Alex Chortos is an Assistant Professor of Mechanical Engineering at Purdue University's School of Mechanical Engineering. His research focuses on bio-inspired electronics, mechanically adaptive materials, and advanced manufacturing techniques. He leads the Chortos Lab, which explores innovations in soft actuators, wearable haptics, and polymer design. Chortos holds a B.A.Sc. from the University of Waterloo (2011), a Ph.D. from Stanford University (2017), and completed a postdoctoral fellowship at Harvard University (2020). His academic work bridges fundamental material science with practical applications in robotics, biomedical devices, and human-machine interfaces. Key research areas include: Multimaterial additive fabrication for soft robotics Stretchable sensors and transistors for e-skin applications Design of durable and adaptive polymer systems His publications emphasize advancements in 3D printing techniques, bioinspired sensor systems, and the development of mechanically robust electronic components. Recent work explores photodynamic polymers and machine learning-driven optimization of soft actuators.
Rahim Rahimi is an Assistant Professor of Materials Engineering at Purdue University, associated with the College of Engineering. His research focuses on advanced materials for biomedical applications, environmental sensing, and flexible electronics. Key interests include developing smart sensors for healthcare, antibacterial coatings for medical implants, and sustainable agricultural monitoring systems. Research emphasizes targeted drug delivery systems via smart capsules, environmental sensor networks for water quality and soil health, and nanotechnology applications in wearable devices. Notable projects include oxygen-generating surgical meshes for wound healing and low-cost wireless sensors for precision agriculture. His work bridges materials science with clinical and environmental challenges, leveraging plasma deposition techniques and nanomaterial functionalization. Recent efforts focus on self-calibrating sensors and integrating machine learning for manufacturing optimization. No scientific awards are explicitly listed in the provided information. His advisory role and grant activities are inferred through his research outputs in materials engineering and biomedical innovation. Rahimi collaborates across disciplines within Purdue's engineering ecosystem, contributing to labs focused on bio-inspired materials and flexible electronics. Future work aims to advance implantable medical devices and scalable sensor technologies for global health applications.
Sveta Zinger is a Full Professor in context-informed dynamic image analysis for clinical decision support at Eindhoven University of Technology (TU/e). She holds affiliations with the Biomedical Diagnostics Lab, NeuroPlatform, and EAISI Health. Her research focuses on medical image/video analysis, temporal data analysis, and machine learning for clinical applications. She has led projects funded by ZonMw, NWO, Philips, and others. She is also Co-Editor-in-Chief of Computer Methods and Programs in Biomedicine and serves on the Vidi committee for NWO. Education: MSc (2000) from Dnepropetrovsk State University; PhD (2004) from École Nationale Supérieure des Télécommunications, France. Postdoctoral roles at the French Atomic Agency and University of Groningen. Research Projects: Includes FORSEE (video monitoring for adverse events in healthcare) and NEUROTREND (fMRI biomarkers for depression). Awards: Second place in the CAMELYON17 challenge for metastases detection. Her teaching includes courses on DSP fundamentals, medical image processing, and cognitive neuroscience. She collaborates with clinical and industrial partners to advance biomedical diagnostics and healthcare technology.
Steven Devleminck is an Associate Professor in the Department of Computer Science at KU Leuven's Faculty of Engineering Technology, concurrently serving as coordinator of the School of Arts (Associated Faculty) in Brussels. His dual appointment bridges engineering and arts through the Human-Computer Interaction (HCI) group at Group T Leuven Campus and Unit Art & Technology in Brussels, with active membership in DigiSoc – KU Leuven Digital Society Institute. His research centers on human-centered computing and speculative design methodologies , with core expertise in tangible interaction for emotion regulation and multispecies futures. Key themes include biofuturing as co-creative response to climate crises, squeeze-based interfaces for workplace stress, and artistic AI collaborations. His work uniquely integrates computer science with choreography, film studies, and anthropology through projects like “Youth TikTok production as public pedagogy” and “Imagining the Post-Anthropocene in BioFutures Living Lab”. Analysis of recent publications reveals three dominant trajectories: (1) Advancement of squeeze interaction techniques for affective computing, (2) Development of biofuturing frameworks for multispecies speculation, and (3) Critical examinations of AI's role in artistic mediumship. Cross-cutting themes include post-anthropocentric design, climate-responsive technologies, and decolonial approaches to digital pedagogy. Devleminck actively mentors doctoral candidates including Ula Sickle (choreographic exhibitions) and J. Verbesselt (cinema studies), while leading major funded projects such as: Living Corpora (2025-2029): Pioneering human-AI collaboration in digital humanities as Co-promotor Experiential Futuring (2022-2026): Co-creative methodology for social media outage response as Co-promotor Deradicalizing the City (2021-2025): Urban intervention research as Promotor He serves on the Computer Science Department Council and Doctoral Committee for the Associated Faculty of Arts. His laboratory ecosystem spans the HCI Group T Leuven Campus for technical development, Brussels-based Unit Art & Technology for artistic integration, and BioFutures Living Lab for participatory multispecies experimentation. This tripartite structure enables transdisciplinary work connecting squeeze sensor engineering with climate futures speculation and museum interface design.
Mendel Rosenblum is the Cheriton Family Professor and holds dual appointments as Professor in the Departments of Computer Science and Electrical Engineering at Stanford University. He is a co-founder of VMware Inc. and served as its Chief Scientist for its first decade, playing a pivotal role in designing foundational virtualization technologies. Rosenblum's research focuses on system software, distributed systems, and computer architecture, with notable contributions to virtualization, data center networks, and operating systems. He leads the Platform Lab at Stanford, exploring next-generation data center technologies and high-performance computing systems. Administrative Role: Faculty Director of Stanford Computer Forum (2012–present) Education: PhD (UC Berkeley, 1992), MS (UC Berkeley, 1989), BA (University of Virginia, 1984) His research interests span disk storage management, computer simulation, scalable operating systems, and security. Recent work emphasizes deployable consensus algorithms, programmable smartNICs, and self-programming networks. Rosenblum has authored over 80 publications and holds multiple patents in virtualization and system software. Awards & Recognition: ACM System Software Award (2009) IEEE Computer Entrepreneur Award (2011) ACM Thacker Breakthrough in Computing Award (2018) Member, National Academy of Engineering (2013) He advises PhD and Master's students, including current advisees Sina Jandaghi Semnani and Zixi Liu. Rosenblum teaches advanced courses on web applications, distributed systems, and independent research projects.
Dr. Oscar Meruvia-Pastor is a faculty member in the Department of Computer Science at Memorial University of Newfoundland, within the Faculty of Science. He holds a B.Sc. from ITESM-Monterrey, Mexico, an M.Sc. from the University of Alberta, and a Ph.D. from Otto-von-Guericke Universität Magdeburg, Germany. His research focuses on interactive 3D graphics, non-photorealistic rendering, and biomedical visualization, with applications in telepresence systems, augmented reality (AR), and virtual reality (VR). He has developed tools like OMARC for respiratory condition training and GeNET for gene co-expression network analysis. Dr. Meruvia-Pastor has supervised numerous graduate students and contributed to over 50 publications. His work includes evaluating stereo correspondence methods in AR, robot arm manipulation via depth sensors, and smartphone integration in immersive VR. He has been recognized with awards such as the Best HCI Poster at Graphics Interface 2014 and a semi-finalist poster at SIGGRAPH 2015. He teaches courses in computer science, including computer graphics, multimedia development, and introductory science modules. His research lab focuses on 3D telepresence, medical visualization, and human-centered VR/AR solutions. His academic contributions span software tools for medical imaging analysis, interactive visualization systems, and educational technologies. He actively collaborates with health professionals to advance telemedicine and remote procedural training through AR platforms. His work bridges computer graphics with real-world applications in healthcare, education, and environmental advocacy.
Tengfei Ma is an Assistant Professor in the Department of Biomedical Informatics at Stony Brook University, with affiliations to Computer Science and Applied Mathematics & Statistics. He holds a Ph.D. from The University of Tokyo, M.S. from Peking University, and B.E. from Tsinghua University. Previously, he was a Research Scientist at IBM T.J. Watson Research Center. His research focuses on machine learning, natural language processing (NLP), and biomedical informatics, particularly deep graph learning, scalable graph methods, and healthcare applications. He has contributed to frameworks like EvolveGCN for dynamic graphs and IGB datasets for graph benchmarks. Key awards include ISWC 2021 Best Paper (Research Track) and IBM Outstanding Research Accomplishments (2019, 2022). His work bridges theory and practice, addressing challenges like over-dilution in GNNs and interpretable time series analysis. Collaborations span interdisciplinary areas, such as AI for wound monitoring and code summarization. He teaches BMI530: Software Development for Biomedical Informatics and is open to graduate students from CS, BMI, and AMS departments. Research highlights include: Deep Graph Learning: Scalability (FastGCN, IGB), dynamic graphs (EvolveGCN), and topology-enhanced GNNs. Healthcare: Models for EHR analysis, medication recommendation (GAMENet), and wearable wound monitoring. NLP: Document summarization, code summarization (CP-BCS), and commonsense generation via knowledge graph compression. Recent projects include AI tools like Influencer for promotional content creation and neural-symbolic models for interpretable time series analysis. His lab explores foundational AI for healthcare, code analysis, and graph systems.
Professor Mia Woodruff is a leading academic at Queensland University of Technology (QUT), holding the position of Professor in the School of Mechanical, Medical and Process Engineering within the Faculty of Engineering. She is the Group Leader of the Biofabrication and Tissue Morphology Group and Acting Director of the Herston Biofabrication Institute. Her research focuses on biofabrication, tissue engineering, and 3D printing applications in medicine, particularly in bone regeneration, vascular surgery, and personalized prosthetics. Woodruff holds a PhD in Materials Engineering from the University of Nottingham, UK. She has led over $40 million in external grants, including ARC and Advance Queensland funding. Her work emphasizes translating biofabrication technologies into clinical practice, such as developing patient-specific implants and surgical tools. She has published over 120 peer-reviewed articles and co-founded initiatives like the Herston Biofabrication Institute to bridge clinical, research, and industry collaboration. Key research areas include composite biomaterials, 3D scanning/modelling, electrospinning, and large-animal models for bone regeneration. She has been awarded the QUT Vice Chancellor’s Research Fellowship and ARC Fellowship. Her outreach efforts include promoting STEM through media appearances and school programs, such as the 3D Printing in All High Schools initiative. Grants & Awards $40M Innovation Manufacturing CRC (Co-Investigator) $3.72M ARC Industrial Transformation Training Center (Additive Biomanufacturing) Advance Queensland Fellowships ($1.2M Cluster Grant for Biofabrication) Media & Engagement Featured in SCOPE TV, SBS The Feed , and ABC News Keynote speaker at global conferences (e.g., TERMIS, ORS) Research Infrastructure Herston Biofabrication Institute: Integrates 3D printing, clinical trials, and patient collaboration World-first Biofabrication Master’s program launched in 2014
Shabaz Mohammed is an Associate Professor of Proteomics at the University of Oxford, holding joint appointments in the Departments of Chemistry and Biochemistry. Since 2020, he has served as Head of the Mechanistic Proteomics research programme at the Rosalind Franklin Institute. His research focuses on advancing proteomics technologies to study protein post-translational modifications and their roles in cellular processes, with applications in viral infections and disease mechanisms. Education: BSc in Chemistry, UMIST (now The University of Manchester), 1999 PhD in Biological Mass Spectrometry, University of Manchester, 2003 Postdoctoral Research, University of Southern Denmark (with Ole Jensen), 2005-2008 Postdoctoral Research, Utrecht University (with Albert Heck), 2008 Professor Mohammed's research centers on developing novel mass spectrometry approaches for large-scale characterization of protein post-translational modifications (PTMs). His group innovates in chromatographic techniques for single-cell proteomics, creates materials for PTM enrichment (glycosylation/phosphorylation), and applies these tools to study viral infections (SARS-CoV-2), cell cycle regulation, and signaling pathways. His work bridges chemistry, biochemistry, and cell biology to understand dynamic protein functions in health and disease. His recent publications (2023-2025) demonstrate strong emphasis on viral proteomics, particularly virus-host RNA-binding protein interactions, and innovations in mass spectrometry fragmentation techniques and chromatography. Key themes include viral remodeling of host cells, new labeling strategies for PTMs, and advancements in single-cell proteomics, with significant implications for understanding viral pathogenesis. Scientific Awards: No specific awards or fellowships were detailed in the source material. Advising and Grants: Information regarding graduate students supervised or specific research grants was not provided in the available text. As an active research group leader, Professor Mohammed likely mentors PhD students and secures competitive funding for proteomics research. Laboratories and Collaborations: Professor Mohammed leads a research group at Oxford focused on proteomics technology development. He collaborates extensively with the Ben Davis group on PTM detection materials and across the university on biochemical applications. At the Rosalind Franklin Institute, he heads the Mechanistic Proteomics programme to unravel protein functions through advanced proteomic methods.
Amir Asif is a Professor at the Lassonde School of Engineering, York University, and concurrently serves as Vice President, Research and Innovation. His academic leadership roles include Dean of the Gina Cody School of Engineering and Computer Science at Concordia University (2014-2020). He specializes in signal processing, communications, and their applications in healthcare, power grids, and distributed systems. Asif holds a PhD from Carnegie Mellon University and a Harvard certification in executive leadership. Education: PhD, Electrical and Computer Engineering, Carnegie Mellon University (1996) MS, Electrical and Computer Engineering, Carnegie Mellon University (1993) BSc, University of Engineering and Technology Lahore (1990) Harvard Certificate in Leadership for Senior Executives (2018) Research Interests: Asif’s work spans signal processing for medical imaging (e.g., ultrasound elastography), smart grid optimization, and cybersecurity in power systems. His recent publications address hydrogen energy systems, EMG-based gesture recognition, and resilient control frameworks against cyberattacks. Grants & Leadership: He leads NSERC-funded projects on federated learning and resilient algorithms. He chairs the Ontario Council of University Research and serves on TRIUMF Innovations and the Richmond Hill Board of Trade. His grants include SSHRC funding for equity initiatives and NSERC support for distributed signal processing. Teaching & Mentorship: Asif has supervised over a dozen graduate students and taught courses like Digital Communications and Statistical Signal Processing Theory. Notable advisees include Arash Mohammadi (PhD, 2014) and Nick Sajadi (PhD, 2017).
Andrew S. Whittaker is a SUNY Distinguished Professor in the Department of Civil, Structural and Environmental Engineering at the University at Buffalo, State University of New York . He serves as Director of the Institute of Bridge Engineering and Interim Director of the Stephen Still Institute for Sustainable Transportation and Logistics , both within the School of Engineering and Applied Sciences . A registered Civil and Structural Engineer in California, Whittaker specializes in structural and earthquake engineering, bridge engineering, blast and impact engineering, performance-based engineering, and nuclear structures. Research Interests: His work focuses on seismic isolation systems for nuclear reactors, fluid-structure interaction in advanced reactor vessels, gamma radiation effects on materials, and the dynamic behavior of graphite blocks in high-temperature gas reactors (HTGRs). He also explores the commodification of microreactors and soil-structure interaction for seismically isolated facilities. Scientific Awards: Distinguished Member, American Society of Civil Engineers (2025) Untermyer & Cisler Reactor Technology Medal (2023) Nathan M. Newmark Medal (2023) Fellow of multiple societies (ASCE, SEI, ACI) Awards and grants highlight his leadership in nuclear safety, seismic engineering, and reactor design.
Dr. Ian Bruce is a Professor in the Department of Electrical and Computer Engineering at McMaster University, Hamilton, ON, Canada. He has been with the department since 2002, conducting interdisciplinary research that bridges electrical engineering with auditory neuroscience. His work has significant implications for hearing technologies and auditory rehabilitation. Education: B.E. (electrical and electronic) from The University of Melbourne (1991) Ph.D. from the Department of Otolaryngology, The University of Melbourne Dr. Bruce's research program focuses on auditory modeling, hearing aids, cochlear implants, tinnitus, neural coding of speech, and digital speech processing. His work centers on understanding the physiological mechanisms of auditory processing and applying this knowledge to develop improved hearing technologies. He has pioneered computational models of the auditory periphery that accurately predict speech intelligibility for hearing-impaired listeners, directly informing hearing aid and cochlear implant design. Analysis of Dr. Bruce's recent publications (2019-2025) reveals a consistent focus on cochlear implants and auditory nerve modeling, with increasing integration of machine learning techniques. His work demonstrates a sophisticated balance between physiological accuracy and computational efficiency, with recent papers exploring WaveNet-based approximations of cochlear models and DNN-based auditory processing. A significant portion of his research examines the relationship between neural responses and perceptual outcomes in hearing-impaired individuals, particularly regarding temporal processing and speech understanding. Scientific Awards and Recognitions: Fellow of the Acoustical Society of America Member of the Association for Research in Otolaryngology Registered Professional Engineer in Ontario Associate Editor of the Journal of the Acoustical Society of America Dr. Bruce has mentored numerous graduate students through various capstone design projects across multiple engineering disciplines including biomedical, electrical, mechanical, and software engineering. His teaching portfolio includes specialized courses in biomedical signals and systems, cellular bioelectricity, models of the neuron, and advanced signal processing. He has consistently supervised M.Eng. projects and independent studies, demonstrating commitment to training the next generation of engineers in auditory technology development. Dr. Bruce's research is conducted within McMaster University's interdisciplinary biomedical engineering framework, collaborating with clinicians and researchers in otolaryngology and audiology. His laboratory work focuses on developing and validating computational models that simulate auditory nerve responses to both natural and prosthetic stimulation, with direct applications to improving cochlear implant performance and hearing aid algorithms for real-world listening environments.
Teresa Cheung is an Adjunct Professor in the Department of Engineering Science at Simon Fraser University’s Faculty of Applied Sciences. Her research focuses on neuroimaging techniques, particularly magnetoencephalography (MEG), and their applications to understanding brain networks in health and disease. She holds a Ph.D. in Physics from SFU (2012) and completed a postdoctoral fellowship at the University of Cambridge (2012–2013). Research interests include: MEG instrumentation and optically pumped magnetometers (OPM) Cortical-cerebellar networks and cerebellar activity localization Neuroimaging of neurological disorders like major depressive disorder and epilepsy Functional and structural connectome analysis across the human lifespan Multimodal integration of MEG, MRI, fMRI, and DTI data Recent work emphasizes the relationship between cardiovascular health, brain aging, and cognitive resilience. Her studies span clinical applications (e.g., depression biomarkers) and technical advancements in neuroimaging systems. Collaborations include multi-site studies on depression and aging cohorts like the Cam-CAN project. Publications highlight innovative methods in MEG system design, neural network dysfunction analysis, and lifespan brain dynamics. Her work bridges engineering, neuroscience, and clinical research to advance non-invasive brain imaging and neurophysiological understanding.
Rikky Muller is an Associate Professor of Electrical Engineering and Computer Sciences at UC Berkeley, holding the S. Shankar Sastry Professorship in Emerging Technologies. She is Co-director of the Berkeley Wireless Research Center (BWRC), a Core Member of the Center for Neural Engineering and Prostheses (CNEP), and an Investigator at the Chan-Zuckerberg Biohub. Her research focuses on implantable/wearable medical devices, low-power wireless systems, and neurotechnology for neurological applications. Education: PhD (2013), UC Berkeley; BS and M.Eng. (2004), MIT, all in EECS. Prior roles include IC designer at Analog Devices and co-founder of Cortera Neurotechnologies (acquired). Research interests include neural interfaces, closed-loop neuromodulation, and biomedical microelectronics. Notable contributions include Neural Dust (ultrasonic implants), wireless EEG systems, and seizure prediction hardware. Awards: MIT TR35 Innovator, NAE Gilbreth Lectureship, NSF CAREER Award, IEEE SSCS New Frontier Award Grants: Bakar Fellows, Hellman Fellowship, NSF CAREER Labs: Muller Lab (UC Berkeley EECS), Chan-Zuckerberg Biohub collaborations
Professor Denis Doorly is a Professor of Fluid Mechanics in the Department of Aeronautics at Imperial College London's Faculty of Engineering. His research focuses on biomedical fluid mechanics, particularly respiratory and cardiovascular systems, with expertise in computational fluid dynamics (CFD) and aerosol transport. He has published extensively on nasal airflow modeling, cardiovascular MRI simulations, and aerosol dynamics in medical contexts. Key contributions include CFD cohort studies on nasal decongestion effects, benchmarking models for SARS-CoV-2 transmission, and ventilator strategies during the pandemic. Research interests span biological fluid mechanics, biomedical flows, and medical device design. His work integrates computational modeling with clinical applications, addressing issues like tracheal compression, myocardial perfusion, and aerosol extraction during surgeries. Collaborations include studies on isolated heart models and particle deposition in respiratory systems. Affiliations include the Biological Fluid Mechanics and Biomedical Flows groups at Imperial. His publications (139+ articles) highlight interdisciplinary applications of fluid mechanics to healthcare challenges.
