SCS Ph.D. Graduation 2019

Doctoral Degrees Conferred

Academic Year: 2021-2022
Name Thesis Advisor(s) Thesis Title
Di Wang Jan Hoffmann Static Analysis of Probabilistic Programs: An Algebraic Approach
Ruosong Wang Ruslan Salakhutdinov Tackling Challenges in Modern Reinforcement Learning: Long Planning Horizon and Large State Space
Samuel Yeom Matt Fredrikson Black-Box Approaches to Fair Machine Learning
Christopher Yu Keenan Crane Repulsive Energies and their Applications
Yu Zhao Ryan O'Donnell Generalizations and Applications of Hypercontractivity and Small-Set Expansion
Tiancheng Zhi Srinivasa G. Narasimhan, Martial Hebert Training Deep Networks with Material-Aware Supervision
Academic Year: 2020-2021
Name Thesis Advisor(s) Thesis Title
Abutalib Aghayev Georget Amvrosiadis Adopting Zoned Storage in Distributed Storage Systems
Naama Ben David Guy Blelloch Theoretical Foundations for Practical Concurrent and Distributed Computation
Rose Bohrer Andre Platzer Practical End-to-End Verification of Cyber-Physical Systems
Noam Brown Tuomas Sandholm Equilibrium Finding for Large Adversarial Imperfect-Information Games
Evan Cavallo Robert Harper Higher Inductive Types and Internal Parametricity for Cubical Type Theory
Michael J. Coblenz Jonathan Aldrich, Brad Myers User-Centered Design of Principled Programming Languages
Ankush Das Jan Hoffmann Resource-Aware Session Types for Digital Contracts
Henry DeYoung Frank Pfenning Session-Typed Ordered Logical Specifications
Laxman Dhulipala Guy Blelloch Provably Efficient and Scalable Shared- Memory Graph Algorithms
Saurabh Kadekodi Greg Ganger, Rashmi Vinayak DISK-ADAPTIVE REDUNDANCY: tailoring data redundancy to disk-reliability-heterogeneity in cluster storage systems
Deborah Stephanie Surden Katz Claire LeGoues Identification of Software Failures in Complex Systems Using Low-Level Execution Data
Jay Yoon Lee Jaime Carbonell, William Cohen Injecting output constraints into neural NLP models
Benjamin Lengerich Eric Xing Sample-Specific Models for Precision Medicine
Charles John McGuffey Phil Gibbons Modernizing Models and Management of the Memory Hierarchy for Non-Volatile Memory
Prashanth Menon Todd Mowry, Andy Pavlo On Building Robustness into Compilation-Based Main-Memory Database Query Engines
Georg P. Schoenherr Jaime Carbonell, Bhiksha Raj The Nonlinearity Coefficient - A Practical Guide to Neural Architecture Design
Amirbehshad Shahrasbi Bernhard Haeupler Coding for Synchronization Errors
Evan Shimizu Kayvon Fatahalian, James McCann Improving Parameterized Design with Interactive User-Guided Sampling and Parameter Identification Tools
Rui Silva Manuela Veloso, Francisco Melo Counterfactual MDPs: Planning Beyond Direct Control
Dana Van Aken Andy Pavlo On Automatic Database Management System Tuning Using Machine Learning
David Wajc Bernhard Haeupler Matching Theory under Uncertainty
Tianlong Yu Srinivasan Seshan, Vyas Sekar Securing Internet-of-Things via Fine-grained Network Detection and Prevention
Yimeng Zhang Tai Sing Lee Modeling early visual cortex using neural network models with recurrent circuits
Qing Zheng George Amvrosiadis, Garth Gibson Distributed Metadata and Streaming Data Indexing as Scalable Filesystem Services
Goran Žužić Bernhard Haeupler Towards Universal Optimality in Distributed Optimization
Academic Year: 2019-2020
Name Thesis Advisor(s) Thesis Title
Carlo Angiuli Robert Harper Computational Semantics of Cartesian Cubical Type Theory
Vijay Bhattiprolu Venkatesan Guruswami On the Approximability of Injective Tensor Norm
Logan Brooks Roni Rosenfeld Pancasting: forecasting epidemics from provisional data
Zack Coker Claire LeGoues Automatic repair of framework applications
Dhivya Eswaran Christos Faloutsos Mining Anomalies Using Static and Dynamic Graphs
Hannah Gommerstadt Frank Pfenning, Limin Jia Session-Typed Concurrent Contracts
Angela Jiang Greg Ganger Improving Deep Learning Training and Inference with Dynamic Hyperparameter Optimization
Anuj Kalia David Andersen Efficient Remote Procedure Calls for Datacenters
Conglong Li David Andersen Learned Adaptive Accuracy-Cost Optimization for Machine Learning Systems
Nicolas Resch Bernard Haeupler, Venkat Guruswami List-Decodable Codes: (Randomized) Constructions and Applications
Yihan Sun Guy Blelloch Join-based Parallel Balanced Binary Trees
Junjue Wang Mahadev Satyanarayanan Scaling Wearable Cognitive Assistance
Jinliang Wei Garth Gibson, Eric Xing Scheduling for Efficient Large-Scale Machine Learning Training
Huanchen Zhang David Andersen Memory-Efficient Search Trees for Database Management Systems
Dong Zhou David G. Andersen Data Structure Engineering for High Performance Software Packet Processing
Academic Year: 2018-2019
Name Thesis Advisor(s) Thesis Title
Brandon Amos Zico Kolter Differentiable Optimization-Based Modeling for Machine Learning
Joy Arulraj Andy Pavlo The Design and Implementation of a Non-Volatile Memory Database Management System
Ben Blum Garth Gibson Practical Concurrency Testing or: How I Learned to Stop Worrying and Love the Exponential Explosion
Se-Joon Chung Nancy Pollard Hand Pose Estimation and Prediction for Virtual Reality Applications
Travis Dick Nina Balcan Machine Learning: Social Values, Data Efficiency, and Beyond Prediction
Shayan Doroudi Emma Brunskill Integrating Human and Machine Intelligence for Enhanced Curriculum Design
Nathan Fulton Andre Platzer Verifiably Safe Autonomy for Cyber-Physical Systems
Yan Gu Guy Blelloch Write-Efficient Algorithms
Zhaohan Daniel Guo Emma Brunskill Directed Exploration for Improved Sample Efficiency in Reinforcement Learning
Guru Guruganesh Anupam Gupta Topics in Approximation and Online Algorithms
Nika Haghtalab Avrim Blum, Ariel Procaccia Foundation of Machine Learning, by the People, for the People
Yong He Kayvon Fatahalian Slang -- A Shader Compilation System for Extensible, Real-Time Shading
Jin Kyu Kim Garth Gibson, Eric Xing Framework Design for Improving Computational Efficiency and Programming Productivity for Distributed Machine Learning
Christian Kroer Tuomas Sandholm Large-Scale Sequential Imperfect-Information Game Solving: Theoretical Foundations and Practical Algorithms with Guarantees
Stefan K. Muller Umut Acar Responsive Parallel Computation
Yuzuko Nakamura Nancy Pollard Understanding and applying human grasping to artificial manipulators
Jun Woo Park Greg Ganger Distribution-based cluster scheduling
Vittorio Perera Manuela Veloso Language-Based Bidirectional Human And Robot Interaction Learning For Mobile Service Robot
Kijung Shin Christos Faloutsos Mining Large Dynamic Graphs and Tensors
Sahil Singla Manuel Blum, Anupam Gupta Combinatorial Optimization Under Uncertainty: Probing and Stopping-Time Algorithms
Wennie Tabib Nathan Michael, Red Whittaker Approximate Continuous Belief Distributions for Exploration
Joseph Tassarotti Robert Harper Verifying Concurrent Randomized Algorithms
Colin White Maria Florina Balcan New Aspects of Beyond Worst-Case Analysis
Zichao Yang Taylor Berg-Kirkpatrick, Eric Xing Incorporating Structural Bias into Neural Networks for Natural Language Processing
Academic Year: 2017-2018
Name Thesis Advisor(s) Thesis Title
Zhuo Chen Mahadev Satyanarayanan An Application Platform for Wearable Cognitive Assistance
Jesse Dunietz Jaime Carbonell, Lori Levin Annotating and Automatically Tagging Constructions of Causal Language
Siddhartha Jain Ziv Bar-Joseph Inferring Temporal Signaling Pathways and Regulatory Mechanisms from High-Throughput Data
Junchen Jiang Vyas Sekar, Hui Zhang Enabling Data-Driven Optimization of Quality of Experience in Internet Applications
Ashiqur Khudabukhsh Jaime Carbonell Distributed Learning in Referral Networks