News

Feb. 2025: Paper with Harsha and Deep on Strong Partitioning and a Machine Learning Approximation for Accelerating the Global Optimization of Nonconvex QCQPs has been accepted for publication in INFORMS Journal on Computing with minor revisions!

Jan. 2025: Excited to begin working with Gavin Esperanza and Jude Sanborn, B.S. students in ISE at Virginia Tech! Welcome to the LOTUS Lab, Gavin and Jude!

Nov. 2024: Excited to begin working with Atharva Anchalwar and Padmapriya Rengasamy, M.S. students in Operations Research! Welcome to the LOTUS Lab, Atharva and Padmapriya!

Nov. 2024: Paper with Guzin and Jim on Data-Driven SAA with Covariate Information has been accepted for publication in Operations Research!

Oct. 2024: Enjoyed participating in the Alpha Pi Mu Undergraduate Research Panel at VT.

Oct. 2024: Honored to be selected for an Excellence in Teaching Spotlight by the Center for Excellence in Teaching and Learning at Virginia Tech.

Oct. 2024: Seed Funding with Luke Achenie from the Institute for Critical Technology and Applied Science (ICTAS) to use Optimization for the Design of Metal-Organic Frameworks!

Oct. 2024: Chaired a session on "Learning and Optimization Techniques for Uncertain Systems" at the 2024 INFORMS Annual Meeting.

Sept. 2024: Honored to have been elected as the Vice-Chair of Global Optimization for the INFORMS Optimization Society.

Aug. 2024: Excited to begin working with Dhruva Sundararajan and Hung Tran, Ph.D. students in Operations Research! Welcome to the LOTUS Lab, Dhruva and Hung!

July 2024: Delivered an invited talk on Learning to Accelerate the Global Optimization of QCQPs at the International Symposium on Mathematical Programming.

June 2024: Grateful to have received several Thank-a-Teacher notes from students in my "Nonlinear Programming" class!

May 2024: Excited to begin working with Hiral Makwana, an M.S. student in the ISE Department! Welcome to the LOTUS Lab, Hiral!

March 2024: Thrilled to announce that the ISE DEI Committee has been awarded a VT Presidential Principles of Community Group Award!

Oct. 2023: Paper with Avinash on Optimization under uncertainty of a hybrid waste tire and natural gas feedstock flexible polygeneration system published in Energy!

Sept. 2023: Paper with Guzin and Jim on Residuals-based DRO with covariate information published in Mathematical Programming!

Aug. 2023: Thrilled to start as an Assistant Professor in the Grado Department of Industrial and Systems Engineering at Virginia Tech! Grateful to my mentors for their guidance and support along the way.

July 2023: Delivered an invited talk on "Data-Driven Multistage Stochastic Optimization on Time Series" at the International Conference on Stochastic Programming.

June 2023: Excited to begin working with Erin George on using graph-based machine learning to accelerate the global solution of nonconvex QCQPs. Erin is a 2023 LANL Applied ML Summer Research Fellow. Welcome, Erin!

May 2023: Gave an invited talk on Learning to Accelerate the Global Optimization of QCQPs at the SIAM Conference on Optimization.

Feb. 2023: New preprint with Evren and Johannes on Optimality-Based Discretization Methods for the Global Optimization of Nonconvex Semi-Infinite Programs!

Dec. 2022: New preprint with Harsha and Deep on Learning to Accelerate the Global Optimization of Nonconvex QCQPs!

Dec. 2022: Proposal with Harsha and Deep on Using Graph Neural Networks to Accelerate Solutions to Nonconvex Optimization Problems will be funded by the 2023 LANL Applied ML Summer Research Fellowship Program.

Oct. 2022: Excited to begin working as a Co-Investigator on the LANL LDRD Exploratory Research project Learning to Accelerate Global Solutions for Non-Convex Optimization.

July 2022: Gave an invited talk on Data-Driven Multistage Stochastic Optimization on Time Series at the International Conference on Continuous Optimization.

May 2022: Excited to begin working with Mithun Goutham on using multistage stochastic programming to model the resilience of the power grid to hurricanes! Welcome, Mithun!