Recent PhD graduate Dr. Janani Sundaresan has been awarded Waterloo’s 2026 Alumni Gold Medal in recognition of exceptional academic achievements during her doctoral studies. Conferred by Alumni Relations, the award consists of a 24-karat gold-plated medal embossed with the University of Waterloo’s seal. Since 1970, the Alumni Gold Medal has recognized outstanding graduating students at convocation.
“Janani’s dissertation exemplifies exactly what an excellent thesis in our field should look like,” said Professor Sepehr Assadi, Janani’s PhD supervisor. “It makes foundational advances on longstanding open questions, brings genuine originality in ideas and methods, and demonstrates exceptional technical rigour. Importantly, it also offers a coherent contribution that changes how a research area approaches its central questions, with exposition that makes difficult ideas accessible to others.”
Left to right: Dr. Janani Sundaresan and Professor Sepehr Assadi
Janani Sundaresan defended her PhD in Computer Science in May 2026. Her dissertation, New Techniques for Lower Bounds in Graph Streaming and Distributed Computing, investigates the fundamental limitations of algorithms for processing large graphs, particularly in streaming and distributed computational models that arise naturally in the design of algorithms for the massive graphs that are ubiquitous in practice today. In 2024, she received the Faculty of Mathematics Graduate Research Excellence Award for her work on streaming algorithms for approximate matchings.
Dr. Sundaresan is currently a Faculty Fellow at New York University’s Courant Institute of Mathematical Sciences.
More about Dr. Sundaresan’s PhD dissertation
Dr. Sundaresan’s dissertation confronts a defining question of modern computation: what is fundamentally achievable when data grows so vast that the basic assumptions of classical algorithm design no longer hold? She studied this question through a theoretical lens in two central models for processing massive graphs — graph streaming, where the constraint is the memory of the algorithm, and the CONGEST model of distributed computing, where the constraint is the communication bandwidth. Her work established the minimum resources algorithms require to solve fundamental problems, including the number of passes over the data, computational rounds, memory space and communication costs.
In an era of ever-larger data and ever-faster algorithms, lower bounds identify the barriers that no amount of engineering can overcome. Her results do more than close gaps. They define the true frontier of computation on massive data. Thus, the central contribution of Dr. Sundaresan’s dissertation is a general framework for establishing impossibility results, also known as lower bounds, for several fundamental problems. This framework has led to the resolution of several longstanding open questions in both graph streaming and distributed computing. As an example, her work established the exact number of passes over the input that any small-space algorithm needs for fundamental graph problems such as maximal independent set and maximum matching.
The impact of Dr. Sundaresan’s work is reflected in its publication record. The seven papers forming the foundation of her dissertation have been presented at top theoretical computer science conferences, including the ACM Symposium on Theory of Computing (STOC), the IEEE Symposium on Foundations of Computer Science (FOCS), and ACM-SIAM Symposium on Discrete Algorithms (SODA), as well as in the Journal of the ACM and the SIAM Journal on Computing. Notably, her STOC 2024, SODA 2025, and FOCS 2025 papers each received invitations to special journal issues, an honour typically reserved for the top 5 to 10 percent of accepted papers.
Seven papers form the core of Dr. Sundaresan’s thesis
Hidden Permutations to the Rescue: Multi-Pass Semi-Streaming Lower Bounds for Approximate Matchings. Sepehr Assadi, Janani Sundaresan. FOCS 2023 (research recognized with the 2024 Faculty of Mathematics Graduate Research Excellence Award)
O(log log n) Passes is Optimal for Semi-streaming Maximal Independent Set. Sepehr Assadi, Christian Konrad, Kheeran K. Naidu, Janani Sundaresan. STOC 2024 (invited to the SICOMP special issue)
Settling the Pass Complexity of Approximate Matchings in Dynamic Graph Streams. Sepehr Assadi, Soheil Behnezhad, Christian Konrad, Kheeran Naidu, Janani Sundaresan. SODA 2025 (invited to the TALG special issue)
Distributed Triangle Detection is Hard in Few Rounds. Sepehr Assadi, Janani Sundaresan. FOCS 2025 (invited to the SICOMP special issue)
Optimal Communication Complexity of Chained Index. Janani Sundaresan. Innovations in Theoretical Computer Science Conference 2025
Better Bounds for Semi-Streaming Single Source Shortest Paths. Sepehr Assadi, Gary Hoppenworth, Janani Sundaresan. Proceedings of the 2026 Annual ACM-SIAM Symposium on Discrete Algorithms
Settling the Pass Complexity of Streaming Set Cover. Sepehr Assadi, Janani Sundaresan. STOC 2026