and 450 nm (violet-blue), to be used in fluorescent spectroscopy, that are based on cascaded nonlinear wavelength conversion using a periodically poled lithium tantalite pumped by microchip Q-switch lasers. The microchip laser monolithic construction, where the laser crystal is directly contacted with the end mirrors, makes them very compact and alignment-free. Such lasers will be pumped with laser diodes either directly or via an optical fiber and will emit pulses of between 5 and 1000 mJ pulse energy, pulse widths in the nanosecond to sub-nanosecond range and repetition rates from single-shot to hundreds of kHz. Their simple and compact construction, as well the use of widely available inexpensive pump laser diodes, makes them reliable at a fraction of the cost of amplified fiber lasers. The infra-red pulses generated by the micro-chip lasers will be converted to the blue spectral range by using cascaded nonlinear interactions using a single a periodic nonlinear crystal to obtain optical parametric oscillation and sum-frequency generation.
Requirements: Undergraduate courses which examine plane wave electromagnetic wave propagation, electrical and electronic circuits. Interfacing with scientific instruments using LabView or similar platform. ECE236 and ECE237A concurrently.
- Project: Target brain stimulation using surface electrodes
Sponsor: Weijian Yang (ECE)
Description: Delivering electrical field into the brain for stimulation has been shown to be effective to treat depression, stroke, dementia and several other medical conditions. The existing brain electrical stimulation paradigms either rely on electrodes implanted deep into the brain or surface electrodes on the skull. The former approach is highly invasive whereas the latter one lacks a spatial specificity. Recently, a new technology utilizes temporal interference of fields from multiple surface electrode pairs to noninvasively stimulate specific brain regions. In this project, we will optimize the design parameters of such temporal interference system to further increase the spatial specificity of the stimulation region, through finite element method simulation. We will also build a prototype of this electrical stimulation system and test it on rodents.
Requirements: Electronic circuits, Electromagnetic waves, Matlab. It is a project for 1~2 students.
- Project: Semi-Autonomous Wall-Climbing Robot for Marking on Vertical Walls
Sponsor: Professor Saif Islam
External Sponsor (potential): Professor Aykutlu Dana
Description: The objective of this project is to create a vehicle that is capable of following a trajectory on a flat surface programmed by the students. The system would be equipped with robust and reliable navigation system and will host a device to draw preprogrammed linear and curvilinear lines using a marker on the surface at precise positions. Additional devices will be used to sense and apply pressure on the drawn lines at varying speed with a goal of erasing the lines. The vehicle is expected to operate both on horizontal as well as vertical flat surfaces. The positioning of the system will be based on remote sensing of the position and orientation of the vehicle using real-time image processing and 3D scene generation. A stereoscopic 3D capture camera (Kinect) along with OpenCV or Matlab code will be used to extract scene and vehicle information. Luminescent markers on the vehicle will be utilized using mathematical framework borrowed from super-resolution localization microscopy to accurately estimate position and trajectory of the vehicle. The project will involve robot design, sensing, motion planning and control, mapping and localization functionality. The students will build model using a 3D printer, servos and microcontrollers with wireless connectivity. The students will familiarize with Python libraries, microcontroller programming and sensor interfacing, image processing and feature extraction, real-time feedback and feedforward control and 3D scene generation.
Requirements: Programming in Python, Matlab, OpenCV. Register for EEC 289K in Winter or Spring 2019.
- Project: Implementing Domain Specific Accelerators for RISC-V
Sponsor: Professor Venkatesh Akella
Description: The discipline of computer architecture is witnessing two dramatic, potentially game changing trends, just as the demand for computation is growing exponentially with machine learning and data-driven-everything. First is the end of Moore’s law and the second is the emergence of an open source computer architecture movement (analogous to Linux in the OS community) based on RISC-V. The future of computer architecture will involve creating domain specific architectures centered around a processing core to improve the performance of a set of closely related applications. In this project, we will explore designing and programming domain specific accelerators for emerging applications in machine learning and computer security based on RISC-V and prototyping them on a FPGA or the Amazon Cloud.
Requirements: You should have taken EEC 270 or equivalent (graduate course in computer architecture) and also EEC 298 in Spring 2019. Ideally, we are looking for a group of 2 or 3 students.
- Project: Non-intrusive Detection of Human Motions or Vital Data using WiFi/Bluetooth
Sponsor: Professor Zhi Ding
Description: Wi-Fi networks are widely available for communication purposes. Interestingly, the ability to detect motion and extract vital animal information has also been recently demonstrated. In this project, we shall build a testbed and experiment with the use of WiFI/Bluetooth for motion detection and subject monitoring with the intrusive video camera. It is important to see whether such technologies can detect simple gestures and detect potentially risky behavior or symptoms of illness. This project contains both software and hardware aspects.
Requirements: Familiarity with common programming languages such as C, C++, Python. Courses in Signals, Systems, Communications, and Networking. Candidates will be interviewed by the Faculty mentor. Ideally, we are looking for a group of 2-3 students.
- Project: Designing GPU-Efficient Algorithms for LLM Inference
Description
The boom of LLM inference serving has exacerbated inefficiencies in GPU utilization. The self-attention layer of Transformers becomes heavily memory bound during auto-regressive inference (one token at a time). The computational patterns result in the GPU having lots of idle time, waiting on large activation tensors (KV cache) to load from memory.
The purpose of this project is to help research and productize new linear algebra techniques that compress these large activations. Our goal is to accelerate inference request latency and save memory space, while preserving model accuracy on industry standard benchmarks. We are designing custom GPU kernels that achieve a speedup by operating on these compressed activation tensors. This is all wrapped inside of a drop-in PyTorch layer, with no extra training required. The work itself is a co-design of the full DL software stack, from PyTorch frameworks all the way down to GPU assembly code. Be prepared to get your hands dirty!
What you can expect:
- Learn about industry challenges and constraints around LLM inference serving.
- Contribute to building out our inference framework support.
- Run and manage hyper-parameter sweeps across language benchmarks and models to validate speed and quality.
- Learn state-of-the-art techniques for writing GEMM GPU kernels.
- Help with profiling and debugging performance issues, iterating on GPU kernel design.
Requirements
- Fundamentals of machine learning, deep learning, linear algebra.
- Basic understanding of modern GPU architectures.
- Some familiarity writing and profiling GPU kernels (CUDA/ROCm C++).
- Experience using PyTorch for inference on large datasets.
- (Preferred) Knowledge of the Transformer architecture, and the uses of various types of attention mechanisms
- (Preferred) Experience working with heavily templated C++ codebases.
How to Apply: Send an email to Cameron Shinn at [email protected] with "MS Project" in the subject line. Include (1) a statement of interest, (2) a brief summary of your qualifications and (3) an attached copy of your CV or resume.