I am a research scientist and principal investigator at HRL Laboratories, Malibu, CA. My research lies in the intersection of applied mathematics, machine learning, and computer vision. I am currently the PI on DARPA Learning with Less Labels (LwLL) and the Co-PI on DARPA Lifelong Learning Machines (L2M) programs. Before joining HRL, I was a post-doctoral researcher at Carnegie Melon University. I received my Ph.D. in Biomedical Engineering from Carnegie Mellon University, where I received the Bertucci Fellowship Award for outstanding graduate students from the College of Engineering in 2014, and the Outstanding Dissertation Award from the Biomedical Engineering Department in 2015.
- Our paper `Statistical and Topological Properties of Sliced Probability Divergences' got accepted to NeurIPS2020 for a spotlight presentation - Sep 25, 2020.
- I gave an ECE Seminar talk on `Sliced Probability Metrics for Next Generation Machine Learning' at University of Virginia - Sep 11, 2020.
- I became a senior member of IEEE - Aug 17, 2020.
- Our paper `Universal Litmus Patterns: Revealing Backdoor Attacks in CNNs' got accepted to CVPR2020 for an oral presentation - March 03, 2020.
- Our papers `Sliced Cramer Synaptic Consolidation for Preserving Deeply Learned Representations' (Spotlight) and 'GAT: Generative Adversarial Training for Adversarial Example Detection and Classification' (Poster) got accepted to ICLR 2020 - Dec 20, 2019.
- Our paper `Generalized Sliced Wasserstein Distances' got accepted to NeurIPS'19, Vancouver, Canada - September 4, 2019.
- We presented our paper `Explainability Methods for Graph Convolutional Neural Networks' in CVPR'19 (Oral presentation), Long Beach, CA, USA - June 20, 2019.
show more- We presented our paper `[SAR Image Classification Using Few-Shot Cross-Domain Transfer Learning](http://openaccess.thecvf.com/content_CVPRW_2019/papers/PBVS/Rostami_SAR_Image_Classification_Using_Few-Shot_Cross-Domain_Transfer_Learning_CVPRW_2019_paper.pdf)' in CVPRW'19 (Oral presentation), Long Beach, CA, USA - June 16 2019. - Our paper on `[Deep Transfer Learning for Few-Shot SAR Image Classification](https://www.preprints.org/manuscript/201905.0030/v1)' got accepted to the IEEE Journal of Remote Sensing.
We presented our `Sliced-Wasserstein Auto-Encoder' paper in ICLR'19, New Orleans, LA, USA - May 9, 2019.
I gave a talk on `Optimal Transport in Biomedical Imaging' in the British Applied Mathematics Colloquium 2019 (BAMC'19), at Unviersity of Bath, UK - April 25, 2019. (slides)
I gave a talk on `Generalized Sliced-Wasserstein Distances' in the Department of Applied Mathematics at University of Cambridge, UK - April 23, 2019.
I gave an ECE Graduate Seminar talk at Carnegie Mellon University on Feb 14, 2019, on the topic of "Generalized Sliced-Wasserstein Distances and Their Applications in Generative Modeling and Transfer Learning".
Our paper "Sliced Wasserstein Auto-Encoders" got accepted to ICLR'19 - Dec 21, 2018
Our paper "Discovering Molecular Functional Groups Using Graph Convolutional Neural Networks" is now available on arXiv - Dec 6, 2018
Our proposal titled, 'Super-Turing Evolving Lifelong Learning ARchitecture (STELLAR)', was funded by DARPA. Dr. Hava Siegelmann is the program manager leading the Lifelong Learning Machines (L2M) program at DARPA. The HRL team is led by Dr. Praveen Pilly and I and consists of academic members from six world-renowned universities - July 2018
We are presenting our paper "Multi-Agent Distributed Lifelong Learning for Collective Knowledge Acquisition" at AAMAS2018 - July 2018
I received my second IR&D Research Award at HRL Laboratories for our Deep Sense Learning (DSL) project - June 2018
Our tutorial on "Optimal Transport in Biomedical Imaging" at the IEEE International Symposium on Biomedical Imaging (ISBI) was an absolute success.
We are presenting our paper "Joint Dictionaries for Zero-Shot Learning" at AAAI'18 - February 2018