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Joseph A. November is an Associate Professor in the Department of History at the University of South Carolina, affiliated with the McCausland College of Arts and Sciences. His research focuses on the history of biomedical computing, distributed computing, and the intersection of technology and medicine. He holds a Ph.D. from Princeton University (2006), an M.A. from the University of Chicago (2002), and a B.A. from Hamilton College (1997). His work includes the award-winning book Biomedical Computing: Digitizing Life in the United States (2012), which explores the co-development of biomedicine and computing technologies. Current projects include Revolutions@home , examining distributed computing in protein folding research, and a biography of computing pioneer Robert S. Ledley. He has received grants from the NSF, NIH, and the Charles Babbage Institute. Teaching interests span the history of science and technology, including courses on the history of medicine, digital humanities, and the role of games in historical education. He actively contributes to professional organizations like SHOT and the History of Science Society. Awards include the Computer History Museum Prize (2013) and the National Institutes of Health DeWitt Stetten Fellowship (2007-2008). His research bridges historical analysis with contemporary issues in technology and biomedical ethics.

• History of Science and Technology
• Biomedical Computing
• History of Medicine
• +3 more

Shrikanth (Shri) Narayanan is a University Professor and holder of the Niki and Max Nikias Chair in Engineering at the University of Southern California (USC), serving as the inaugural Vice President for Presidential Initiatives. He leads the Signal Analysis and Interpretation Lab (SAIL) and holds joint appointments in Computer Science, Linguistics, Psychology, Neuroscience, Pediatrics, and Otolaryngology-Head and Neck Surgery. His research focuses on speech and audio processing, behavioral signal processing, and real-time MRI of speech production, with applications in healthcare, education, and technology. Education: B.E. in Electrical Engineering from College of Engineering, Guindy (Chennai, India, 1988); M.S., Engineer, and Ph.D. in Electrical Engineering from UCLA (1990, 1992, 1995). Research interests span computational linguistics, machine learning, and multimodal human behavior analysis. He pioneered technologies for speech biomarkers in mental health, real-time MRI of speech production, and wearable sensor systems for longitudinal health studies. His work in speech emotion recognition, forensic interviews, and clinical applications has been recognized through over 40 awards, including the IEEE Flanagan Award and ISCA Medal. He has published extensively in journals like Proceedings of the IEEE , Journal of the Acoustical Society of America , and PLOS One . Key Grants: NSF CAREER, Okawa Research, IBM Faculty, Google/Amazon awards. Labs/Teams: Signal Analysis & Interpretation Lab (SAIL), USC Information Sciences Institute (ISI), Google Visiting Faculty Researcher.

• Speech and Audio Processing
• Behavioral Signal Processing
• Real-Time MRI of Speech Production
• +4 more

Polina Golland is a Professor in the Department of Electrical Engineering and Computer Science (EECS) at MIT and a Principal Investigator in the Computer Science and Artificial Intelligence Laboratory (CSAIL). Her research focuses on developing novel techniques for biomedical image analysis and understanding, particularly in medical vision, AI/ML, and health care applications. She leads the Medical Vision Group and collaborates with the Vision Group at CSAIL. Her work emphasizes statistical modeling of medical images, shape modeling, and predictive analytics for biological processes. Current projects include fetal MRI analysis, cardiac MRI segmentation, and quantitative assessment of pulmonary edema in chest X-rays. She has secured grants from NIH, MIT-IBM Watson AI Lab, and other institutions to support her research. Dr. Golland teaches courses on inference, probability, and probabilistic systems. She advises graduate students in MIT's EECS program and has mentored numerous postdocs and researchers. Her lab focuses on translating advanced imaging techniques into clinical workflows, with applications in neuroimaging, fetal health monitoring, and cardiovascular disease analysis. Notable collaborations include work with Harvard Medical School affiliates, Brigham and Women's Hospital, and the MIT Jameel Clinic. Her research aims to bridge computational methods with clinical needs, improving diagnostic tools and treatment planning through machine learning and medical imaging innovation.

• Biomedical Image Analysis
• Medical Vision
• AI & Machine Learning
• +8 more

Kenneth S. Breuer is a Professor of Engineering at Brown University, serving as Director of the Center for Fluid Mechanics. He holds appointments in the School of Engineering and collaborates across disciplines, including Biology and Physics. His research focuses on fluid mechanics, animal flight mechanics (particularly bats), bacterial motility, renewable energy, and turbulence. Breuer earned his Sc.B. from Brown University and M.Sc./Ph.D. from MIT, returning to Brown in 1999 after faculty service at MIT. Education: Sc.B. (Brown), M.Sc./Ph.D. (MIT). Awards include Fellowships from the American Physical Society and American Society of Mechanical Engineers, and the Harold and Esther Edgerton Chair at MIT. He has authored over 100 publications and edited books such as *Microscale Diagnostic Techniques*. Research Interests: Fluid mechanics at micro/nanoscales, bio-inspired flight mechanisms, energy harvesting, and vortex dynamics. Collaborations include Professors Sharon Swartz (Biology) and Thomas Powers (Engineering). Current projects explore bat wing aerodynamics, membrane hydrofoils, and aerosol transmission in vehicles. Awards: APS Division of Fluid Dynamics Chair (2012), Midwest Mechanics Lecturer, and multiple fellowships. Teaching includes courses in Fluid Mechanics, Transport Phenomena, and Renewable Energy Systems. His lab develops bio-inspired robotic systems and studies flow interactions in animal and engineered systems.

• Fluid Mechanics
• Animal Flight
• Bacterial Motility
• +4 more

Bobak Mortazavi is an Associate Professor in the Department of Computer Science & Engineering at Texas A&M University. His research focuses on medical analytics, machine learning, wearable sensors, and cyber-physical systems. He leads interdisciplinary projects in healthcare technology, including AI-driven diagnostics and predictive modeling for cardiovascular diseases. He has received notable awards such as the Best Demonstration Award at IEEE EMBS 2012 and the Best Paper Award at the Fourth International Conference on Data Analytics 2015. His work bridges machine learning with clinical applications, emphasizing practical solutions for healthcare challenges. Recent research includes developing AI tools for aortic stenosis detection, electrolyte estimation via ECG, and real-time patient monitoring systems. He collaborates with industry and academic partners to advance telemedicine and wearable health technologies. Key contributions include the SMART-LV project for smartphone-based cardiac diagnostics and the ArterialNet framework for blood pressure reconstruction using wearable sensors. His work is published in top journals like IEEE Journal of Biomedical and Health Informatics and Elsevier's Pervasive and Mobile Computing.

• Medical analytics
• Machine learning
• Embedded systems design
• +3 more

Josh Seim is an Assistant Professor of Sociology at Boston College, affiliated with the Morrissey College of Arts and Sciences. His work focuses on the sociologies of work, medicine, welfare, punishment, pedagogy, and ethnographic methods. He holds a Ph.D. from the University of California, Berkeley, and has published widely in top journals including *American Sociological Review* and *Social Problems*. Education: B.A., Gonzaga University M.S., Portland State University Ph.D., University of California, Berkeley Research Interests: His research explores how institutions like healthcare systems, welfare offices, and penal institutions interact with urban poverty. Recent projects include studies on ambulance crews’ labor processes, welfare bureaucracy, and post-prison labor. His writing also emphasizes pedagogical innovation in sociology teaching and ethnographic methodological rigor. Key themes include the governance of suffering, medical labor, and carceral systems. Publications & Books: Bandage, Sort, and Hustle: Ambulance Crews on the Front Lines of Urban Suffering (UC Press, 2020) The Welfare Assembly Line: Public Servants in the Suffering City (forthcoming UC Press, 2026) Teaching: Sociology 7715: Classical Sociological Theory (graduate) Sociology 7716: Contemporary Sociological Theory (graduate)

• Sociology
• Medical Sociology
• Welfare Studies
• +5 more

Rolf Halden is a Professor and Center Director at Arizona State University, holding appointments in the School of Sustainable Engineering and the Built Environment, the Biodesign Center for Environmental Health Engineering, and the Global Futures Scientists and Scholars program. He is a leading expert in environmental health engineering, wastewater-based epidemiology, and bioremediation. Education: Ph.D. in Civil (Environmental) Engineering, University of Minnesota (1997) M.S. in Civil (Environmental) Engineering, University of Minnesota (1994) M.S. in Biology, Technical University of Braunschweig, Germany (1992) Postdoctoral Fellow, Environmental Science, Lawrence Livermore National Laboratory (1998) Research Focus: Halden’s research integrates environmental chemistry, public health, and sustainability to understand how anthropogenic chemicals affect ecological and human health. His lab uses advanced mass spectrometry (LC-MS/MS, MALDI-TOF) to track pollutants such as PPCPs, microplastics, pesticides, and dioxins across air, water, soil, and biological systems. He pioneered the use of wastewater treatment plants as public health observatories, enabling real-time tracking of disease, drug use, and environmental exposures. Scientific Awards & Recognition: Leadership Award, Arizona State University (2018) Rocky Mountain Emmy Award (2018) Leroy E. Burney Lecturer, Johns Hopkins School of Public Health (2011) ACS Expert Program Member (2014–present) NIEHS Superfund R01 Working Group National Leader (2012–2014) Labs & Teams: Halden is the Founding Director of the Biodesign Center for Environmental Health Engineering at ASU, where he leads a multidisciplinary team focused on environmental proteomics, bioremediation, and diagnostic tool development. He also co-leads the Human Health Observatory , a national wastewater monitoring network. Grants & Funding: Halden has secured major funding from NSF, NIH, EPA, DoD, and private industry. Notable projects include the development of in-situ groundwater monitoring devices, national wastewater surveillance of SARS-CoV-2, and studies on microplastics and neurodegenerative disease.

• Environmental Health Engineering
• Wastewater-Based Epidemiology
• Bioremediation
• +7 more

Byron Wallace is the Sy and Laurie Sternberg Interdisciplinary Associate Professor at Northeastern University's Khoury College of Computer Sciences, where he also serves as Associate Dean for Research and Director of the BS in Data Science Program. His research focuses on Natural Language Processing and Machine Learning applications in healthcare. Education Details of formal education are not explicitly provided in the available text, though he holds a PhD from Tufts University (mentioned in thesis award context). Research Interests His work centers on developing NLP and ML models for health applications, with particular emphasis on: Biomedical evidence synthesis automation Electronic Health Record processing Model interpretability and trustworthiness Human-in-the-loop systems Learning with limited supervision Research Trends Recent publications demonstrate strong focus on large language model applications in healthcare, including factuality evaluation for medical summarization, evidence extraction from clinical trials, and interpretable risk prediction models. Notable contributions include work on GPT-3 applications in medical evidence synthesis and neural methods for EHR analysis. Scientific Awards ACL Outstanding Paper Award (2022) ICLR Spotlight (top 5% acceptance) (2024) Best Student-led Paper Award at AMIA 2021 NSF CAREER Award (2018-2023) Advising and Grants Currently advises 4 PhD students and has mentored numerous others. Major funding includes: NSF CAREER Award ($500K+) NIH R01 grant for EHR summarization NSF Medium grant for healthcare summarization Support from Army Research Office, Amazon, and Seton Hospital Labs and Teams Leads the Evidence Inference project team working on automated biomedical evidence synthesis. Collaborates with Brigham and Women's Hospital, Mass General Hospital, and Reboot Rx for clinical translation of research.

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +5 more

Dr. Mo Rastgaar is a Professor at Purdue Polytechnic Institute, Purdue University. He holds a PhD in Mechanical Engineering from Virginia Tech (2008) and completed a postdoctoral fellowship at MIT's Newman Laboratory for Biomechanics and Human Rehabilitation. He leads the Human-Interactive Robotics Lab (HIRoLab), focused on assistive and rehabilitation robots for enhanced mobility, particularly lower-extremity devices. His research emphasizes understanding agile gait dynamics through human experiments and modeling. Research interests include assistive robotics, cyber-physical systems, dynamics, and control systems. Notable awards include the 2014 NSF CAREER Award. He has secured grants such as the 2019 NRI Collaborative Grant on robotic ankle prosthetics and 2020 grants for undersea infrastructure. Dr. Rastgaar's work bridges biomechanics, robotics, and clinical applications, advancing prosthetic designs and human-robot interaction. Key contributions include developing steerable powered ankle-foot prostheses and exploring multi-robot systems for underwater exploration. His labs integrate interdisciplinary approaches to solve complex mobility challenges, emphasizing both technical innovation and real-world clinical impact.

• Assistive Robotics
• Rehabilitation Robotics
• Cyber-Physical Systems
• +3 more

Daniel W. Bliss is a Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University and Director of ASU's Center for Wireless Information Systems and Computational Architectures (WISCA). With over $50 million in research funding as principal investigator from organizations including DARPA, ONR, Google, and Airbus, his work bridges theoretical foundations with practical implementations across multiple domains of wireless systems. Dr. Bliss received his educational foundation with a B.S.E.E. from Arizona State University (1989), followed by M.S. and Ph.D. degrees in Physics from the University of California-San Diego (1995, 1997). His academic journey includes significant industry experience at General Dynamics (1989-1993) and MIT Lincoln Laboratory (1997-2012) before joining ASU. His research program focuses on advanced wireless systems spanning radar, communications, precision positioning, computational architectures, and medical monitoring applications. Bliss employs information theory, estimation theory, and signal processing to develop novel system concepts with disruptive capabilities. Current research emphasizes RF convergence, integrated sensing and communications, and anticipatory medical analytics using wireless technologies, with particular focus on extracting physiological data from radar signals. Analysis of recent publications reveals a strong trend toward integrated sensing and communications systems, particularly utilizing mmWave and radar technologies for medical monitoring applications. His work increasingly bridges traditional communications and radar domains while expanding into physiological monitoring, demonstrating a clear trajectory toward convergence of wireless technologies for healthcare applications and remote vital sign detection. Dr. Bliss has received significant recognition for his contributions: Fellow of the IEEE (2015) 2021 IEEE Warren D. White Award for Excellence in Radar Engineering 2016-2017 Top 5% Teaching Award at ASU 2017 ASU Fulton Engineering Exemplar Faculty As a dedicated mentor, Dr. Bliss has supervised numerous graduate students through successful dissertation and thesis defenses across both PhD and Master's programs. His research portfolio includes substantial funding from diverse sources with over $50 million secured as principal investigator. Current projects include the $17M DARPA DASH project focused on advanced software-reconfigurable heterogeneous SoCs for next-generation RF systems, and multiple initiatives in contactless vital sign monitoring using radar technologies. Dr. Bliss leads the BLISS Lab and serves as director of WISCA, fostering interdisciplinary research in wireless systems. His team includes researchers working on distributed coherent systems, MIMO radar, RF convergence, and medical monitoring applications, with recent successes including the Making Waves team that tied for first place in the Air Force Spark Tank challenge. He has founded two startup companies: DASH Tech Integrated Circuits Company and the Big Little Sensor Company, focusing on high-performance embedded processing and small-scale radar physiological monitoring, respectively.

• Radar
• Wireless Communications
• Precision Positioning
• +7 more

John Oakey is a Professor and Graduate Coordinator in the Department of Chemical and Biomedical Engineering at the University of Wyoming, with additional affiliations to the INBRE Program, Molecular and Cellular Life Sciences Program, and Materials Science and Engineering Program. Education Postdoctoral Fellow, Center for Engineering in Medicine, Massachusetts General Hospital & Harvard Medical School (2007–2010) Ph.D. Chemical Engineering, Colorado School of Mines (2003) M.S. Chemical Engineering, Colorado School of Mines (1999) B.S. Chemical Engineering, Penn State University (1997) Research Interests Oakey’s laboratory integrates fluid dynamics, colloidal science and materials science to understand how biological systems behave under flow, on surfaces and within complex 3-D geometries. A unifying theme is the use of microfabrication and microfluidics to create new diagnostic, prognostic and therapeutic platforms. Current thrusts include: Heterogeneous biomaterials: self-assembled particulate tissue scaffolds whose mechanical and transport properties can be temporally programmed. Inertial microfluidics: exploiting lift forces for membrane-free particle sorting, enrichment and diagnostics. Multi-temporal analysis by flow cytometry: development of closed-loop, high-throughput microfluidic cytometers for longitudinal single-cell studies. Publication Trends From 2025 back to 2010, Oakey’s articles reveal a consistent trajectory that marries fundamental physics (microtubule mechanics, inertial focusing) with translational applications (cell encapsulation, tissue scaffolds, drug delivery). Recent work (2023-2025) increasingly targets injectable granular hydrogels, single-cell therapeutic delivery and sustainable carbon-sequestering living materials, demonstrating an evolution from microscale transport phenomena to macroscopic biomedical and environmental impact. Scientific Awards No named awards are listed in the supplied text. Advising & Coordination Roles As Graduate Coordinator for the Department of Chemical and Biomedical Engineering, Professor Oakey oversees graduate program development and student mentoring. While no individual students are named, his role implies active supervision of M.S. and Ph.D. advisees in chemical and biomedical engineering. Laboratory & Teams The Oakey Research Group operates from the Energy and Environmental Research Building (EERB 435A) at the University of Wyoming. The lab enjoys R1-level research infrastructure and collaborates broadly with the Wyoming INBRE network, the Molecular and Cellular Life Sciences Program, and the Materials Science and Engineering Program.

• Microfluidics
• Microscale transport phenomena
• Tissue engineering and regenerative medicine
• +4 more

Minseok Ryu is an Assistant Professor at the School of Computing and Augmented Intelligence, Arizona State University (ASU). He holds a Ph.D. in Industrial & Operations Engineering from the University of Michigan (2020). Prior to ASU, he was a postdoctoral appointee at Argonne National Laboratory’s Mathematics and Computer Science Division. His research focuses on optimization methodologies for decentralized and stochastic decision-making distributed algorithms for machine learning and operations research applications in healthcare systems and energy grids Teaching responsibilities include courses on applied deterministic operations research (IEE 574), optimization (IEE 622), and research practicums (IEE 792). His work emphasizes computational challenges in decision-making under uncertainty, with recent projects addressing nurse staffing optimization, federated learning frameworks (e.g., APPFL/APPFLX), and resilient power grid systems. He has no recorded academic awards but actively contributes to open-source software and cross-disciplinary research collaborations. Research interests bridge theory and practice, targeting social goods through optimization techniques like distributionally robust optimization, federated learning, and heuristic algorithms for energy and healthcare systems.

• Operations Research
• Machine Learning
• Optimization under Uncertainty
• +4 more

Nancy Margaret Reid is a University Professor of Statistical Sciences at the University of Toronto, holding the Canada Research Chair in Statistical Theory and Applications. She has served as Scientific Director of the Canadian Statistical Sciences Institute (2015–2019) and led the Department of Statistical Sciences as Chair (1997–2002). Her research focuses on theoretical statistics, particularly likelihood inference and foundational aspects of statistical methodology. Reid earned her PhD from Stanford University (1979) under Rupert G. Miller, with Brad Efron and Vernon Johns on her committee. Reid's accolades include Fellowships from the Royal Society, Royal Society of Canada, and National Academy of Sciences, as well as the Guy Medal in Gold (2022) and David R. Cox Award (2023). She has authored influential books like *Theory of the Design of Experiments* and contributed to courses on mathematical statistics and likelihood inference. Active in academic service, she teaches graduate-level courses and has advised numerous students and postdocs in theoretical and applied statistical research.

• Theoretical Statistics
• Likelihood Inference
• Design of Studies
• +3 more

Ram Vasudevan is an Associate Professor and Associate Chair of Graduate Studies in the Department of Robotics at the University of Michigan. His research focuses on developing tools for safe and robust deployment of robotic systems, emphasizing optimization, nonlinear control, and real-world applications. Key areas include legged robot locomotion, shared control systems, and safety-critical autonomous systems. Research Interests: Optimization and control of nonlinear systems, locomotion of legged robots, shared control active safety systems, and automation of diagnostic/rehabilitative tasks. His ROAHM Lab prioritizes mathematical guarantees for robotic performance, with applications in medical robotics, autonomous vehicles, and soft robotics. Recent work emphasizes trajectory optimization, sensor fusion, and safety-aware control strategies. He has contributed to benchmarks for autonomous vehicle perception and novel methods in thermal image restoration using neural radiance fields. Awards: None explicitly listed in provided text. Labs/Teams: Directs the ROAHM Lab, collaborating on projects like robotic tail mechanics, real-time motion planning, and sensor data analysis. Active in academic conferences including RSS and ICRA.

• Optimization and control of nonlinear systems
• Legged robot locomotion
• Autonomous systems safety
• +4 more

Alex Wong is an Assistant Professor of Computer Science at Yale University, specializing in computer vision, robotics, and medical imaging. His research focuses on sensor fusion, unsupervised learning, 3D vision, robust perception under adverse conditions, and medical image analysis. He holds degrees from the University of California, Los Angeles (UCLA), including a B.S., M.S., and Ph.D. in Computer Science. Wong’s work bridges theoretical advances with practical applications, particularly in depth estimation, autonomous systems, and medical diagnostics. He has received prestigious awards such as the NeurIPS Outstanding Student Paper Award (2011) and the ICRA Best Paper Award in Robot Vision (2019). His research often addresses challenges in unstructured environments, emphasizing robustness and adaptability. Recent projects include developing novel frameworks for unsupervised depth completion, adversarial robustness in vision systems, and multimodal fusion techniques. His contributions span conferences like CVPR, ICCV, and ICRA, with a strong focus on advancing AI for real-world applications in healthcare and robotics. Education: B.S., Computer Science, UCLA M.S., Computer Science, UCLA Ph.D., Computer Science, UCLA Awards: NeurIPS Outstanding Student Paper Award (2011) ICRA Best Paper Award in Robot Vision (2019) His lab at Yale Engineering focuses on AI-driven solutions for perception challenges, collaborating across disciplines to advance medical imaging and autonomous systems. Current efforts explore generative models, continual learning, and vision-language integration for robust scene understanding.

• Sensor fusion
• Unsupervised learning
• 3D vision
• +2 more