• December 2025

  • I am honored to deliver an invited contributed talk titled "Adaptive, Scalable, and Fast Algorithms for Large-Scale Nonlinear Optimization" in the CBMS Conference: Research at the Interface of Applied Mathematics and Machine Learning, Department of Mathematics, University of Houston.  

• October 2025

  • It was my a great opportunity to give a talk titled "Flexible, Adaptive, and Efficient Algorithms for Decentralized Optimization" in the AI Seminar Series at Oak Ridge National Laboratory  

• September 2025

  • It was my privilege to visit the Department of Computational Applied Mathematics & Operations Research  at Rice University to give a seminar titled "Adaptive, Scalable, and Fast Algorithms for Large-Scale Nonlinear Optimization"

• April 2025

  • I am honored to deliver a keynote talk titled "Adaptive, Scalable, and Fast Algorithms for Nonlinear Stochastic Optimization" at the East Coast Optimization Meeting 2025. 

  • Our Paper "A Flexible Gradient Tracking Algorithmic Framework for Decentralized Optimization" is now published in Computational Optimization and Applications. DOI: 10.1007/s10589-025-00685-w

• March 2025

  • It was my privilege to visit the Department of Industrial and Systems Engineering at Lehigh University to give a seminar titled "Flexible, Adaptive, and Efficient Algorithms for Decentralized Optimization."

  • Our paper "A stochastic gradient tracking algorithm for decentralized optimization with inexact communication" is now published in IEEE Transaction on Automatic Control. DOI: 10.1109/23M1599379 

• December 2024

  • Our work on "Central Finite-Difference Based Gradient Estimation Methods for Stochastic Optimization" was presented at Winter Simulation Conference 2024, Orlando, FL.

• November 2024

  • Our paper "Adaptive Consensus: A network pruning approach for decentralized optimization" is now published in SIAM Journal On Optimization. DOI: 10.1137/23M1599379 

  • Our paper on adaptive sampling based negative-curvature approaches for solving unconstrained stochastic optimization is now available online. https://arxiv.org/pdf/2411.10378 

  • Our paper on efficient mathematical programming approaches for optimal camera placement is now available online. https://arxiv.org/pdf/2411.17942

• October 2024

  • Our paper "Balancing Communication and Computation in Gradient Tracking Algorithms for Decentralized Optimization" is now published in Journal of Optimization Theory and Applications. DOI: 10.1007/s10957-024-02554-8 

  • I am honored to have been elected Vice Chair of Nonlinear Optimization for the INFORMS Optimization Society (2024–2026).  

  • Our research group organized multiple sessions and delivered talks at the 2024 INFORMS Annual Meeting. Congratulations to Shagun Gupta, Yash Kumar, and  Jiahao Shi on their contributions!

• September 2024

  • Our paper "A Retrospective Approximation for Smooth Stochastic Optimization" is now published in Mathematics of Operations Research. DOI: 10.1287/moor.2022.0136

  • Congratulations Marissa Llamas!!!  Won the best poster award for her poster on "Towards Adaptive Selection of Directions in Unconstrained Deterministic Derivative-Free Optimization" at the Texas Advanced Computing Center Symposium.

  • Marissa Llamas (Summer Undergraduate Research Student) presented poster at the STARS Conference in San Diego, CA.

• August 2024

  • Our paper "On the fast convergence of heavy ball momentum" is now published in IMA Journal of Numerical Analysis.  DOI: 10.1093/imanum/drad033

  • Our paper on Hessian averaging that achieves provably (deterministic) superlinear convergence without increasing Hessian sample sizes is available online. https://arxiv.org/pdf/2408.07268

  • Congratulations Cem Karamanli!!! Successfully defended his thesis on "Design and Analysis of Adaptive Methods for Nonlinear Optimization". He will be joining Amazon. 

My research is supported by an NSF grant DMS-2324643, Argonne National Laboratory (ANL) and Lawrence Livermore National Laboratory (LLNL).