PhD Awards and Honors

Outstanding Dissertation Award

Presented in recognition of scholarly excellence


Qitong Gao

Qitong stands out as one of the most exceptional PhD students I've had the privilege of working with.  His groundbreaking contributions to automated decision-making in healthcare demonstrate not only a profound grasp of machine learning theory but also an extraordinary talent for translating these concepts into impactful real-world solutions.  Qitong is the 1st student I have seen throughout my academic career who has demonstrated algorithmic frameworks that transcend traditional domain boundaries while delivering tangible improvements in healthcare applications, e.g., improving the current deep brain stimulation therapy for treating Parkinson's disease with practical outcomes justified in clinics with real Parkinson's partients.  Qitong's work represents a rare combination of academic excellence, practical innovation, and collaborative leadership.  His achievements not only advance our understanding of automated decision-making but also hold the potential to transform healthcare delivery for the better.


Jessica Centers

Jessica’s dissertation, entitled "Applied Millimeter Wave Radar Vibrometry," is a groundbreaking work that pushes the boundaries of millimeter‐wave radar technology in its applications in wireless communications and non‐acoustic human speech analysis.  One of the most compelling aspects of Jessica's dissertation is the development of a completely new form of wireless communications called Vibrational Radar Backscatter Communications (VRBC).  This approach allows mmW radars, such as those in most automotive advanced driver assistance systems, to receive messages encoded in the vibration of transponding surfaces.  Her results and analyses position VRBC as a desirable solution in spaces like X2V, offering unique benefits over commonly considered higher rate solutions such as direct short‐range communications (DSRC) which face challenges related to spectrum allocation, interference, security, and infrastructure cost.

Ang Li

Ang’s dissertation, titled "Enable Intelligence on Billion Devices with Deep Learning", stands out as a testament to his exceptional research abilities and commitment to the field of Electrical and Computer Engineering.  His dissertation focuses on the development of large-scale networked and trustworthy edge intelligent systems, aimed at addressing practical challenges in a collaborative, scalable, secure, and ubiquitous manner. His research has directly contributed to numerous advancements in the fields of edge computing, federated learning, privacy, and security.  For example, his design of revolutionary secure, computation and communication-efficient federated learning frameworks have served as the foundation for other independent research studies, and also became the state-of-the-art method in this field. In addition, Dr. Ang Li also introduced the groundbreaking privacy-respecting data crowdsourcing framework for deep learning, as well as privacy-preserving techniques for online machine learning services.


Zhongxi Li 

As his main research topic, Zhongxi worked on medical device technology, specifically technology to noninvasively activate neurons in the brain. Instead of incrementally following the trends in the field and pushing the boundaries, he designed quite radical techniques to bypass the problem of limited focality of electromagnetic fields in the low-frequency range where neurons are susceptible. He developed an understanding and the necessary technology to use the type-specific activation dynamics of neurons to shift the balance of activation between neuron populations in the focus. That step, however, required the development of fundamentally different high-power electronic circuit concepts since conventional power electronics considered the problem of generating an arbitrary high-bandwidth output at high power as not solvable with existing circuits and semiconductors. This concept has now already been taken up by various other groups and several companies evaluate its commercialization.

Furthermore, Zhongxi developed a strong affection for energy and power topics, which he initially only pursued as his unrelated personal interest. He designed a novel concept to turn conventional hard-wired batteries into dynamically reconfigurable systems using only relatively low-cost low-voltage electronics to reach high power levels. Such reconfigurable batteries can for the first time solve the major problem of the large manufacturing tolerances of battery cells. In conventional batteries, the weakest cell determines the overall battery performance with respect to power, capacity, aging, and terminal damage. Zhongxi’s reconfigurable battery circuits can rapidly change the series and parallel configuration of its subunits to control charge, power, aging potential, and heat, while even bypassing broken elements at little extra cost. As this limitation is gone in reconfigurable batteries, which can further dynamically adjust their output voltage and even generate AC, Zhongxi’s concepts have started a new research field. Leading companies from the automotive and large silicon-valley technology companies are currently taking up this idea.

In addition to the first two contributions, which have already left a likely long-lasting impression on research and our actual world as products using such technology emerge, several courses here at Duke inspired his interest for unbiased statistics and estimation theory. Instead of only studying existing methods and applying them as an amateur, he again was eager to bring his work to a professional level so that he could himself successfully make a contribution to the field. He designed an estimator for neural responses to brain stimulation, which has substantially higher sensitivity than any method known in the field, is unbiased, and even achieves maximum-likelihood properties. With that method, Zhongxi could further demonstrate that excitatory responses to brain stimulation happen already at very low stimulation amplitudes and that what was previously considered the stimulation threshold in noninvasive brain stimulation and used as dosage parameter for all related diagnostic and treatment applications, is rather in the middle of the dose response curve.


Linghao Song

In his PhD study, Linghao’s research focus is computer architecture and acceleration for deep learning and graph processing. He contributed to 29 publications on top venues including 1 ISCA, 4 HPCA, 5 DAC, 2 ICCAD, 5 DATE, 4 ASP-DAC and others. His Google Scholar profile records 885 citations and one of his works PipeLayer has been cited more than 300 times and is the most cited one among all papers in HPCA’17. He is also very active in serving the research community, including serving on the committee of 9 IEEE/ACM conferences and serving as a reviewer for 15 IEEE/ACM/Elsevier journals. He also mentored several female and undergraduate students in research and their works got accepted to top venues such as DAC, DATE. Linghao demonstrates diversified success of a Duke ECE PhD student.


Joseph Andrews

There are rare times when a PhD student manages to succeed in every possible area of dissertation-related work; such was the case for Joseph "Joey" Andrews. In his four years as a PhD student at Duke, Joey was able to invent a now-patented sensor technology that led to a funded startup company, publish multiple papers in high-profile journals, win the best paper award at a top conference in his field, be selected as an NIH fellow based on a research proposal that he wrote, mentor countless graduate and undergraduate students, and make numerous discoveries that continue to be transformative for ongoing research in the field.  His multitude of accomplishments made Joey an attractive candidate for faculty positions and he began as an assistant professor at the University of Wisconsin-Madison, a top engineering school, directly out of his PhD. Truly, Joey embodies that level of diversified success that we strive for in Duke ECE.

Junfei Li

By both objective and subjective metrics, Junfei brought a wide range of technical skills, from theory to experimental implementation, and technical fearlessness to his research. His research work as a PhD student resulted in a remarkable variety of notable publications in the field of acoustic metamaterials and wave propagation theory. That body of work has already had real impact and influence, and he received internal recognition through a John Chambers Scholar fellowship through Duke's Fitzpatrick Institute for Photonics. His most significant contributions were in the area of new paradigms for acoustic metamaterial design and in the development of tools to analyze and design them. His Google Scholar citation record (h=13, n=730 citations) demonstrates overall research impact that would be enviable for an assistant professor being considered for tenure, much less a PhD student less than one year from his defense. Junfei was an excellent student in all aspects of his PhD work at Duke; and the breadth, quality, volume, and impact of the research contained in his dissertation was very high.


Mohamed Ibrahim

Mohamed’s research interests include EDA and Optimization Techniques; Formal Methods and Applied Machine Learning; System-on-Chip Design and Testing; Microfluidic Biochips, etc. In this five-year PhD study, Mohamed coauthored two books, three book chapters, 15 journal papers (nine on the flagship journals in his area, IEEE society TCAD, on on Proceedings of IEEE, the flagship magazine of IEEE, and on on TC), and 18 conference papers on the top venues. His works also include four keynote/feature/spotlight papers and a Best Paper Award from the largest conference in Europe. During his study, Mohamed worked on four different but also integrated topics spanning from health, security, and CPS using microfluidic chips; which construct a comprehensive and systematic research work. Mohamed received the 2018 Council of Graduate Schools/ProQuest Distinguished Dissertation Award. The depth and breadth of Mohamed’s research serve as a true exemplar of a Duke ECE PhD student.

James Thostensen

James’s dissertation was scientifically exceptional and simultaneously has immense potential for social impact. This is a rare combination and, coupled with the excellent research required to obtain these results, make his dissertation truly stand out. The focus of Jimmy’s dissertation was to understand the material, electrochemical, and biological mechanisms required to efficiently disinfect liquid human waste, otherwise known as blackwater, for developing countries. Funded by the Bill and Melinda Gates Foundation’s Reinvent the Toilet Challenge, the application of Jimmy’s dissertation research was to develop a blackwater disinfection system that could be powered in “off-grid” locations, has a long service-lifetime, does not need additional chemicals for sanitation, and can be operated for less than 5 cents per user, per day. The scientific accomplishments and future social impact of James’s research make his dissertation truly outstanding.

Outstanding Service Award

Presented in recognition of extraordinary service to Duke ECE


Natalie Ann Rozman

Natalie is a perfect example of a student going above and beyond to give back to the Duke and ECE communities during her time in the program.  She has helped with countless recruitment events, organized student social events, and put in the place many of the organizational structures of the current graduate student leadership group, EASE (ECE Advocacy for Student Engagement).  She has spearheaded many events and programs that promote diversity, equity, inclusion, and community, some of which include ECHO (ECE College-High School Opportunity) and the Graduate Student Application Workshop.  These events show Natalie's desire to provide support to prospective students in the community with a focus on underrepresented groups.  During her involvement with EASE, they were selected to receive the 2022 Dean's Award for Inclusive Excellence in Graduate Education.  The ECE Advocacy for Student Engagement program was chosen from a highly competitive pool of nominees for its consistent and intentional creation of an environment that demonstrates and is dedicated to exemplary inclusiveness and diversity in graduate education and the broader community.  We are going to miss her terribly, but she can be assured that our department is only better because of her collaboration and support of our graduate students.


No award was given.  An additional Outstanding Dissertation Award was given as an alternative. 


Huanrui Yang

During his Ph.D. study, Huanrui served as a TA for 5 semesters, including ECE 550D Fundamentals of Computer Systems and Engineering (Fall 2018), ECE 681 Pattern Classification and Recognition (Spring 2019), and ECE 590 / ECE 661 Computer Engineering Machine Learning and Deep Neural Nets (Fall 2019, Fall 2020 & Fall 2021). ECE 661 was a new course, first offered in Fall 2019. Huanrui contributed his expertise to the course's design and served as the lead TA over subsequent semesters. The help from Huanrui was essential in making ECE 661 well-received by graduate and undergraduate students; the upcoming offering in Fall 2022 has more than 100 students enrolled. Huanrui is also leading the effort to draft a textbook for the course, which could have a broader impact on ECE education in the future. 

Huanrui received top ratings and outstanding evaluation feedback from the students every semester that he TA'd. Moreover, multiple students expressed their intention of nominating Huanrui for a Departmental TA award, stating him to be “the best TA I have met in Duke ECE,” “dedicated, helpful and knowledgeable, very well deserved to be nominated,” and saying “he went above and beyond in TAing.” Besides teaching, Huanrui has mentored the research of multiple graduate and undergraduate students in the group.

Huanrui served as a reviewer for IEEE TNNLS, IEEE TCAD, Elsevier Computers & Security, Elsevier Neurocomputing, and multiple top conferences, including ICLR, ICML, NeurIPS, CVPR, MLSys, and TinyML etc. He was selected to receive a NeurIPS 2021 Outstanding Reviewer Award given to the top 8% of reviewers.


Runren Zhang

Runren Zhang has shown outstanding service to the department. He served as a TA for 551 for four semesters and for 571 for one semester. He was always friendly and approachable with students and it was really valuable to the class to have a TA with such thorough expertise.


Tamara Lehman 

Tami was the kind of student who would offer to help with an event before anyone even realized help was needed. She became a go-to volunteer for every type of event. In addition to fruitful involvement in Duke’s ACM-W chapter and the Triangle’s GWIS chapter, Tami was a dream recruiter for the ECE department – brilliant, hard-working, engaged in her work, aware of the greater Duke and engineering communities – we couldn’t have asked for a better representative of the type of students we want to recruit to the ECE Department. Tami also came to the rescue for ECE as a repeat TA. We asked her to TA many more times than the average student, because of her expertise in a variety of important classes. And of course, also because she was fantastic TA!