I have two primary research areas. The first is focused on scientific machine learning and numerical PDEs and, which encompasses topics operator learning and physics informed neural networks. The second area involves the development of mathematical models for cancer immunology, with a specific emphasis on CART cell therapy. You can access most of my latest works in my Github.
I am the Spelman PI for two collaborative grants, MOLUcQ (Uncertainty Quantification for Multifidelity Operator Learning) and SEA-CROGS, both funded by the Department of Energy and focused on scientific machine learning. I also recently received an individual grant from the Simons Foundation to develop an operator learning framework for optimizing targeted drug delivery strategies for brain tumor treatments.
Mathematical modeling insights into improving CAR T cell therapy for solid tumors with bystander effects, 2024, Erdi Kara, Trachette L Jackson,, Chartese Jones, Reginald McGee, Rockford Sison, 2024, Nature Systems Biology and Applications.
Deep Learning Based Object Tracking in Walking Droplets and Granular Flow Experiments, Erdi Kara, George Zhang, Joseph J. Williams, Gonzalo Ferrandez-Quinto, Leviticus J. Rhoden, Maximilian Kim, J. Nathan Kutz, Aminur Rahman, 2023, Journal of Real-Time Image Processing
Tumor ablation due to inhomogeneous – anisotropic diffusion in generic 3-dimensional topologies, Erdi Kara, Aminur Rahman, Eugenio Aulisa, Souparno Ghosh,2021, Physical Review E.
Computational Math Seminar, Hamburg University of Technology , Online, October 16, 2024
U.S. National Congress on Computational Mechanics (USNCCM17) , Albuquerque, NM, July 26, 2023
The Sandia Machine Learning and Deep Learning Workshop, Albuquerque, NM, July 20, 2023
AI Institute of Dynamical Systems , University of Washington, Seattle, WA, February 14, 2023
Analysis and Applied Math Seminar , Kennesaw State University, Kennesaw, GA March 22, 2023.
Mathematical Aspects of Data Sciences , jointly organized by Spelman College and Georgia Institute of Technology, Spelman College, Atlanta, GA February 23, 2023.
Atlanta Undergraduate Research Seminar : The Rise of Transfer Learning; YOLO, GPT3 and Stable Diffusion, Emory University, Oct. 2022
Mathematical Science Research Institute(MSRI) , Berkeley, CA, July 2022
The Center for Computational Oncology Seminar, ODEN Institute for Computational Engineering and Sciences, Oct. 2021
* please check my resume for the full list and topics
Visiting Researcher, Sandia National Laboratories, Summer 2023
Worked on structure preserving graph neural networks for chaotic dynamical systems.
Sloan-NSF Program Deep Learning Mentorship, Summer 2023
Collaborative program between Michigan State University(MSU) and Spelman College, supported by the Sloan Foundation and NSF.
Trained five master’s students from MSU in the mathematical foundations of deep learning with applications in PyTorch
National Science Foundation, Computational and Data-Enabled Science and Engineering in Mathematical and Statistical Sciences (CDS&E-MSS) Review Panel, December 2022
Reviewed NSF proposals on scientific machine learning topics, including nonlinear PDEs, geometric data analysis, multifidelity modeling, and computational methods for multi-physics problems, evaluating project feasibility, impact, and alignment with NSF criteria.
Beginner Python Academy Funded by AUC Data Science Initiative, May 2022, Atlanta, GA
Ran 4-day Python workshop for data science for AUC faculty members. Check our repo.