About
The ORNL AI Seminar Series (Biweekly/Hybrid), organized by the AI Initiative, serves as a platform for researchers and engineers from diverse scientific, engineering, and national security backgrounds spanning ORNL, universities, and industry. Our main objective is to encourage collaboration with the goal of driving transformative advancements in safe, trustworthy, and energy-efficient AI research and its applications. The seminar will be held every other Thursday from 10 am to 11 am ET. The seminar will be held every other Thursday from 10–11 am ET. Please reach out to the organizers if you would like to give a talk.
Next Presentation
Data Science for Scientific Data Compression and Transportation Applications
Room: Weinberg Auditorium (4500N/I-126)
Time: 10-11 am ET, Thursday, 10/19/2023
Microsoft Teams link: TBA
Anand Rangarajan and Sanjay Ranka
University of Florida
 Anand Rangarajan Professor Computer & Information Science & Engineering University of Florida |
 Sanjay Ranka Distinguished Professor Computer & Information Science & Engineering University of Florida |
Abstract: In this we will present my recent work on developing data science solutions for large scale applications in scientific computing and transportation.
The volume of data generated by scientific applications has continued to outpace the growth of computing power and storage capacities. Unlike video and image compression, scientists require downstream quantities of interest to be conserved along with error bounds on primary data. We have developed novel constrained auto encoders based algorithmic and software pipelines that satisfy both these requirements. For data generated using Tokomak simulation codes that produce petabytes of data using thousands of GPUS, we have shown that our approach can compress the data by two orders of magnitude while requiring less than one percent of computational resources.
Mitigating traffic congestion and improving safety are the cornerstones of transportation. We have developed an ML based edge-cloud based system to analyze and fuse data streams from LIDAR, cameras and ground sensor data for quantifying and impacting pedestrian and vehicle safety. Using the data collected, we are also developing digital twins that model behavior at traffic intersections. The underlying models are useful for detecting interruptions as well as optimizing signal timing plans. We will present experimental results on data collected from real-traffic intersections in the City of Gainesville and City of Orlando.
This work is supported by DOE, NSF, and FDOT.
Bio:
Professor Sanjay Ranka
Sanjay Ranka is a Distinguished Professor in the Department of Computer Information Science and Engineering at the University of Florida. From 1999-2002, as the Chief Technology Officer at Paramark (Sunnyvale, CA), he developed a real-time optimization service called PILOT for marketing campaigns. PILOT served more than 10+ million optimized decisions a day in 2002 with a 99.99% uptime. Paramark was recognized by VentureWire/Technologic Partners as a Top 100 Internet technology company in 2001 and 2002 and was acquired in 2002. Sanjay has also held positions as a tenured faculty member at Syracuse University, academic visitor at IBM and summer researcher at Hitachi America Limited.
He has coauthored one book, four monographs, 340+ journal and refereed conference articles. His recent coauthored work has received a best student paper runner-up award at IGARSS 2015, best paper award at BICOB 2014, best student paper award at ACM-BCB 2010, best paper runner-up award at KDD-2009, a nomination for the Robbins Prize for the best paper in the Journal of Physics in Medicine and Biology in 2008, and a best paper award at ICN 2007. His work has received 15,900+ citations with an h-index of 63 (based on Google Scholar).
He is a fellow of the IEEE, AAAS and AAIA (Asia-Pacific Artificial Intelligence Association) and a past member of IFIP Committee on System Modeling and Optimization. He received the 2020 Research Impact Award from IEEE Technical Committee on Cloud Computing and the 2022 Distinguished Alumnus Award from Indian Institute of Technology, Kanpur. He is a board member of American Society on Artificial Intelligence.
Schedule
Please reach out if you are interested in presenting at a future event
| Date | Location | Name | Affilication | Talk |
|---|---|---|---|---|
| 08/03 | Emory (5200/214) | Florian Schäfer | Georgia Tech | Solvers, Models, Learners: Integrating inference and simulation |
| 08/17 | Bredesen Center (5100/140) | Samantha Cox | University of Rochester | AI’s Expanding Role: Transforming Scientific Automation with LLM-Powered Agents |
| 08/31 | Teams | Adam Gleave | FAR AI | Automated Testing for Machine Learning Systems |
| 09/14 | Teams | James Chapman | Boston University | Understanding Atomic-scale Materials Behavior Using Graph-based Machine Learning |
| 09/28 | Teams | Michael Grosskopf | LANL | Data efficient optimization with Gaussian process egression for fusion target design |
| 10/12 | Teams | Elizabeth Qian | Georgia Tech | Reduced operator inference for nonlinear PDEs |
| 10/19 | Weinberg Auditorium (4500N/I-126) | Anand Rangarajan and Sanjay Ranka | University of Florida | Data Science for Scientific Data Compression and Transportation Applications |
| 10/26 | Teams | Bradley Malin | Vanderbilt University | TBA |
Organization
For questions, please contact us.
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| Pei Zhang Computational Scientist Computational Science and Engineering Division, ORNL |
Ayana Ghosh Research Scientist Computational Science and Engineering Division, ORNL |
Prasanna Balaprakash Director of AI Programs Distinguished R&D Staff Scientist Computing and Computational Sciences Directorate, ORNL |