Dave Kielpinski

Pioneered machine learning strategy for proprietary futures trading and delivered a prototype machine learning model for asset pricing.

Led technical work on inaugural customer engagement for a major quantum computing platform, saving up to 50% of AWS infrastructure costs and reducing time for quantum computer characterization by 100x.

Provided AI strategy and modeling for code vulnerability detection and productionized graph neural network code for drug discovery, significantly reducing model training time.

Led data integrity initiatives and prototyped data ingestion and ETL for machine learning models of automated DevOps, enhancing business analytics.

Optimized the primary machine learning recommendation model, reducing model training time by 50% and led research in online optimization of contextual A/B testing.

Led a complete rewrite of the company's core machine learning code in PyTorch, achieving significant speedup in 3D image recognition and reducing prediction costs.

Led a DARPA project on optical neural networks and designed Python/SQL data ingestion and modeling for silicon photonics hardware tests.

Initiated pioneering experiments in quantum information and attosecond physics, contributing to significant advancements in the field.

Developed novel cooling schemes for atoms at ultra-low temperatures, contributing to groundbreaking research in quantum physics.

Achieved world-first temperatures in quantum physics research, contributing to significant advancements in the field.

Major role in construction of first fully functional quantum computer.

Also completed requirements for Honors B.A. in Mathematics.