CV

Education

University of California, Berkeley2025–present

PhD in Statistics · NSF Graduate Research Fellow

Coursework: High-Dimensional Statistics, Deep Learning and Applied Statistics, Causal Inference
Teaching: GSI, STAT 134 (Concepts of Probability)

California Institute of Technology2019–2023

BS in Applied and Computational Mathematics

SMat-Attention: Structured Long-Context Sequence Modeling Emile Anand, Abdullah Ateyeh, Archer Wang, Marin Soljačić Under review at ICLR 2027. Long Context Frontier Models Workshop, NeurIPS 2026.
Continuous Latent Contexts Enable Efficient Online Learning in Transformers Emile Anand, Abdullah Ateyeh, Xinyuan Cao, Max Dabagia Under review at ICLR 2027.

Venture Capital and Technological Innovation2021

Caltech, with Prof. Michael Ewens and BlackRock

Linked patent, venture-financing, and incorporation records into a new dataset and used time-series and logistic-regression models to characterize how VC investment follows innovation. Presented to BlackRock's quantitative research team.

Searching for High-Redshift Radio-Loud Quasars2020

Caltech SURF, with Prof. Vikram Ravi

Cross-matched Pan-STARRS and VLASS survey data to find quasar candidates, then prioritized them with a multilayer perceptron trained on four additional infrared surveys. Presented at Caltech's SURF symposium.

Quantitative Trader, The Voleon Group2023–2025

Managed portfolio risk across equities, FX, ETFs, futures, and index swaps using ML-driven signal and execution systems.
Built automated hedging via convex optimization over large covariance structures, and constrained-optimization tools for securities lending.