NTT Research Congratulates Simons-Berkeley NTT Research Fellows

By NTT Research

NTT Research congratulates the incoming class of Simons-Berkeley Research Fellows, in particular, the three computer scientists who have also been designated NTT Research Fellows: Cynthia Rush, Andrea Lincoln and Umang Mathur.

Each year the Simons Institute for the Theory of Computing, an independent research organization on the UC Berkeley campus devoted to collaborative research in theoretical computer science, invites exceptional young scientists to apply for a competitive fellowship that allows them to participate in at least one of the ongoing programs at the Institute. The Simons Institute offers up to 16 fellowships each semester.

As an industrial partner to the Simons Institute, NTT Research is honored to have three such scientists also named NTT Research Fellows. Other industrial partners to the Simons Institute are Microsoft, Google and VMware. After the fellowships begin in the fall or spring semesters, NTT Research will invite the Fellows to deliver an initial talk and meet with other researchers. More engagement with the NTT Research Cryptography & Information Security (CIS) Lab will be arranged on an individual basis.

We congratulate these Simons-Berkeley/NTT Research Fellows for their achievement and look forward to learning more about their ongoing research in due time. Meanwhile, here is more background, including ongoing areas of research, semester of participation, current affiliations and recent publications:

Cynthia Rush – Probability, geometry and computation in high dimensions. Fall 2020. For the past three years Dr. Rush has been an assistant professor in the department of statistics and an affiliated member of the Data Science Institute, both at Columbia University. She has a Ph.D. in statistics from Yale University. Her recent publications include: “Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing,: NeurIPS 2019; “Analysis of Approximate Message Passing with Non-Separable Denoiser and Markov Random Field Priors,” IEEE Transactions on Information Theory, Vol. 65, No. 11, November 2019; “The Error Probability of Sparse Superposition Codes with Approximate Message Passing Decoding,” IEEE Transactions on Information Theory, Vol. 65, No. 5, May 2019; and “Spatially Coupled Sparse Regression Codes with Sliding Window AMP Decoding,” Proceedings of the IEEE Information Theory Workshop (ITW) 2019.

Andrea Lincoln – Satisfiability: Theory, Practice and Beyond. Spring 2021. Ms. Lincoln will be a postdoctoral researcher at UC Berkeley this fall. She will graduate with her Ph.D. in Computer Science at MIT in the summer of 2020 and holds two master’s degrees in computer science (Stanford and MIT). Her recent work includes two publications in the Innovations in Theoretical Computer Science Conference, ITCS, 2020: “Algorithms and lower bounds for cycles and walks: Small space and sparse graphs,” and “Monochromatic triangles, intermediate matrix products, and convolutions.” Other publications include “New Techniques for Proving Fine-Grained Average-Case Hardness”, FOCS, 2020; “Faster Random k-CNF Satisfiability, ICALP, 2020; “Public key cryptography: in the fine-grained setting,” CRYPTO, 2019; and “Cache-adaptive exploration: Experimental results and scan-hiding for adaptivity,” in Proceedings of the 30th Symposium on Parallelism in Algorithms and Architectures, SPAA 2018, pp. 213-222, NY, NY, 2018, ACM.

Umang Mathur – Theoretical Foundations of Computer Systems. Spring 2021. Mr. Mathur is a Ph.D. candidate in computer science at the University of Illinois at Urbana Champaign (UIUC). His recent publications include “Atomicity Checking in Linear Time using Vector Clocks,” Proceedings of the 25th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2020 [forthcoming]; “Deciding Memory Safety for Single-Pass Heap-Manipulating Programs,” Proceedings of the ACM on Programming Languages (POPL), 2020 [forthcoming]; “Decidable Verification of Uninterpreted Programs,” POPL, 2019; and “Data Race Detection on Compressed Traces,” Proceedings of the 26th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) 2018 (ACM SIGSOFT Distinguished Paper Award.) Mr. Mathur is recipient of a Google Ph.D. Fellowship (2019).

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