I obtained my Ph.D. degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT) in 2013. While at MIT, I was a member of the Laboratory for Computational Physiology and Clinical Inference under the direction of Professor George C. Verghese, and a research fellow at the Brigham and Women's Hospital and the Harvard Medical School, where I held a National Research Service Award (NRSA) under the supervision of Professor Atul Malhotra. I have worked and published on several areas of research, including advanced signal processing and machine learning techniques, computational neuroscience/brain machine interface, physiological control systems, predictive monitoring in intensive care unit, and nonlinear and nonstationary multidimensional time-series analysis in massive temporal biomedical databases; resulting in over 40 peer-reviewed publications. As a James S. McDonnell postdoctoral fellow in complex systems at Harvard Intelligent Probabilistic Systems group (PI: Professor Ryan Adams) I obtained two years of postdoctoral training in Machine Learning. My postdoctoral work was focused on development of deep learning algorithms for pattern discovery in massive temporal biomedical datasets. I have recently been awarded a five year Mentored Career Development Award (K01) in biomedical big data science (FOA: HG14-007) through the NIH Big Data to Knowledge (BD2K) initiative to develop advanced analytic techniques for prediction of adverse events in the intensive care unit (ICU) at the Emory University School of Medicine. Please visit my Publications and Research for a summary of my previous and ongoing work (including my dissertation). RESEARCH INTERESTS: Physiological Signal Processing, Modeling and Control for Real-Time Clinical Decision Support; Deep Learning and Reinforcement Learning; Computational Neuroscience and Deep Brain Stimulation.
Shamim Nemati, Ph.D.
Assistant Professor at Emory School of Medicine