Doctoral Degrees Conferred

Search

Academic Year: 2025-2026

Name	Thesis Advisor(s)	Thesis Title
Adithya Abraham Philip	Justine Sherry	Accurately Parameterizing Internet Performance Testing for Realistic Evaluations
Dorian Chan	Matthew O'Toole	Holographic Illumination for Computer Vision
Jun-Ting Hsieh	Pravesh K. Kothari	Algorithms and Explicit Constructions via Spectral Techniques
Suhas Jayaram Subramanya	Greg Ganger	Efficient and Responsive Job-Resource Co-adaptivity for Deep Learning Workloads in Large Heterogeneous GPU Clusters
Meng-Chieh Lee	Christos Faloutsos, Leman Akoglu	Explainable Mining of Graphs and Time Series: Algorithms and Applications
Sara McAllister	Nathan Beckmann, Gregory R. Ganger	Toward Sustainable Datacenters through Efficient Data Retrieval
Hojin Park	George Amvrosiadis, Gregory R. Ganger	Cost-Efficient Storage and Caching in Public Clouds
Long Pham	Jan Hoffmann	Hybrid Resource-Bound Analyses of Programs
Madhusudhan Reddy Pittu	David Woodruff, Anupam Gupta	Fairness, Diversity, Explainability, and Robustness for Algorithmic Decision-Making
Siddharth Prasad	Maria-Florina Balcan, Tuomas Sandholm	Mechanism Design and Integer Programming in the Data Age
Jeff (Sichao) Xu	Pravesh K. Koathari	Spectral Techniques for Average-Case Complexity
Brian Hu Zhang	Tuomas Sandholm	New Solution Concepts and Algorithms for Equilibrium Computation and Learning in Extensive-Form Games and Beyond

Academic Year: 2024-2025

Name	Thesis Advisor(s)	Thesis Title
Jatin Arora	Umut A. Acar	Provably Efficient Coscheduling of Computation and Memory through Disentanglement
Mihir Bala	Mahadev Satyanarayanan	Towards Fully-Autonomous Ultralight Drones
Lucio Mwinmaarong Dery	Graham Neubig, Ameet Talwalkar	On Resource Efficient Transfer Learning via End Task Aware Training
Magdalen Dobson Manohar	Guy E. Blelloch	New Techniques for Parallelism and Concurrency in Nearest Neighbor Search
Travis Hance	Bryan Parno	Verifying Concurrent Systems Code
Ananya Joshi	Roni Rosenfeld, Bryan Wilder	Event Monitoring in Modern Public Health Data Streams
Praneeth Kacham	David P. Woodruff	On Efficient Sketching Algorithms
David M. Kahn	Jan Hoffmann	Liveraging Linearity to Improve Automatic Amortized Resource Analysis
Shiva Kaul	Geoffrey Gordon	Classical Improvements to Modern Machine Learning
Mikhail Khodak	Maria-Florina Balcan, Ameet Talwalkar	The Learning of Algorithms and Architectures
Jenny Lin	James McCann	Formalizing Object Equivalence in Machine Knitting
Peter Manohar	Venkatesan Guruswami, Pravesh K. Kothari	New Spectral Techniques in Algorithms, Combinatorics, and Coding Theory: The Kikuchi Matrix Method
Elisaweta Masserova	Bryan Parno, Vipul Goyal	Distributed Cryptography as a Service
Yue Niu	Robert Harper	Cost-sensitive Programming, Verification, and Semantics
Justin Raizes	Vipual Goyal	Quantum Approaches to Verifiable Deletion
Dravyansh Sharma	Maria-Florina Balcan	Data-Driven Algorithm Design and Principled Hyperparameter Tuning in Machine Learning
Eric Mark Sturzinger	Mahadev Satyanarayanan	Survival-Critical Machine Learning
Mingjie Sun	Elaine Shi, Guilia Fanti	Hidden Properties of Large Language Models
Asher James Trockman	J. Zico Kolter	Mimetic Initialization for Deep Neural Networks
Haithem Turki	Deva Ramanan	Towards City-Scale Neural Rendering
Ranysha Ware	Justine Sherry, Srinivasan Seshan	Battle for Bandwidth: On the Deployability of New Congestion Control Algorithms
Justin Alexander Whitehouse	Zhiwei Steven Wu, Aaditya Ramdas	Modern Martingale Methods: Theory and Applications
Daniel Lin-Kit Wong	Gregory R. Ganger	Machine Learning for Flash Caching in Bulk Storage Systems
Juncheng Yang	Rashmi Vinayak	Designing Efficient and Scalable Key-value Cache Management Systems
Minji Yoon	Christos Faloutsos, Ruslan Salakhutdinov	Deep Learning on Graphs: Tackling Scalability, Privacy, and Multimodality
Runtian Zhai	Pradeep Ravikumar, Zico Kolter	Contextures: The Mechanism of Representation Learning
Mingxun Zhou	Elaine Shi, Guilia Fanti	Private Information Retrieval and Searching with Sublinear Costs
Yi Zhou	Bryan Parno	Towards Scalable Automated Program Verification for System Software
Anders Øland	Roger Dannenberg, Bhiksha Raj	Efficient Deep Learning

Academic Year: 2023-2024

Name	Thesis Advisor(s)	Thesis Title
Daniel Anderson	Guy E. Blelloch	Parallel Batch-Dynamic Algorithms Dynamic Trees, Graphs, and Self-Adjusting Computation
Jay Bosamiya	Bryan Parno	A Principled Approach towards Unapologetic Security
Matthew Butrovich	Andrew Pavlo	On Embedding Database Management System Logic in Operating Systems via Restricted Programming Environments
Bailey Flanigan	Ariel Procaccia	Expanding our Participatory Democracy Toolkit using Algorithms, Social Choice, and Social Science
Mark Gillespie	Keenan Crane	Evolving Intrinsic Triangulations
Isaac Grosof	Mor Harchol-Balter	Optimal Scheduling in Multiserver Queues
Yue (Sophie) Guo	Katia Sycara	Enhancing Policy Transfer in Action Advising for Reinforcement Learning
Quang Minh Hoang	Carl Kingsford	Practical Methods for Automated Algorithm Design in Machine Learning and Computational Biology
Steven Jecmen	Nihar B. Shah, Fei Fang	Making Peer Review Robust to Undesirable Behavior
Byungsoo Jeon	Tianqi Chen, Zhihao Jia	Automated and Portable Machine Learning Systems
Pallavi Koppol	Reid Simmons, Henny Admoni	Interactive Machine Learning from Humans: Knowledge Sharing via Mutual Feedback
Katherine Kosaian	André Platzer	Formally Verifying Algorithms for Real Quantifier Elimination
Abhiram Kothapalli	Bryan Parno	A Theory of Composition for Proofs of Knowledge
Tian Li	Virginia Smith	Scalable and Trustworthy Learning in Heterogeneous Networks
Chun Kai Ling	J. Zico Kolter	Scalable Learning and Solving of Extensive-Form Games
Francisco Maturana	Rashmi Vinayak	Designing storage codes for heterogeneity: theory and practice
Kevin Pratt	Ryan O'Donnell	Hypergraph Rank and Expansion
Klaas Pruiksma	Frank Pfenning	Adjoint Logic with Applications
Jielin Qiu	Christos Faloutsos, Lei Li	On the Alignment, Robustness, and Generalizability of Multimodal Learning
Rohan Sawhney	Keenan Crane	Monte Carlo Geometry Processing: A Grid-Free Approach to Solving Partial Differential Equations on Volumetric Domains
Siva Kamesh Somayyajula	Frank Pfenning	Total Correctness Type Refinements for Communicating Processes
Yuanhao Wei	Guy E. Blelloch	General Techniques for Efficient Concurrent Data Structures
Jalani K. Williams	Weina Wang	Setup Times in Multiserver Systems
Ke Wu	Elaine Shi	What Can Cryptography Do For Transaction Fee Mechanism Design
Taisuke Yasuda	David P. Woodruff	Algorithms for Matrix Approximation: Sketching, Sampling, and Sparse Optimization
Han Zhang	Yuvraj Agarwal, Matt Fredrikson	Secure and Practical Splitting of IoT Device Functionalities
Hanrui Zhang	Vincent Conitzer	Designing and Analyzing Machine Learning Algorithms in the Presence of Strategic Behavior
Giulio Zhou	David G. Andersen	Building reliable and transparent machine learning systems using structured intermediate representations

Academic Year: 2022-2023

Name	Thesis Advisor(s)	Thesis Title
Ainesh Bakshi	Pravesh K. Kothari, David P. Woodruff	Algorithms for Learning Latent Models: Establishing Tractability to Approaching Optimality
Benjamin Berg	Mor Harchol-Balter	A Principled Approach to Parallel Job Scheduling
Emily Black	Matt Fredrikson	(Un)Fairness Along the AI Pipeline: Problems and Solutions
Andrew Chung	Gregory R. Ganger	Realizing value in shared compute infrastructures
Chen Dan	Pradeep Ravikumar	Statistical Learning Under Adversarial Distribution Shift
Priya L. Donti	J. Zico Kolter, Inês Azevedo	Bridging Deep Learning and Electric Power Systems