I am an applied scientist working at the interesection of operations research and artificial intelligence. I have experience building end-to-end optimization solutions at variety of scales and maturity, between my time at Amazon, Auger, and now DEFCON AI. These solutions have ranged in application including multi-objective container loading, global maritime path planning, pick path optimization, supply chain optimization, and network design. Recently, many of these solutions have included integration between an optimization model and an LLM for improved explainability and guided strategic decision-making.

In my academic life, I was an Assistant Professor (tenure-track) of Operations Research at the University of Illinois at Urbana-Champaign. My training includes a postdoctoral fellowship at Carnegie Mellon University, under the supervision of Dr. Gérard Cornuéjols, and a Ph.D. from the Georgia Institute of Technology, working with Dr. Santanu Dey and Dr. Marco Molinaro, in 2022. 

You can reach me at ydubey0711 [at] gmail [dot] com.

Research interests:

• data-driven algorithm design (e.g. learning-to-optimize, discrete optimization with predictions)

• design and analysis of optimization algorithms for operations research and machine learning 

• theoretical and practical properties of algorithms for integer programming (e.g. branch-and-bound, cutting planes)