In her remarks to the graduates, Jamieson urged the cohort to be flexible and resilient in the face of the unexpected. She used the current pace of artificial intelligence as an example, saying the graduates would need to adapt and find new ways to collaborate to excel in their fields. "Embrace the change," she said. Jamieson is the Ransburg Distinguished Professor of Electrical and Computer Engineering at Purdue University and formerly served as dean of Purdue's College of Engineering. She is a past president of the IEEE and the IEEE Signal Processing Society.

Zheng Liu won the Bede Liu Best Dissertation Award in Electrical and Computer Engineering. Liu’s work in wireless communications devices has led to flexible, programmable architectures that increase the energy efficiency of high-speed circuits and improve the bandwidth of millimeter-wave systems. "His thesis is a tour de force that has broken several frontiers in the field of wireless architectures and, in my opinion, will have a long-lasting impact in the field of integrated wireless systems for sensing and communication," said his adviser, Kaushik Sengupta, associate professor of electrical and computer engineering.

Atsutse Kludze and Tianhao Wang each won Pramod Subramanyan *17 Early Career Graduate Awards, recognizing their outstanding academic and research performance during the first two years of the graduate program.

Kludze's work on wireless technologies spans from the physics of high-speed devices to novel sensing and low-power communication. "He is a rising star in the field, and I am confident he will have a very successful career," said his adviser Yasaman Ghasempour, assistant professor of electrical and computer engineering.

Wang's work on machine learning includes pioneering research into the theoretical foundations of some of the field's most daunting open problems. He "has hit the ground running at Princeton, with a pace of innovations in privacy-preserving machine learning that is truly stunning," said his adviser Prateek Mittal, professor of electrical and computer engineering.

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

Ph.D. recipients

Gerasimos Angelatos, Ph.D.
Adviser: Hakan Tureci
Thesis: Reservoir Computing and Quantum Systems

Kyle Castoria, Ph.D.
Adviser: Steve Lyon
Thesis: Surface-State Electrons on Thin Helium Films with Amorphous Metal Substrates

Yanxi Chen, Ph.D.
Advisers: Yuxin Chen and Vincent Poor
Thesis: Machine Learning and Optimization with Latent Variables

Ting-Han Fan, Ph.D.
Adviser: Peter Ramadge
Thesis: Principles and Applications of Discrete Deep Generative Models

Shayan Hassantabar, Ph.D.
Adviser: Niraj Jha
Thesis: Efficient Neural Network Synthesis and Its Application in Smart Healthcare

Zejiang Hou, Ph.D.
Adviser: Sun-Yuan Kung
Thesis: Model and Data Efficiency in Deep Learning

Aashu Jha, Ph.D.
Adviser: Paul Prucnal
Thesis: Nonlinear Photonic Signal Processing

Tianran Liu, Ph.D.
Adviser: Lynn Loo
Thesis: Operational stability of perovskite and organic solar cells for efficient energy conversion and see-through applications

Yuchen Liu, Ph.D.
Advisers: Sun-Yuan Kung and David Wentzlaff
Thesis: Building Efficient Deep Neural Networks

Zheng Liu, Ph.D.
Adviser: Kaushik Sengupta
Thesis: Universal Spectrally Agile and Energy Efficient Non-periodic Arrays and Transmitter Architectures at Millimeter-Wave Band

Hooman Mohajeri Moghaddam, Ph.D.
Advisers: Prateek Mittal and Nick Feamster
Thesis: Tracking and Behavioral Targeting on Connected TV Platforms

Chengzhuo Ni, Ph.D.
Adviser: Mengdi Wang
Thesis: Topics in Low-rank Markov Decision Process: Applications in Policy Gradient, Model Estimation and Markov Games

Alexander Place, Ph.D.
Adviser: Andrew Houck
Thesis: Increasing Lifetimes of Superconducting Qubits

Hooman Saeidi, Ph.D.
Adviser: Naveen Verma
Thesis: Integrated and Programmable Chip-Scale millimeter-wave and Terahertz systems for Communication, Sensing, and Imaging

Tanujay Saha, Ph.D.
Adviser: Niraj Jha
Thesis: Machine Learning-based Efficient and Generalizable Cybersecurity Frameworks

Vikash Sehwag, Ph.D.
Advisers: Prateek Mittal and Mung Chiang
Thesis: Promises and Pitfalls of Generative AI: An AI-Safety Centric Approach

Hannah Smith, Ph.D.
Adviser: Antoine Kahn
Thesis: Doping at the Limit: Improving Charge Injection in Organic Light-Emitting Diodes Using Molecular Dopants

Anirudh Sridhar, Ph.D.
Adviser: Vincent Poor
Thesis: Inference of Cascades and Correlated Networks

Di Jia Su, Ph.D.
Advisers: John Mulvey and Vincent Poor
Thesis: Topics in Machine Learning

Ping Wang, Ph.D.
Adviser: Minjie Chen
Thesis: Granular Power Conversion with Distributed Switching Cells and Magnetics Integration

Zeyu Wang, Ph.D.
Adviser: Olga Russakovsky
Thesis: Tackling Imperfections in Data for Building Real-world Computer Vision Systems

Tsung-Yen Yang, Ph.D.
Adviser: Peter Ramadge
Thesis: Safe Reinforcement Learning and Constrained Learning for Dynamical Systems

Zhuozhi Yao, Ph.D.
Advisers: Barry Rand and David Wentzlaff
Thesis: Benchmarking digital logic styles for high-performance OTFT circuits

Zihuai Zhang, Ph.D.
Adviser: Nathalie de Leon
Thesis: Engineering Quantum Defects in Diamond for Quantum Networks

Zhiwu Zheng, Ph.D.
Advisers: James Sturm and Naveen Verma
Thesis: Large-Scale Flexible Actuation and Sensing

Master of Engineering Recipients

Maryam Abdurrahman, M.E.

Musab Almajnouni, M. E.

Cosmin Andrei, M. E.

Cole Becker, M. E.

David Booth, M. E.

Miguel Caranti, M. E.

Mark Castellano, M. E.

Benjamin Herber, M. E.

Gerald Huang, M. E.

Manya Kapoor, M. E.

Mary Catherine Lorio, M. E.

William Stevens, M. E.

Elie Svoll, M. E.

Tobias Zypman, M.E.