Critical Care Informatics Group
Professor Thomas Heldt
W.M. Keck Career Development Professor in Biomedical Engineering
Associate Professor of Electrical and Biomedical Engineering
Thomas Heldt joined the MIT faculty in 2013 as Hermann L.F. von Helmholtz Career Development Professor in the Institute for Medical Engineering & Science and as Assistant Professor of Electrical and Biomedical Engineering with the Department of Electrical Engineering and Computer Science. Additionally, Thomas is a Principal Investigator with MIT’s Research Laboratory of Electronics (RLE).
Thomas studied Physics at Johannes Gutenberg University, Germany, at Yale University, and MIT. In 2004, he received the PhD degree in Medical Physics from MIT's Division of Health Sciences and Technology and commenced postdoctoral training at MIT's Laboratory for Electromagnetic and Electronics Systems. Prior to joining the faculty, Thomas was a Principal Research Scientist with the RLE, where he co-founded and co-directed (with Prof. George Verghese) the Computational Physiology and Clinical Inference Group.
Thomas's research interests focus on signal processing, mathematical modeling, and model identification to support real-time clinical decision making, monitoring of disease progression, and titration of therapy, primarily in neurocritical and neonatal critical care. In particular, Thomas is interested in developing a mechanistic understanding of physiologic systems, and in formulating appropriately chosen computational physiologic models for improved patient care. His research is conducted in close collaboration with colleagues at MIT and clinicians from Boston-area hospitals.
RLE Bio | email@example.com
Caitlin Vinci holds a BA in English from the University of Massachusetts Amherst, a Post-Baccalaureate Teaching Licensure from Bridgewater State University, and a Graduate Certificate in Programming from Harvard Extension School. She worked for the Vice Provost of Research at Tufts University, the Office of Admissions and Financial Aid at Suffolk University Law School, and as a teacher at Mashpee Public Schools before joining MIT in May of 2014. Caitlin currently supports three faculty members and their research groups in MIT's Institute for Medical Engineering and Science, utilizing her organizational and communication skills to keep on top of administrative tasks.
Minoru Matsushima received his B.A. in Basic Life Sciences in 2006, and his M.S./Ph.D. in Computational Biology in 2008 and 2011, respectively, all from the University of Tokyo. From 2008 to 2011, he was a research fellow with the Japan Society for the Promotion of Science (JSPS) and a member of the Brain and Neural Systems Team in the Next-Generation Integrated Simulation of Living Matter Project at RIKEN. Since 2011, he has been working in Nihon Kohden Corporation, a medical equipment company in Japan, as an embedded technology software engineer. His research interests include medical device application, biomedical signal processing, and system identification and modeling of living matter.
Andrea Fanelli is a Research Scientist at the Integrative Neuromonitoring and Critical Care Informatics Group of MIT's Institute for Medical Engineering & Science and the Research Laboratory of Electronics. He received the B. S. and M.S. degrees in Biomedical Engineering from Politecnico di Milano, Italy, in 2007 and 2009, respectively. He received his PhD at the Department of Bioengineering of Politecnico di Milano in May 2013, after spending 9 months as a visiting PhD student with the Computational Physiology and Clinical Inference Group at MIT. In his doctoral thesis he developed a wearable device for fetal ECG monitoring during pregnancy. He started his postdoc at MIT in May 2013 and became a Research Scientist in April 2017. He is currently working on noninvasive estimation of intracranial pressure. His research focuses on algorithm development, signal and image processing, hardware design and data analysis.
Varesh Prasad is a Ph.D. student in Medical Engineering & Medical Physics in the Health Sciences & Technology program at MIT and Harvard Medical School. Prior to beginning his graduate studies in 2013, Varesh earned a B.S.E. in bioengineering at the University of Pennsylvania in 2008 and subsequently worked at an Indian medical devices company as a Whitaker International Fellow for a year. His research interests currently involve taking advantage of the wealth of information available about individual patients in the hospital, including real-time physiological signals and medical records data, to enhance critical care monitoring and to predict serious adverse events.
Jeffrey Peterson is a Research Affiliate at INCCI from the Massachusetts General Hospital Emergency Department where he is a software engineer developing real-time clinical decision support technologies. Prior to joining MIT, Jeff spent two years as a Clinical Engineer for the MGH Medical Device Plug and Play Interoperability Research Lab (MD PnP) where he worked on medical device communication standards and prototypes, including OpenICE (the Open-source Integrated Clinical Environment). He holds an M.S. in Biomedical and Clinical Engineering and a B.S. in Biomedical Engineering, both from the University of Connecticut in 2013 and 2011, respectively. Jeff worked as a Clinical Engineer at UMass Memorial Medical Center in Worcester, MA where he completed his Master’s thesis on clinical alarm management. His research interests include improving patient care and safety by surfacing new insights from data within existing medical device systems and improving the pathway for adoption of novel healthcare IT research.
Freddie is a Research Fellow at Boston Children’s Hospital, Harvard Medical School and a Research Affiliate in the INCCI group at MIT. After completing his medical degree and an intercalated research degree in Neuroscience at the University of Cambridge and University College London in the UK, Freddie worked as a medical doctor in an academic post at Oxford University’s Clinical Academic Graduate School and the John Radcliffe Hospital. During this time, he had clinical jobs in acute general medicine, intensive care and emergency medicine. His previous research was in computational genetics. He came to the US in 2015 to begin his research fellowship in the field of cerebral autoregulation with Prof. Robert Tasker, director of Neurocritical Care at Boston Children’s Hospital. At MIT, Freddie is using different measurement techniques, including transcranial Doppler and near-infrared spectroscopy to measure changes in cerebral hemodynamics in response to the autonomic challenges imposed by a tilt-table.
Rohan is pursuing his Ph.D. in Electrical Engineering and Computer Science (EECS) at MIT. He received his Bachelor's of Technology degree in Electrical Engineering from the Indian Institute of Technology (IIT), Madras in 2015. He worked as a research intern in the Institute for Computational Medicine at Johns Hopkins University in 2014, where he worked on a project on sepsis detection using a network-based classification approach in Prof. Sridevi Sarma's lab. His current research is in developing a spectral technique to non-invasively estimate intracranial pressure of patients in ICUs, utilizing the arterial blood pressure and cerebral blood flow velocity waveforms and deploying these systems in hospitals.
James Lynch received a B.S. in physics and applied mathematics from the University of Rhode Island in 2015. He is currently conducting research with the Integrative Neuromonitoring and Critical Care Informatics Group at MIT. Ongoing research topics include a collaboration with Massachusetts General Hospital where he is participating in the development of a consolidated database of patients presenting to the emergency room.
Kai E. Thomenius
Visiting Research Scientist
Kai E. Thomenius is currently a Research Scientist at the Institute of Medical Engineering and Science in MIT, Cambridge, MA. Until recently, he was a Chief Technologist in Diagnostics & Biomedical Technologies at General Electric Global Research in Niskayuna, NY, USA. Previously, he has held senior R&D roles at ATL Ultrasound Inc. (now Philips Healthcare), Interspec Inc., Elscint Inc., as well as other companies. In addition, he has been an Adjunct Professor in the Electrical, Computer, and Systems Engineering Department at Rensselaer Polytechnic Institute. Dr. Thomenius' academic background is in electrical engineering with a minor in physiology with degrees from Rutgers University. His long-term interests have been in beamformation and miniaturization of ultrasonic scanners, propagation of acoustic waves in inhomogeneous media, delivery and drugs and DNA to cells, and gaining physiological information from echoes that arise from acoustic beams. His current focus is on estimation of speed of sound in tissues and the impact that its variations has on image quality. Dr. Thomenius is a Fellow of the American Institute of Ultrasound in Medicine.
Syed M. Imaduddin
Syed M. Imaduddin is a first year Ph.D. candidate in the Electrical Engineering and Computer Science (EECS) department at MIT where he is working in Professor Thomas Heldt’s group. He graduated from the National University of Science and Technology (NUST), Pakistan in 2015 with a major in Electrical Engineering. Imad is interested in developing model based biomedical signal processing algorithms and devices to monitor and regulate patient health. He is presently working on algorithms for continuous noninvasive blood pressure estimation.
Gladynel Saavedra Peña
Gladynel Saavedra Peña received her B.S. degree in Electrical Engineering from the University of Puerto Rico in Mayagüez (UPRM) in 2016. Gladynel is currently a PhD student pursuing her Master’s Degree under the supervision of Prof. Vivienne Sze and Prof. Thomas Heldt. Her research focuses on developing models and algorithms for detecting the onset of Alzheimer’s Disease in patients with Mild Cognitive Impairment and early dementia. These models and algorithms will eventually be transferred onto low power systems. Gladynel was a recipient of the MIT Presidential Fellowship in 2016.
Hsin-Yu Jane Lai
Hsin-Yu Lai received the B. S. degree in EE and math from National Taiwan University. She completed her M. S. degree in Electrical Engineering and Computer Science from MIT in 2016 with Prof. Alan Oppenheim on amplitude sampling. She is currently pursuing a Ph.D. with Prof. Vivienne Sze and Prof. Thomas Heldt. Her research interests include signal processing, inference, and machine learning.
B.S. in Mechanical Engineering, MIT
Medical Student, Health Sciences and Technology MD program at MIT and Harvard Medical School
B.S. in chemical and biomedical engineering, Carnegie Mellon University
Medical Student, Brown University School of Medicine
Sarah L Hensley
Sarah Hensley is an M.Eng. student in the Electrical Engineering and Computer Science (EECS) department at MIT. She previously completed her B.S. in EECS at MIT in 2017. Her current research involves working to reduce false and nuisance alarm rates in the intensive care unit.
Daniel Teichmann received Dipl.-Ing. and Dr.-Ing. (Ph.D.) degrees in electrical engineering from RWTH Aachen University, Aachen, Germany, in 2009 and 2015, respectively. In his doctoral thesis, he worked on non-contact monitoring of cardiorespiratory activity. In 2015, he was appointed Senior Scientist and head of the medical instrumentation group at the Philips Chair for Medical Information Technology at RWTH Aachen University. In 2018, he began a postdoctoral fellowship at the Integrative Neuromonitoring and Critical Care Informatics Group of MIT's Institute for Medical Engineering & Science. His research interests include unobtrusive vital sign monitoring, biomedical signal processing, and sensor fusion.
Rajib is a visiting student researcher at MIT, where he is working on micro emboli detection through ultrasound systems in ECMO and life support machines. He is a M.Sc.-student in electrical engineering at RWTH Aachen University and a 4th-year medical student at Heinrich-Heine University Düsseldorf, Germany. He has previously been a research intern at Siemens Corporate Research in Princeton, working on topics related with perception, computer vision, and deep learning. During his Bachelor thesis, he worked in Prof. Leonhardt's research group in Aachen and built a pulsatile cerebrospinal model with a cardio-vascular coupling for hydrocephalus patients. His current interests are in biomedical signal processing and quantitative modeling of physiological systems to give doctors tools that help them to make better decisions in critical situations.
Karen Brastad Evensen
Karen Brastad Evensen is currently pursuing a PhD in noninvasive intracranial pressure estimation at the University of Oslo under the supervision of Prof. Eide, Prof. Holm and Dr. Prieur. The PhD project is a collaboration between Oslo University Hospital and the Digital Signal Processing and Image Analysis Group at UiO. Prior to her PhD studies, Karen received an M.Sc. degree in Applied Physics from the Norwegian University of Science and Technology. Her master thesis was written at the NTNU Acoustics group on the topic of wave propagation in annular tubes. She subsequently worked as an acoustic consultant for two years before joining the PhD program.
A spectral approach to noninvasive model-based estimation of intracranial pressure
An Embedded Device for Real-Time Noninvasive Intracranial Pressure Estimation
PhD EECS, 2016
Learning and Model-Based Approaches to Improved Patient
Monitoring, Assessment and Treatment in Capnography and
B.S. in Mechanical Engineering, MIT
Medical Student, Health Sciences and Technology MD program at MIT and Harvard Medical School