MCW Data Science Institute Welcomes Dr. Suhas Sreehari

The Data Science Institute (DSI) is pleased to welcome Dr. Suhas Sreehari as an assistant professor. He brings 14 years of research, academic, and industry experience in machine learning, statistical analytics, deep learning, optimization, computational imaging, anomaly detection, and predictive analytics.

Dr. Sreehari received his PhD in electrical engineering from Purdue University in 2017. He is the Founder of Pelagia Labs working on AI foundation models. Additionally, he is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE), an elected member of the IEEE Technical Committee on Computational Imaging, past President of IEEE East Tennessee, and is the recipient of the 2020 SIAM Imaging Sciences Best Paper Prize and the 2018 IEEE Signal Processing Society Young Author Best Paper Award.

From 2019 through 2021, Dr. Sreehari was the Assistant Vice President of Quantitative Analytics at Wells Fargo, San Francisco, where he developed AI/ML/statistical anomaly detection models for tracking financial crime/fraud, designed explainable ML techniques and surrogate models for neural networks, created KPIs and sensitivity analysis tests to monitor model performance, automated ML pipeline to build internal platform, and taught a graduate-level course on optimization, estimation theory, and ML.

Most recently, Dr. Sreehari was an Assistant Professor of Electrical Engineering and Computer Science at The University of Tennessee in Knoxville, TN with a joint faculty appointment with Oak Ridge National Laboratory in Oak Ridge, TN. At the Oak Ridge National Laboratory, Dr. Sreehari designed robust latent space representations in autoencoders for biological data (such as protein structures), served as the lead investigator on federated learning for medical image super-resolution and machine learning modeling specialist for US Veterans Affairs-funded research on environmental determinants of health, created privacy-preserving face ID algorithms using generative neural networks, and developed AI/ML solutions for anomaly detection in healthcare.

Dr. Sreehari will contribute to the missions of MCW and DSI by applying his imaging informatics expertise to a range of biomedical and healthcare research challenges. Similarly, his expertise in foundation AI models, especially protecting them against adversarial attacks, will be invaluable in collaborations developing and implementing such models in research and healthcare settings.