Welcome to my website. My name is Albert S. Berahas and I am an Assistant Professor in the Department of Industrial and Operations Engineering at the University of Michigan.
My research focuses on designing, developing, analyzing and implementing algorithms for solving large scale nonlinear optimization problems. Such problems are ubiquitous, and arise in a plethora of areas such as engineering design, economics, transportation, robotics, machine learning and statistics. Specifically, I am interested in and have explored several sub-fields of nonlinear optimization such as: (i) general nonlinear optimization algorithms, (ii) optimization algorithms for machine learning, (iii) constrained optimization, (iv) stochastic optimization, (v) derivative-free optimization, and (vi) distributed optimization. I am affiliated with the Michigan Institute for Data Science (MIDAS), the Michigan Institute of Computational Discovery and Engineering (MICDE), and the Michigan Center for Applied and Interdisciplinary Mathematics (MCAIM).
Email: [email protected], [email protected]
Office: 2783 IOE Building, 1205 Beal Avenue Ann Arbor, MI 48109 (map)
Quick Links: Full CV, Bio, Google Scholar, arxiv, LinkedIn
Announcements
I am always looking for outstanding and highly motivated PhD students and Postdoctoral Research Fellows to join my team. If you are interested, please send me an email with your CV, and apply to our PhD program.
News
- September 2024: Hosted Francisco Jara Moroni (Universidad Diego Portales, Santiago, Chile) as a research visitor in the IOE department
- September 2024: Presented in the ORIE Seminar Series at the University of Texas in Austin
- August 2024: Received a grant titled “Advanced Algorithms for Nonlinear Constrained Stochastic Optimization” from the Office of Naval Research (in collaboration with Michael J. O’Neill)
- August 2024: Presented at the Modeling and Optimization: Theory and Applications (MOPTA) conference in Bethlehem, PA; also served on the organizing committee
- July 2024: Hosted Clément Royer (Université Paris Dauphine-PSL) as a research visitor in the IOE department
- July 2024: Presented at the International Symposium on Mathematical Programming in Montreal, Canada and organized 4 sessions
- July 2024: Our paper “Gradient Descent in the Absence of Global Lipschitz Continuity of the Gradients” (joint work with Vivak Patel) has been accepted for publication in the SIAM Journal on Mathematics of Data Science
- June 2024: Presented at the 2nd Derivative-Free Optimization Symposium in Padova, Italy
- June 2024: Received a 2024 Propelling Original Data Science (PODS) award in collaboration with Professor Raed Al Kontar from the Michigan Institute for Data and AI in Society (MIDAS) (WinAI: Propelling UM Soccer with Data-Driven AI)
- June 2024: New Paper “Modified Line Search Sequential Quadratic Methods for Equality-Constrained Optimization with Unified Global and Local Convergence Guarantees” (joint work with Raghu Bollapragada and Jiahao Shi)
- May 2024: Honored to be awarded the IISE Operations Research Division Teaching Award (link)
- May 2024: Thrilled to receive an Engaged Detroit Workshop Grant for our project Engineering Detroit’s Future: Empowering Detroit’s Next Generation through Engineering Exploration in collaboration with Leia Stirling and Patrícia Alves-Oliveira and the Detroit Educational Takeover and NSBE Detroit Professionals (link)
- April 2024: Hosted OPTIMAIZE DAY 2024 in collaboration with the Detroit Educational Takeover, a workshop for highschool students from Detroit
- April 2024: New Paper “Second-order Information Promotes Mini-Batch Robustness in Variance-Reduced Gradients” (joint work with Sachin Garg and Michał Dereziński)
- March 2024: Presented at the Control Seminar at the University of Michigan
- March 2024: Honored to be awarded the IOE Department Award
- February 2024: Our paper “Non-Uniform Smoothness for Gradient Descent” (joint work with Lindon Roberts and Fred Roosta) has been accepted for publication in Transactions on Machine Learning Research
- February 2024: Jiahao Shi will intern at Amazon this summer. Congratulations, Jiahao!
- January 2024: Honored to be awarded the 2024 North Campus Dean’s MLK Spirit Award for Community Building & Impact
- December 2023: Presented at CSE DSI Machine Learning Seminar Series at the University of Minnesota
- December 2023: New Paper “A Flexible Gradient Tracking Algorithmic Framework for Decentralized Optimization” (joint work with Raghu Bollapragada and Shagun Gupta)
- November 2023: Presented at Department of Mathematics and Statistic Seminar at Loyola University
- November 2023: New Paper “Non-Uniform Smoothness for Gradient Descent” (joint work with Lindon Roberts and Fred Roosta)
- November 2023: Co-organized the inaugural IOE Undergraduate Research Symposium
- October 2023: Hosted OPTIMAIZE DAY, a one-day workshop for high-school students from Detroit
- October 2023: Honored to serve on the INFORMS DEIC
- October 2023: Presented at the INFORMS Annual Meeting in Phoenix, AZ; also chaired 4 sessions and co-organized the INFORMS JFIG Luncheon
- September 2023: Our paper “A Stochastic Sequential Quadratic Optimization Algorithm for Nonlinear Equality Constrained Optimization with Rank-Deficient Jacobians” (joint work with Frank E. Curtis, Michael J. O’Neill and Daniel P. Robinson) has been accepted for publication in Mathematics of Operations Research
- September 2023: New Paper “Adaptive Consensus: A network pruning approach for decentralized optimization” (joint work with Suhail M. Shah and Raghu Bollapragada)
- August 2023: Presented at the Modeling and Optimization: Theory and Applications (MOPTA) conference in Bethlehem, PA; also served on the organizing committee and chaired the poster competition
- August 2023: Baoyu Zhou joins the research team as a postdoctoral research fellow-Welcome, Baoyu!
- July 2023: Our paper “First- and Second-Order High Probability Complexity Bounds for Trust-Region Methods with Noisy Oracles” (joint work with Liyuan Cao and Katya Scheinberg) has been accepted for publication in Mathematical Programming
- June 2023: Visited Clément Royer at Université Paris Dauphine-PSL for 2 weeks
- June 2023: New Paper “Collaborative and Distributed Bayesian Optimization via Consensus: Showcasing the Power of Collaboration for Optimal Design” (joint work with Xubo Yue, Raed Al Kontar, Yang Liu, Zhenghao Zai, Kevin Edgar and Blake N. Johnson)
- May 2023: Presented at the SIAM Optimization conference in Seattle, WA and organized 4 sessions
- May 2023: Our paper “Multiblock Parameter Calibration in Computer Models” (joint work with Cheoljoon Jeong, Ziang Xu, Eunshin Byon and Kristen Cetin) has been accepted for publication in the INFORMS Journal on Data Science
- May 2023: Jiahao Shi will intern at Argonne National Lab this summer. Congratulations, Jiahao!
- April 2023: Our paper “Accelerating stochastic sequential quadratic programming for equality constrained optimization using predictive variance reduction” (joint work with Jiahao Shi, Zihong Yi and Baoyu Zhou) has been accepted for publication in Computational Optimization and Applications
- March 2023: New Paper “Balancing Communication and Computation in Distributed Optimization” (joint work with Raghu Bollapragada and Shagun Gupta)
- February 2023: Honored to be awarded the Mathematical Programming 2022 Meritorious Service Award
- January 2023: Presented at the Michigan Institute Computational Discovery and Engineering (MICDE) Seminar Series Winter 2023
- January 2023: Presented at the 12th US-Mexico Workshop on Optimization and Its Applications, Huatulco, Mexico
- January 2023: New Paper “A Sequential Quadratic Programming Method with High Probability Complexity Bounds for Nonlinear Equality Constrained Stochastic Optimization” (joint work with Miaolan Xie and Baoyu Zhou)
(For the full list of news please check the News tab.)