Audience: Alumni
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Liu, P. (CM) – Reimagining Workplace Concern Reporting: From Emotional Harm to Co-Designed Futures
Workplace concern reporting infrastructure, including human resources (HR) portals, grievance procedures, and whistleblower hotlines, is the formal channel through which employees in most organizations raise concerns about harassment, discrimination, and retaliation. Yet existing research consistently finds that these systems fail the employees they are meant to protect: reports stall, concerns get filtered, retaliation occurs, and…
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Zhou, K. (CSE) – Toward Safer Frontier AI: From Evaluation and Red-Teaming to Alignment and Oversight
This dissertation investigates how to make modern AI systems safer as they grow more capable. It addresses two central sources of risk: malicious misuse, in which adversarial users coerce models into harmful behavior, and internal misalignment, in which models themselves pursue goals that diverge from human intent through deception, sandbagging, or other covert behaviors. The…
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Baskaran, D. (CM) – More than Just Fun: Exploring Meaningful Play, Communities of Play, and Relatedness of Play
Play is often seen as a form of entertainment, leisure, or childhood development. However, it also acts as a meaningful experience that shapes how people connect with others and interact with the world around them throughout their lives. Prior work on meaningful play and communities of play has mainly focused on individual experiences and participation,…
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Yang, D. (CSE) – Inner Monologue: a Pathway to Human-Like Reasoning for Complex Tasks
A central goal on the path toward general AI is to build systems capable of deliberative reasoning before action. Such systems should inspect what they know, identify what they need, seek or construct useful information, and revise their reasoning through intermediate cognitive states. This dissertation studies this goal through the lens of Inner Monologue (IM),…
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Castro, S. (CSE) – Agentic AI for Security: Adversarial Foundations for Autonomous Cyber Operations
Autonomous Cyber Operations (ACO) agents promise effective security automation with minimal human intervention, yet their deployment raises three interconnected challenges: agents must be realistic (reproducing diverse attacker sophistication), secure (preventing autonomy from becoming an attack surface), and feasible (safely replicating human behavior at full autonomy). We argue that these three properties are requirements for ACO…
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Paul Pena, D. (CSE) – Efficient Pattern Counting in Sparse Graphs and Hypergraphs
Pattern counting is a fundamental problem in computer science with applications in many domains. For a fixed small pattern H, we are given a large graph G and we are asked to count the number of subgraphs or homomorphisms (edge-preserving maps) of H in G. For practical applications where the input graph can be very…
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Zhu, R. (ECE) – From Neuromorphic Principles to Efficient Neural Language Architectures
This dissertation investigates how neuromorphic and brain-inspired principles can guide the design of efficient neural language architectures. It addresses two central limitations of modern Transformer-based language models: memory growth with context length and high computational cost from dense matrix multiplication. Through studies of spiking neural networks, linear-recurrent language models, hybrid attention architectures, MatMul-free models, and…
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Bai, G. (BMEB) – Long-read single-molecule chromatin architecture and its role in transcriptome regulation
Sequencing technologies have revolutionized our understanding of biology, yet many existing methods require fragmentation of DNA or RNA, fundamentally limiting our ability to study these molecules in their native, intact forms. Long-read sequencing overcomes this constraint by enabling the sequencing of long, single-molecule native DNA and RNA, providing simultaneous access to both sequence and base…
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Kordonowy, S. (CS) – The Role of Circuits in Near-Term Quantum Computation
As quantum computing transitions from theory to practice, understanding which algorithms suit near-term devices becomes critical. Current quantum computers are severely constrained by limited qubit counts, short coherence times, and high error rates that quickly degrade computation into noise. This thesis addresses two interconnected questions: what non-trivial computational tasks can near-term devices execute and how…
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Lucas, J. (BMEB) – Enabling Population-Scale Analysis of Human Centromere Diversity
Centromeric DNA is critical for accurate chromosome segregation and genome stability, but due to its repetitive nature, it was only recently fully included in a human reference. Rapid evolution and sequence diversity in these regions limit the utility of one reference sequence, however. Integrating centromeric and pericentromeric satellite DNA – which together constitute over 5%…