I am recruiting graduate RAs and postdocs for 2021. If you are passionate about Machine Learning and have strong analytical skills, please contact me. Students with degrees from other disciplines such as Math, Physics and Stats are also encouraged.
- I gave a talk on "Data poisoning attack on certifiably robust classifiers" at the LATech's ECE seminar (May 2021).
- The prospect of AI's impact from our faculty's point of view was recently featured in Tulanian.
- Welcome Kiran Shrestha to the Machine Learning Group !!!
- Riley Juenemann (co-advised by Scott McKinley who is the primary) will be pursuing her PhD at Stanford University with the prestigious NSF Graduate Research Fellowship. She also received the William Wallace Peery Medal for Academic Excellence. Congratulations!!!
- I gave a short presentation on "ML predictions of mixing enthalpy of complex alloys " at 2021 LAMDA Technical Conference (Apr 2021).
- Caroline Mayberry and Samantha Rothman will be presenting our work on "A Machine Learning Exploration of Early Handwriting Development" at the Association for Psychological Science (APS) 2021 Virtual Convention. The poster and the paper will be released soon.
- Akshay Mehra will be presenting our paper titled "How Robust are Randomized Smoothing based Defenses to Data Poisoning?" at the Computer Vision and Pattern Recognition (CVPR) 2021. We will release the camera-ready version soon.
- Chanho Lim will be presenting our current work on "Machine Learning Approaches in Digital Health" at the 14th Annual Western Afib Symposium.
- I gave a tutorial talk on Adversarial Machine Learning (slides are here) at the Pattern Recognition and Machine Learning Winter School 2021. (Feb 2021)
- Byunggill Joe will be presenting "Machine Learning with Electronic Health Records is vulnerable to Backdoor Trigger Attacks" at the AAAI 2021 Workshop on Trustworthy AI for Healthcare.
- Akshay Mehra will be presenting "Stealthy Poisoning Attack on Certified Robustness" at the NeurIPS'20 Workshop on Dataset Curation and Security. There is also the poster and the full arXiv version.
- I'm the Tulane lead of the Louisiana Material Design Alliance (LAMDA). We have recently been awared $20 milion NSF RII grant.
All aspects of Machine Learning. Specific topics include the following:
- Foundations of Deep Learning
- Adversarial Learning and Optimization
- Private and Secure Machine Learning
- Medical Image Analysis and Computational Anatomy
- Nonlinear Dimensionality Reduction and Manifold Learning
You can find the list of publications from Google scholar.