CV

Education

• HS Diploma, Science, Mathematics & Computer Science Magnet, Montgomery Blair High School, 2022
• B.S. in Computer Science, Stanford University, 2025 (in progress)
• M.S. in Computer Science, Stanford University, 2026 (in progress)

Work experience

• Summer 2023: Machine Leanring/Bioinformatics Co-op
  • Regeneron Pharmaceuticals
  • Devleoped a novel bioinformatics pipeline called DeepHaplosmith - An iterative variational autoencoder-based deep clustering and annealing pipeline for separating viral and somatic haplotypes
  • In process of patent and publication
  • Supervisor: Dr. Ayush Saxena
• Fall 2022 - Present: Researcher
  • Koyejo Lab (STAIR)
  • Project: A Probabilistic Geometric Framework for Mechanistic Interpretability
  • Supervisor: Ph.D. student Rylan Schaeffer, Prof. Sanmi Koyejo

  • Two ICML Workshops publications, presented at CS 231N final conference

  • Project: An Information-Theoretic Understanding of Maximum Manifold Capacity Representations (ongoing)
  • Supervisor: Ph.D. student Rylan Schaeffer, Prof. Sanmi Koyejo, Meta researchers
• Fall 2022 - Spring 2023: Researcher
  • Supervised Program in Alignment Research (SPAR)
  • Project: In-context learning for preference elicitation

  • Supervisor: Koyejo Lab Ph.D. student Zachary Robertson

  • Project: Causal Deep Neural Network Training
  • Supervisor: Wu Tsai Neurosciences Institute Ph.D. student Max Kanwall
• Fall 2020 - Spring 2022: Researcher
  • NASA Harvest
  • Project: Addressing Crop Market Uncertainty during COVID-19 through Remote Sensing and Machine Learning
  • Supervisor: Ph.D. student Rylan Schaeffer, Prof. Sanmi Koyejo
  • Published in Science of Remote Sensing, Sigma Xi conference award winner
• Summer 2021: RSI Scholar
  • Harvard Psychiatry Neuroimaging Lab
  • Project: Representation of and Deep Learning on Brain Surfaces for Rapid, Targeted Transcranial Magnetic Stimulation
  • Supervisor: Dr. Ning Lipeng
  • Presented at International Science and Engineering Fair and RSI final symposium, Regeneron Science Talent Seaerch finalist project

Skills

• AI/ML
  • Computer vision
  • Natural language processing
  • Science of deep learning
  • Foundation models
  • Reinforcement learning
  • Unsupervised learning
  • Generative models
  • Graph learning
  • Algorithmic design
  • Optimizaiton
• Applied math
  • Mathematical modeling & simulation
  • Numerical methods
  • Data science
  • Causal inference
• Mathematics
  • Analysis
  • Differential equations
  • Statistical mechanics
  • Linear algebra
  • Measure theory

Publications

Mapping the genealogy of medical device predicates in the United States

Pai, DB. “Mapping the genealogy of medical device predicates in the United States,” PLOS ONE, Oct 7, 2021. DOI:10.1371/journal.pone.0258153.

Deceptive Alignment Monitoring

Pai, DB, Carranza, A, Schaeffer, R, Koyejo, S. “Deceptive Alignment Monitoring.” Adversarial ML Frontiers, ICML Workshops, Jun 20, 2023.

FACADE: A Framework for Adversarial Circuit Anomaly Detection and Evaluation.

Pai, DB, Carranza, A, Tandon, A, Schaeffer, R, Koyejo, S. “FACADE: A Framework for Adversarial Circuit Anomaly Detection and Evaluation.” Adversarial ML Frontiers, ICML Workshops, Jun 20, 2023.