Trainee Profile

Mohammad M. Ghassemi, BSc, MPhil

Mohammad Ghassemi 2017 T32 pre-doc

Administrative Title(s)

PhD Candidate, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology

See publications


Address

540 Memorial Drive
#603
Cambridge, MA 02139
USA

Phone 617-599-6010

Email ghassemi@mit.edu

Society Memberships

IEEE
ACM

Research Unit(s)

Laboratory of Computational Physiology

Research Interests

Mohammad Ghassemi is a doctoral candidate at the Massachusetts Institute of Technology. As an undergraduate, he studied Electrical Engineering and graduated as both a Goldwater scholar and the University's "Outstanding Engineer". Mohammad later pursued an MPhil in Information Engineering at the University of Cambridge where he was a recipient of the prestigious Gates-Cambridge Scholarship. Since arriving at MIT in 2011, he has pursued research which has allowed him to leverage his knowledge of machine learning and background in hardware/sensor design to enhance critical care medicine. Mohammad's doctoral focus is machine learning techniques in the context of multi-modal, multi-scale datasets. He has currently put together the largest collection of post-anoxic coma EEGs in the world, which he is investigating for his doctoral thesis. He has published in several top Artificial Intelligence and Medical venues including: Nature, Science,  Intensive Care Medicine, AAAI and KDD. Mohammad's work has been internationally recognized by venues including: BBC, NPR, The Wall Street Journal, Newsweek. In addition to his research efforts, Mohammad is also involved in a range of entrepreneurial activities including a platform to facilitate connections between students, and an algorithm for social coaching.

Mentor(s)

Dr. Emery N. Brown
Dr. Roger G. Mark

Research Funding

T32 HL 007901
Training in Sleep, Circadian, and Respiratory Neurobiology

Selected Publications

Original articles

A Moskowitz, K Chen, A Cooper, A Chahin, MM Ghassemi, LA Celi. Management of Atrial Fibrillation with Rapid Ventricular Response in the Intensive Care Unit: A Secondary Analysis of Electronic Health Record Data, Shock (2017).

T Pollard, A Johnson, L Shen, L Lehman, M Feng, MM Ghassemi, B Moody, P Szolovits, LA Celi, and RG Mark. MIMIC-III, A Freely Accessible Critical Care database, Nature Scientific Data (2016).

J Salciccioli, MM Ghassemi et al. A Datathon Model to Support Cross-Disciplinary Collaboration, Science Transnational Medicine(2016).

AEW Johnson, MM Ghassemi, S Nemati, KE Niehaus, D Clifton, GD Cliford. Machine Learning and Decision Support in Critical Care, Proceedings of the IEEE (2016).

MM Ghassemi, SE Richter, IM Eche, TW Chen, J Danziger, LA Celi. A Data-Driven Approach to Optimized Medication Dosing: A Focus on Heparin, Intensive Care Medicine (2014).

ND Shaw, JP Bulter, S Nemati, T Kangarloo, MM Ghassemi, A Malhotra, JE Hall. Nocturnal pulsatile LH secretion is preserved even during fragmented deep sleep in pu-
bertal children, Journal of Clinical Endocrinology & Metabolism (2014).

NMT Houlsby, F Huszar, MM Ghassemi, G Orban, DM Wolpert, M Lengyel. Cognitive Tomography Reveals Complex Task-independent Mental Representations,Current
Biology (2013).

J Liu, MM Ghassemi, AM Michael, D Boutte,W Wells, N Perrone-Bizzozero, F Macciardi, DH Mathalon, JM Ford,SG Potkin, JA Turner, VD Calhoun. An ICA with Reference Approach in Identification of Genetic Variation and Associated Brain Networks,Frontiers of Human Neuroscience (2012)

Site Map | Contact Us | © 2017 by the President and Fellows of Harvard College