Welcome to the website of the Optimization and Machine Learning (OptML) research group at Lehigh University! Please explore our page to find out more about the current and past people affiliated with our group, the research areas of our affiliated faculty members, our seminar series, and our events.
- May, 2023: OptML faculty member Luis Nunes Vicente was awarded a three-year grant from the Air Force Office of Scientific Research for a project entitled “Multi-Level Multi-Objective Stochastic Methods for Learning and Optimization.” Check out this news item for further information.
News Fall 2020 through Spring 2023
During this time period, our news was posted on Twitter. It might be found through the LehighOptML handle on that service.
News through Fall 2020
- September, 2020: OptML faculty members Daniel P. Robinson and Frank E. Curtis won the call to organize the International Conference on Continuous Optimization (ICCOPT) at Lehigh University in the summer of 2022! Check out the ICCOPT 2022 website for further information. Also follow @iccopt2022 on Twitter.
- September, 2020: OptML is proud to welcome its new postdoctoral researcher, Michael O’Neill. Mike received his Ph.D. from the University of Wisconsin-Madison under the supervision of Stephen J. Wright. He is a recipient of a prestigious NSF-funded Computing Innovation (CI) Fellowship awarded by the Computing Research Association (CRA) and the Computing Community Consortium (CCC). He is supervised by OptML faculty members Frank E. Curtis and Daniel P. Robinson.
- August, 2020: OptML postdoctoral researcher, Albert Berahas, started his new position as an assistant professor in the Department of Industrial and Operations Engineering at the University of Michigan. Congratulations, Albert!
- July 15, 2020: OptML faculty members Daniel P. Robinson and Frank E. Curtis received an award from the National Science Foundation for a project entitled “An Accelerated Decomposition Framework for Structured Sparse Optimization.”
- February 18, 2020: OptML faculty member Frank E. Curtis and collaborators Daniel Molzahn (Georgia Tech), Andreas Waechter (Northwestern), Ermin Wei (Northwestern), and Elizabeth Wong (UC San Diego) were awarded second place in the ARPA-E Grid Optimization Competition; see the announcement.
- December 13, 2019: OptML postdoc Albert Berahas and colleagues from Rice University, the University of California at Berkeley, and the University of Queensland organized a workshop on “Beyond First-Order Methods in ML” at the Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019) in Vancouver, CANADA.
- November 12, 2019: OptML faculty members Daniel P. Robinson and Frank E. Curtis were awarded the 2018 Best Paper Prize by Optimization Letters for their paper entitled “Concise Complexity Analyses for Trust Region Methods.” Check out the announcement here.
- October 20-23, 2019: OptML faculty and students attended the 2019 INFORMS Annual Meeting in Seattle, Washington.
- August 8, 2019: OptML faculty member Frank E. Curtis gave a semi-plenary lecture on “New Quasi-Newton Ideas for (Non)smooth Optimization” at the International Conference on Continuous Optimization (ICCOPT) in Berlin, Germany.
- July 1, 2019: OptML is proud to welcome its newest faculty member, Daniel P. Robinson!
- July 1, 2019: Founding OptML faculty member Katya Scheinberg has accepted a new position at Cornell University. We’re very sorry to see her go, but take solace in the fact that we know that she’ll remain a close collaborator with OptML for many years to come. Best wishes, Katya!
- January 28-30, 2019: OptML faculty and students attended the MIT Workshop on “Non-convex optimization and deep learning”.
- November 5, 2018: OptML faculty member Frank E. Curtis has been awarded the INFORMS Computing Society Prize along with James V. Burke (University of Washington), Adrian S. Lewis (Cornell University), and Michael L. Overton (New York University) for their work on gradient sampling methods for nonsmooth optimization.
- November 4-7, 2018: OptML faculty and students attended the 2018 INFORMS Annual Meeting.
- September 1, 2018: Welcome Albert Berahas, who is joining the group as a postdoctoral researcher. Albert completed his thesis on “Methods for Large Scale Nonlinear and Stochastic Optimization” at Northwestern University, where he was advised by J. Nocedal.
- August 13-17, 2018: OptML faculty helped to organize and run a three-day NSF-sponsored summer school, an NSF/DIMACS sponsored workshop on Optimization and Machine Learning, and the 2018 MOPTA Conference. All were great successes! For more information, please see here.
- July 13-15, 2018: Katya Scheinberg is co-organizing a workshop on “Modern Trends in Nonconvex Optimization for Machine Learning” at ICML 2018; see the workshop website for more information.
- January 8-12, 2018: Katya Scheinberg is chair of the organizing committee for the U.S.-Mexico Workshop on Optimization and its Applications; see the workshop website for more information.
- January 1, 2018: Welcome Courtney Paquette, who is joining the group as a postdoctoral researcher. Courtney completed her thesis on “Structure and complexity in non-convex and nonsmooth optimization” at the University of Washington, where she was advised by D. Drusvyatskiy.
- August 28, 2017: Frank E. Curtis has left for sabbatical for the 2017-2018 academic year. He will be spending most of the Fall semester at Columbia University (hosted by Donald Goldfarb) and most of the Spring semester at New York University (hosted by Michael Overton) with shorter stints at Johns Hopkins University in the Fall (hosted by Daniel P. Robinson) and Northwestern University in the Spring (hosted by Jorge Nocedal and Andreas Waechter).
- August 24, 2017: Katya Scheinberg, Frank E. Curtis, and Martin Takac have been awarded a grant from the National Science Foundation’s Division on Computing and Communication Foundations, award number CCF-1740735, to create a TRIPODS Institute for Optimization and Learning. The institute is a collaborative effort with Francesco Orabona from Stony Brook University and Han Liu from Northwestern University, and will run from January 1, 2018 until December 31, 2020. Read more about the award here.
- May 24, 2017: Congratulations to Matt Menickelly for passing his dissertation defense!
- May 24, 2017: Katya Scheinberg gave a plenary talk at the SIAM Conference on Optimization in Vancouver, Canada. The presentation slides from her talk can be found on our Talks page.
- April 18, 2017: Congratulations to Wei Guo for passing his dissertation defense!
- March 3, 2017: Members of OptML attended the 11th Annual Machine Learning Symposium at the New York Academy of Sciences (NYAS).
- September 1, 2016: Katya Scheinberg has left for sabbatical for the 2016-2017 academic year. She will be spending half of the year at Google Research in New York City and the other half at the University of Oxford in the United Kingdom. At Google, she will be working with a machine learning research team on improving optimization algorithms for deep learning tools, as well as on other large-scale learning algorithms. At Oxford, she will be joining the Mathematical Institute as a visiting faculty member and joining both Balliol and Exeter Colleges as a visiting fellow. She will also hold a part-time visiting position at the new Alan Turing Institute in London. While in the UK, she will be focusing on research on stochastic optimization methods.
- September 1, 2016: OptML Faculty members Katya Scheinberg, Frank E. Curtis, and Martin Takac have been awarded a grant from the National Science Foundation’s Division on Computing and Communication Foundations, award number CCF-1618717. Their award is entitled “AF: Small: New Classes of Optimization Methods for Nonconvex Large Scale Machine Learning Models” and will run from September 1, 2016 until August 31, 2019.
- June 24, 2016: OptML faculty members Katya Scheinberg and Frank E. Curtis, along with Jorge Nocedal (Northwestern University) and Yoshua Bengio (University of Montreal), are organizing a workshop at ICML 2016 on Optimization Methods for the Next Generation of Machine Learning; see the announcement here. More details about the workshop can be found under Events or here.
- June 19, 2016: OptML faculty member Frank E. Curtis, along with Leon Bottou (Facebook AI Research) and Jorge Nocedal (Northwestern University), is giving a tutorial at ICML 2016 on “Stochastic Gradient Methods for Large Scale Machine Learning”. The announcement can be found here and the presentation slides can be found on our Talks page.
- March 4, 2016: Members of OptML attended the 10th Annual Machine Learning Symposium at the New York Academy of Sciences (NYAS). The symposium involved a competition sponsored by American Express, the winners of which included Wei Guo (overall winner) and Chenxin Ma (honorable mention) from OptML! (The 9th Annual Symposium had a similar competition, which was won by Zheng Han, a previous OptML member!)
- March 1, 2016: Welcome to the new website of the optimization and machine learning (OptML) research group at Lehigh University!