Celebrating recent doctoral and master's graduates

Well-wishers surround newly minted Ph.D. graduate in computer science Claudia Veronica Roberts (center, in regalia) and her sister, Laura Roberts (center-right, in black and white), who completed her own Ph.D. in computer science from Princeton in 2020. Photo by Nicole Guglielmo

The Department of Computer Science celebrates the important contributions of the 29 doctoral students and 25 master’s students who earned graduate degrees in computer science over the past academic year. 

Princeton's Graduate Hooding and Recognition Ceremony took place on Monday, May 29, 2023.

The full list of doctoral and master’s degree recipients for the 2022–2023 academic year is below:

Ph.D. recipients

Zoe Clara Ashwood, Ph.D.
Thesis: Probabilistic Models for Characterizing Animal Learning and Decision-Making
Adviser: Jonathan Pillow

Rachit Dubey, Ph.D.
Thesis: The successes and failures of human drives
Adviser: Thomas Griffiths

Meryem Essaidi, Ph.D.
Thesis: User-Centered Algorithmic Mechanism Design: theoretical frameworks at different levels of central regulation
Adviser: Matthew Weinberg

Sinong Geng, Ph.D.
Thesis: Model-Regularized Machine Learning for Decision-Making
Adviser: Ronnie Sircar

Ankit Goyal, Ph.D.
Thesis: Towards Geometric Intelligence: Seeing, Grounding and Reasoning over Geometries
Adviser: Jia Deng

Christopher Charles Hodsdon, Ph.D.
Thesis: Stronger Abstractions and Performance Guarantees for Building Strongly Consistent Distributed Services
Adviser: Wyatt Lloyd

Andrew Jones, Ph.D.
Thesis: Probabilistic models for structured biomedical data
Adviser: Barbara Engelhardt

Paul McMullen Krueger, Ph.D.
Thesis: Metacognition: toward a computational framework for improving our minds
Adviser: Thomas Griffiths

Hei Law, Ph.D.
Thesis: Learning to Detect Objects by Grouping
Adviser: Jia Deng

Kevin Lee, Ph.D.
Thesis: The Research-Practice Gap in User Authentication
Adviser: Arvind Narayanan

Zhuqi Li, Ph.D.
Thesis: Cross-layer Optimization for Video Delivery on Wireless Networks
Adviser: Kyle Jamieson

Hao Liu, Ph.D.
Thesis: A Serverless Architecture for Application-Level Orchestration
Adviser: Amit Levy

Yuping Luo, Ph.D.
Thesis: Towards Efficient and Effective Deep Model-based Reinforcement Learning
Adviser: Sanjeev Arora

Aninda Manocha, Ph.D.
Thesis: Optimizing Data Supply and Memory Management for Graph Applications in Post-Moore Hardware-Software Systems
Adviser: Margaret Martonosi

Timothy Charles Murphy, Ph.D.
Thesis: Relational Verification of Distributed Systems via Weak Simulations
Adviser: Zachary Kincaid

Matthew A. Myers, Ph.D.
Thesis: Inferring Intra-tumor Heterogeneity from DNA Sequencing Data
Adviser: Benjamin Raphael

Sergiy Popovych, Ph.D.
Thesis: Self-Supervised Metric Learning for Alignment of Petascale Connectomics Datasets
Adviser: Sebastian Seung

Vikram V. Ramaswamy, Ph.D.
Thesis: Tackling bias within Computer Vision Models
Adviser: Olga Russakovsky

Claudia Veronica Roberts, Ph.D.
Thesis: Human-machine Collaboration in Real-World Machine-Learning Applications
Adviser: Arvind Narayanan

Nikunj Umesh Saunshi, Ph.D.
Thesis: Towards Understanding Self-Supervised Representation Learning
Adviser: Sanjeev Arora

Corwin William Sinnamon, Ph.D.
Thesis: Analysis of Self-Adjusting Heaps
Adviser: Robert Tarjan

Theano Stavrinos, Ph.D.
Thesis: Leopard: Unlocking Better Cache Performance at Lower Cost with Expiration Time-based Flash Caching
Adviser: Wyatt Lloyd

Zachary Rickard Teed, Ph.D.
Thesis: Optimization Inspired Neural Networks for Multiview 3D Reconstruction
Adviser: Jia Deng

Teague Joseph Tomesh, Ph.D.
Thesis: Co-designing Quantum Computer Architectures and Algorithms to Bridge the Quantum Resource Gap
Adviser: Margaret Martonosi

Yushan Su, Ph.D.
Thesis: Making Neural Network Models More Efficient
Adviser: Kai Li

Xingyuan Sun, Ph.D.
Thesis: Gradient-Based Shape Optimization for Engineering Using Machine Learning
Adviser: Szymon Rusinkiewicz and Ryan P. Adams

Daniel Can Suo, Ph.D.
Thesis: Scaling Machine Learning in Practice
Adviser: Kai Li

Kaiyu Yang, Ph.D.
Thesis: Neurosymbolic Machine Learning for Reasoning
Adviser: Jia Deng

Yuting Yang, Ph.D.
Thesis: Exploiting Program Representation with Shader Applications
Adviser: Adam Finkelstein

Master of Science in Engineering recipients

Gianluca Michele Bencomo, M.S.E.
Promise Osaine Ekpo, M.S.E.
Watson Jia, M.S.E.
Jane Pan, M.S.E.
Maxine Alexandra Perroni-Scharf, M.S.E.
Nikhil Pimpalkhare, M.S.E.
Sacheth Sathyanarayanan, M.S.E.
Ryan Daniel Torok, M.S.E.
Alfredo Velasco II, M.S.E.
Kathryn Lee Wantlin, M.S.E.
John Boda Yang, M.S.E.
Yuxuan Zhang, M.S.E.

Master of Engineering recipients

Brianna Butler, M.Eng.
Gabriel Andrew Contreras, M.Eng.
Qingchen Dang, M.Eng.
Nathan Joshua Finkle, M.Eng.
Mikako Rose Inaba, M.Eng.
Yingxi Lin, M.Eng.
Xinran Liu, M.Eng.
Daniel Birku Melesse, M.Eng.
Morgan Herminia Nanez, M.Eng.
Shiyun Qiu, M.Eng.
Charles Michael Smith, M.Eng.
Brian Max Nyuyki Tchouambe, M.Eng.
Beiqi Zou, M.Eng.