David Hidary

Research Assistant at Columbia EE/CS

d.hidary@columbia.edu LinkedIn GitHub

Experience

Research Assistant

Columbia University Department of Computer Science

Conducting AI research with Prof. Micah Goldblum and CAIL, compute supported by Google TRC and the hillclimb residency.

Co-Founder

Autumn AI (YC W26)

Co-founded Autumn AI and was accepted into Y Combinator. Initially focused on RWD, prior auth, nursing, and voice AI evals, later moved to people intelligence. Secured large contracts with healthcare partners, trained custom models, and developed a voice AI prior auth pipeline using a HIPAA-compliant AWS stack.

AI Resident

SandboxAQ

Co-authored a paper on differentiable causal discovery accepted at NeurIPS CALM. Designed novel knowledge graph evaluation methods and trained models for automatic knowledge graphs construction from unstructured data. Worked on diffusion-based generative models for use in drug-discovery pipelines.

Student Researcher

CERN

Selected as 1 of 30 students to join CERN Openlab (CS R&D). Worked under Prof. Brian Cole (Jan-Apr) to develop predictive models for calorimeter modules at ATLAS. Worked on AtmoRep (May-Sep), a 3.5B-parameter transformer for unsupervised atmospheric representation learning in collaboration with the Jülich Supercomputing Centre.

Data Scientist

Bentex

Revamped inventory tracking, recovering over $1M in missing product. Integrated Amazon's SP API. Led the design of database architectures and connected automation scripts. Built an API around database-integrated programs and deployed on a VM. Taught a 10 part course on calculus, linear algebra, deep learning, and how to build an LLM from scratch in PyTorch.

Research Assistant

Mortimer B. Zuckerman Mind Brain Behavior Institute

Worked under Prof. Ray Lee at the Zuckerman Institute. Built experiment-stimulus patient interfaces for use in fMRI machines. Developed RCNN and LSTM models in TensorFlow to predict voxel-level fMRI activation patterns from visual stimuli. Designed CAD models in SolidWorks for 3D-printed components used in dual-head fMRI holders.

Education

Columbia University

BA, Applied Mathematics (Columbia College)

GPA: 3.9/4.0

Relevant Coursework: Deep Learning, Machine Learning, Artificial Intelligence, Theory of LLMs, Computation and the Brain, Invariance Causality and Applications, Fourier Series, Real Analysis, Complex Analysis, Abstract Algebra, ODEs, Linear Algebra, Statistics, Data Structures, Quantum Mechanics, Electricity and Magnetism, Mechanics and Relativity, Columbia Core Curriculum.

The Bronfman Fellowship

Fellow

Princeton University

Summer Student, Machine Learning