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Bio
Bio
I am a fourth-year PhD candidate in the Department of Industrial and Operations Engineering at the University of Michigan. My research focuses on developing scalable algorithms for solving structured mixed-integer quadratic programs arising in large-scale settings across machine learning, statistics, and operations research. By exploiting graph structure and sparsity, I design efficient algorithms for problem instances that are otherwise computationally challenging.
I am advised by Prof. Salar Fattahi.
Contact:
Contact:
aareshfb@umich.edu
Updates
Updates
March 2026: Our new paper introduces an algorithm to solve structured convex quadratic optimization with indicators, with applications in forecasting: Solving convex quadratic optimization with indicators over structured graphs. Joint work with Salar Fattahi, Andrés Gómez, and Simge Küçükyavuz.
August 2025: New paper on a scalable framework for joint inference of dynamic gene regulatory networks using a discrete ℓ₀ penalty, based on the parametric algorithm for MIQPs over trees: Efficient Inference of Dynamic Gene Regulatory Networks Using Discrete Penalty. Joint work with Visweswaran Ravikumar, Wajd Al-Holou, Salar Fattahi, and Arvind Rao.
August 2025: Honored to be selected as a 2025–2026 MICDE Fellow.
March 2025: Our paper A Parametric Approach for Solving Convex Quadratic Optimization with Indicators Over Trees, is accepted to appear in Mathematical Programming. Joint work with Salar Fattahi, Andrés Gómez, and Simge Küçükyavuz.
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