Saikat Dutta, Saurabh Jha, Cong Ximon Xie, Jiyong Yu, and Umang Mathur have received PhD fellowships from industry sponsors that recognize innovative research and provide generous financial support.
Five Illinois CS doctoral students have received prestigious PhD fellowships from industry sponsors—Facebook, Google, IBM, J.P. Morgan Chase, and Microsoft—that recognize innovative research and provide generous financial support.
Saikat Dutta was one of 36 doctoral students from 22 different universities worldwide who received a 2020 Facebook Fellowship. Dutta’s research interests lie broadly in the domain of program analysis and software testing; he is a member of Sasa Misailovic’s research group.
Dutta is currently working on developing techniques to test and debug probabilistic programming languages and machine learning frameworks and improve their reliability. In the past three years, he has published and presented his research at ISSTA ’20, ESEC/FSE ’18, and ESEC/FSE ’19.
This summer, he interned at Microsoft Research, Redmond, in the RISE group, where he worked on harnessing program analysis, big code, and machine learning techniques to automate environment modeling to significantly boost static analyzers for security and reliability.
Facebook Fellowship recipients receive tuition and fees paid for up to two academic years and a $42,000 stipend, which includes conference travel support. After he graduates in 2022, Dutta plans to pursue a career in research.
Saurabh Jha was one of 24 doctoral students worldwide who received a 2020 IBM PhD Fellowship. A member of Electrical and Computer Engineering professor Ravi Iyer’s research group, Jha is designing model-driven machine learning techniques for building robust autonomous systems, including frameworks for managing, monitoring, and assessing computers systems that use machine learning techniques.
A highlight of his work was bringing together probabilistic graph models (PGMs) with real-time data from high-speed networks and filesystems to detect and isolate performance and reliability problems. This work, supported by Sandia and the Department of Energy, became the foundation for work on the IBM Cloud, which he developed and implemented while working as a summer intern at IBM in 2019.
Jha, who expects to earn his doctorate in 2021, has presented his research results at top systems conferences, including USENIX Symposium on Networked Systems Design and Implementation and the IEEE/IFIP International Conference on Dependable Systems and Networks.
The 2020 IBM PhD Fellowship Award Program received hundreds of applications from 140 universities in 31 countries. Applications were reviewed by eminent technologists from across IBM. 2020 Fellowship recipients at U.S. universities will receive $35,000 for living expenses, travel and conference fees, as well as $25,000 toward their education.
Umang Mathur received a 2019 Google PhD Fellowship in the area of programming technology and software engineering. He is developing automated techniques and tools for detecting subtle concurrency bugs in multi-threaded programs such as web browsers and computer games. Concurrency bugs like data races and deadlocks can cause memory corruption, security vulnerabilities, and diminished user experience.
His research has been published in several top programming languages, software engineering, and logic conferences, including PLDI, POPL, ASPLOS, OOPSLA, ESEC/FSE, CAV and LICS.
During the summer of 2018, Mathur worked as a software engineering intern at Google, contributing to a project to improve time series forecasting for ads. During the summer of 2019, he worked as a research intern at Facebook, where he helped software developers isolate and interpret root causes behind app crashes.
In his second year of the three-year Fellowship, Mathur receives $75,000 to cover tuition, a stipend and travel expenses. A member of professor Mahesh Viswanathan’s research group, Mathur expects to graduate in 2020. He will begin work at the National University of Singapore as an assistant professor of computer science in the fall of 2021 after spending a year at Facebook as a research scientist and as a Simons Institute Research Fellow.
Mathur has earned other recognition for his work, including the 2019 Mavis Future Faculty Fellowship award from the Grainger College of Engineering, 2019 C.W. Gear Outstanding Graduate Student Award from the Computer Science department, and 2018 ACM SIGSOFT Distinguished Paper Award at ESEC/FSE. He has also been invited to the 8th Heidelberg Laureate Forum (to be held in 2021) as a young researcher.
Cong Simon Xie received a 2020 J.P. Morgan AI Research PhD Fellowship. Xie’s research aims to make distributed machine learning systems secure from attackers and enhance the efficiency of federated machine learning.
Federated machine learning refers to the process of training global models on private data sources without moving all the data to a central server. This process introduces the possibility of the model trainer encountering unreliable data sources (e.g. a malicious device user or web page owner could poison the data).
Xie is developing a new generation of machine learning algorithms that tolerate unreliable data sources while having efficient communication. His work is valuable to the financial services industry, which applies federated learning models on datasets from banks, credit agencies and insurance companies to detect fraud and calculate credit ranking without sharing data between these organizations.
Xie, who expects to graduate in 2021, is advised by CS faculty Indranil Gupta and Oluwasanmi Koyejo. He has presented his research results at leading conferences such UAI’19, ECML-PKDD’19, ICML’19, ICML’20
Jiyong Yu was one of 10 doctoral students across North America to receive a 2020 Microsoft Research PhD Fellowship. Yu is designing high-performance hardware systems that defend against microarchitectural side and covert channel attacks like Spectre and Meltdown, which involve a fundamental security vulnerability affecting most microprocessors, where a malicious program can exploit speculative execution and caching to gain access to data that was previously considered secure.
Yu’s approach is unique in the computer architecture community. Rather than design point defenses to specific side or covert channels like cache, he developed a holistic solution that blocks data leakage through every hardware structure. His solution drew the interest of Intel, which hired him in the summer of 2019 as a research intern
Working with Intel’s Security and Privacy Research Group, Yu modeled various side channel mitigations on the company’s CPU simulator.
He is also developing a hardware framework that targets side channel attacks based on speculative execution. He presented this work at the 2019 ACM/IEEE International Symposium on Microarchitecture, where he received a best paper award.
A member of assistant professor Christopher Fletcher’s research group, Yu plans to graduate in 2022. His Microsoft Fellowship provides a stipend and travel funding worth $42,000 for each of the next two years.