George Washington University SIAM Student Chapter Explores Data Science and Deep Learning

In April 2024, the George Washington University (GW) SIAM Student Chapter hosted its 5th Annual Conference on Applied Mathematics: Emerging Trends in Data Science and Deep Learning. During the event, which took place on GW’s main campus, speakers from both academic and industrial settings in the greater Washington, D.C., metro area presented their recent work in applied mathematics, with a particular focus on data science and deep learning.

Since its establishment in 2014, the GW SIAM Student Chapter has consistently organized talks, conferences, and social events to promote applied mathematics and computational science in and around Washington, D.C. The chapter began to host regular conferences in 2017, with subsequent events in 2018, 2019, 2023, and 2024. For the first time, the 2024 conference adopted a specific theme and opted to concentrate on data science and deep learning. We plan to maintain this approach in the future and feature a distinct research area at each forthcoming annual meeting.

The 2024 conference attracted more than 20 attendees, including professors, postdoctoral researchers, undergraduate and graduate students from local universities, and research scientists from the technology industry. This gathering—which served as a platform for distinguished scientists to present their recent findings in the realm of data science and deep learning—also allowed attendees to network, exchange research insights, discuss career developments, and establish potential collaborations.

The invited speakers included two postdoctoral researchers, four graduate students, and one industrial research scientist, all of whom came from three local universities and one technology corporation. The presenters addressed a variety of engaging topics, as follows:

• Dong An (Joint Center for Quantum Information and Computer Science at the University of Maryland, College Park): “Quantum Algorithms for Linear Differential Equations”
• Rohit Khandelwal (George Mason University): “The Obstacle Problem: Optimal Control and Elliptic Reconstruction”
• Jessica Masterson (George Mason University): “Modeling and Optimization Applied to Cryopreservation”
• Zezheng Song (University of Maryland, College Park): “A Finite Expression Method for Solving High-dimensional Committor Problems”
• Derek (Binshuai) Wang (GW): “Identifying Similar Thunderstorm Sequences for Airline Decision Support Using Optimal Transport Theory”
• Yaqi Wu (GW): “Supervised Gromov-Wasserstein Optimal Transport”
• Jingjing Xu (Amazon): “An Introduction to Advertising Technology.”

Each speaker delivered a 25-minute presentation that was followed by a brief question-and-answer period to facilitate a dialogue with audience members. “I was honored to present my recent work at this conference and learn from the presentations of other speakers,” Khandelwal said. “I am looking forward to attending the annual conference next year if possible.”

The GW SIAM Student Chapter would like to thank SIAM and the Department of Mathematics at GW for their financial support of this event. Stay tuned for the 2025 annual conference, which will explore a new theme in applied mathematics and computational science.