Prof. Hedan Bai is an Assistant Professor at the Department of Materials, ETH Zürich, specializing in robotics materials, bio-inspired systems, and soft robotics. Their research focuses on developing advanced materials for sensing, energy-efficient systems, and biomedical applications. Notable projects include the SmartSuit architecture for space exploration and self-healing optical sensors for soft robots. Research interests span bioelectronics, stretchable sensors, haptic interfaces, and biomimetic materials. Bai's work integrates material science with robotics to create adaptive, sustainable, and intelligent systems. Key areas include wireless implants for neuromodulation, environmental-responsive textiles, and energy-harvesting devices. Publications highlight innovations in optical waveguides, self-healing materials, and wearable technologies. Their interdisciplinary approach bridges robotics, biomedical engineering, and aerospace applications. No formal awards are listed, but contributions to next-gen materials for robotics are prominent. Advising and grants are not detailed in the text, but Bai's lab focuses on projects like SmartSuit for extravehicular activities and synthetic afferent neural networks. Collaborations likely involve aerospace and biomedical sectors.
Swiss Federal Institute of Technology in LausanneSwitzerland
Pascal Frossard is a Full Professor at the Department of Electrical Engineering in the School of Engineering (STI) at EPFL, with a courtesy appointment in the School of Computer and Communication Sciences. He founded and directs the LTS4 laboratory since 2003, co-leads the EPFL AI Center and Swiss Data Science Center, and serves as Associate Dean for Research at STI. Research Focus: Machine Learning, Graph Signal Processing, AI Applications in Healthcare, Computer Vision Academic Leadership: IEEE Fellow, ELLIS Fellow, Conference Chair roles Key Projects: Digital Pathology for Oncology, Cardiac Digital Twins, Robust Machine Learning Research Interests: His work bridges signal processing, machine learning, and applied mathematics, emphasizing biomedical applications. Recent research includes adversarial robustness in classifiers, network representation learning, and 360-degree video analysis. Scientific Awards: IEEE Fellow ELLIS Fellow Leadership in IEEE technical committees Advising & Grants: Supervised 20+ PhD students and postdocs. Secured major grants from PHRT, Hasler Foundation, FNS-Sinergia, Armasuisse, Google, and Cisco.
Robert Rohling is a Professor at the University of British Columbia's Faculty of Applied Science, affiliated with the Department of Mechanical Engineering and holding a joint appointment with the Department of Electrical and Computer Engineering. As Director of the Institute of Computing, Information and Cognitive Systems (ICICS), his research focuses on biomedical engineering, medical imaging, robotics, and computational methods. B.A.Sc. (UBC) M.Eng. (McGill) Ph.D. (Cambridge) Rohling's work spans three primary research areas: medical imaging (3D ultrasound, spatial compounding, elasticity reconstruction), medical information systems (radiologist navigation tools for large image datasets), and robotic calibration for surgical applications. His multidisciplinary approach integrates mechanical and electrical engineering principles with clinical needs. Rohling's publications (2020-2022) reveal trends in advanced ultrasound techniques (e.g., shear wave vibro-elastography), AI-driven image processing (cycleGAN translation), and computational optimization for diagnostic accuracy. Keywords across his work include Medical Imaging, Biomedical Engineering, Robotics, and Computational Modeling. As director of the Robotics and Control Laboratory , Rohling leads interdisciplinary collaborations with industry and clinical partners to address practical challenges in medical diagnostics and surgical robotics. His research emphasizes translating engineering innovations into clinical practice.
Johnny Guzmán is a Professor of Applied Mathematics at Brown University, specializing in numerical analysis of partial differential equations and scientific computing. He holds a Ph.D. in Applied Mathematics from Cornell University (2005) and a B.S. in Mathematics from California State University, Long Beach (1999). His research focuses on numerical methods for PDEs, including discontinuous Galerkin methods, mixed finite element methods, and fluid-structure interaction problems. Key contributions include work on hybridizable and mixed finite element methods, discontinuous Galerkin discretizations, and stability analysis of numerical schemes. He has been funded by multiple NSF grants, including a Postdoctoral Fellowship (2005–2008) and awards totaling over $1M in research support. Notable recognitions include the Comfort and Urry Family Fund Prize (2013). Guzmán collaborates with institutions globally and serves on editorial boards for journals like Journal of Numerical Mathematics and Calcolo . His teaching spans computational linear algebra, numerical methods for differential equations, and finite element analysis.
Romain Lopez is an Assistant Professor of Computer Science and Biology at New York University, with a joint appointment in the Courant Institute of Mathematical Sciences and the Department of Biology. He will be joining NYU in September 2025, bringing expertise at the intersection of machine learning and computational biology. Prior to joining NYU, he was a Postdoctoral Fellow at Genentech and Stanford Medicine from 2021 to 2025, working with Jonathan Pritchard and Aviv Regev. Dr. Lopez received his educational training at prestigious institutions: PhD in Computer Science (2021) from the University of California, Berkeley, advised by Mike Jordan and Nir Yosef M.S. in Applied Mathematics (2016) from École polytechnique, Palaiseau, France Dr. Lopez's research focuses on developing machine learning methods to understand biological systems at the cellular level. His work bridges computational techniques with biological applications, particularly in single-cell and spatial omics analysis. He pioneered probabilistic approaches for single-cell analysis with scVI and co-developed scvi-tools, now widely adopted tools in the field. His research spans deep generative models, causal inference, perturbation modeling, and representation learning for biological data. His publication record demonstrates a consistent trajectory of innovation in computational biology, with recent work focusing on spatial biology, disentangled representations of cellular perturbations, and causal modeling of cellular responses. He has made significant contributions to the field of single-cell analysis, developing methods that help scientists interpret complex cellular data and predict how cells respond to various perturbations. Dr. Lopez has received numerous honors and awards for his research: Best Paper Award from the ICML Workshop on AI for Science (2024) Best Paper Award Honorable Mention from the AAAI Conference on Artificial Intelligence (2021) Best Student Poster Award from the ICML Workshop on Computational Biology (2019) UC Berkeley EECS Departmental Graduate Fellowship (2016) Carnot Foundation Fellowship (2016) Monahan Foundation Fellowship (2016) French National Defence Medal, Bronze Echelon (2014) At NYU, Dr. Lopez will lead the Biological Machine Learning group, which develops probabilistic machine learning methods to uncover biological mechanisms governing cellular behavior and disease. His lab focuses on creating tools that transform complex cellular data into biological insights, with applications in understanding cancer, immune responses, and fundamental cellular processes. His work has significant implications for precision medicine and drug discovery.
Shreyas Sen is the Elmore Associate Professor of Electrical and Computer Engineering at Purdue University, jointly affiliated with the School of Biomedical Engineering. He directs the Center for Internet of Bodies (C-IoB) and leads the SPARC Lab, focusing on circuits/systems for secure, energy-efficient body-centric communication and biomedical applications. Education: B.E. (Jadavpur University, 2006), M.S. & Ph.D. (Georgia Tech, 2009-2011). His research spans Human Body Communication (HBC), hardware security, IoT/IoB systems, and low-power sensing. Notable innovations include Electro-Quasistatic HBC (EQS-HBC) technology, which enables covert body-wire communication with 100x lower energy than conventional methods. Research Themes: Secure communication for medical wearables Physical layer security in IoT Ultra-low-power biosensors Side-channel attack mitigation in cryptographic ICs Publications: Over 200 papers in top venues (ISSCC, DAC, CICC, HOST) with focus on HBC systems, electromagnetic security, and biomedical circuits. Recent work explores EQS-HBC privacy properties (Nature Scientific Reports, 2019) and 350x current-domain signature attenuation for AES security (ISSCC 2020). Awards: NSF CAREER Award (2020) AFOSR Young Investigator (2016) MIT TR35 India (2018) 9 Best Paper Awards Intel Outstanding Researcher (2020) He advises over 20 students and leads industry collaborations through Ixana Inc. (founded 2020), commercializing EQS-HBC technology. Current efforts include EQS-based authentication systems and radiation dosimetry wearables.
Gary Fedder is the Howard M. Wilkoff Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU), with courtesy appointments in Biomedical Engineering, Mechanical Engineering, and Robotics. He serves as Faculty Director of the Manufacturing Futures Institute (MFI) and previously held roles such as Vice Provost for Research and Interim CEO of the Advanced Robotics for Manufacturing (ARM) Institute. Fedder’s research focuses on MEMS, advanced manufacturing, and implantable microsystems. He earned his B.S., M.S., and Ph.D. in EECS from MIT and UC Berkeley, respectively. Education: Ph.D., Electrical Engineering and Computer Science, UC Berkeley (1994) M.S., Electrical Engineering and Computer Science, MIT (1984) B.S., Electrical Engineering and Computer Science, MIT (1982) Research Interests: Microelectromechanical systems (MEMS), digital twins, aerosol jet printing, stretchable electronics, and manufacturing innovation. His work integrates MEMS with CMOS processes, emphasizing low-cost, high-performance systems. Key Contributions: Co-founded the ARM Institute; developed MEMS-based sensors and actuators; pioneered methods for manufacturing innovation through projects like America Makes. His research spans over 300 publications and 21 patents. Awards: IEEE Fellow (2007), Ross Tucker Award (1993), NSF CAREER Award (1996), and leadership roles in Manufacturing USA initiatives. Leadership & Outreach: Directed the Institute for Complex Engineered Systems and led national initiatives to advance U.S. manufacturing competitiveness. Active in editorial roles for journals like IoP Journal of Micromechanics .
SUNY College of Environmental Science and ForestryUnited States
Jun Hyung Lee is a Visiting Assistant Professor in the Department of Environmental Biology at SUNY College of Environmental Science and Forestry (ESF). His research focuses on advancing forest tree improvement and conservation through molecular and synthetic biology approaches, with a particular emphasis on enhancing plant resilience to environmental stresses via beneficial microbial interactions. He teaches courses in plant biotechnology and tissue culture methods. Education includes a Ph.D. in Forest Genetics from Purdue University (USA), and M.S. and B.S. degrees in Plant Science from Seoul National University (South Korea). His work integrates cutting-edge genetic engineering techniques with ecological studies to address challenges in plant stress tolerance, symbiosis, and epigenetic regulation. Recent projects include identifying novel symbiosis pathways for thermotolerance and analyzing flooding tolerance in hybrid poplars. Publications highlight contributions to plant-microbe interaction research, synthetic biology applications, and genome editing epigenetic impacts. Collaborations span institutions like Oak Ridge National Laboratory and the University of Georgia, reflecting his transdisciplinary approach to plant science. Lee’s teaching emphasizes practical skills in biotechnology, bridging laboratory innovation with field applications.
Hang Lu is a Professor and holds the Cecil J. "Pete" Silas Chair of Chemical & Biomolecular Engineering at the Georgia Institute of Technology. Dr. Lu also holds a Love Family Professorship and leads the Lµ Fluidics Group, which focuses on engineering microfluidic systems and machine learning tools to address complex questions in neuroscience, developmental biology, and cell biology that are difficult to address with conventional techniques. Dr. Lu's research lies at the intersection of engineering and biology, with primary interests including: Microfluidic systems for high-throughput screens and image-based genetics and genomics Systems biology: large-scale experimentation and data mining Microtechnologies for optical stimulation and optical recording Big data, machine vision, and automation Developmental neurobiology, behavioral neurobiology, and systems neuroscience Cancer biology, immunology, embryonic development, and stem cells Her laboratory engineers microfluidic devices and BioMEMS to study neuroscience, genetics, cancer biology, and biotechnology. These miniaturized Lab-on-a-chip tools operate at scales comparable to biological systems, leveraging unique micro and nano-scale phenomena to gather large-scale quantitative data about complex biological systems. Current projects include Microfluidics for Life Sciences, Optical Neuron Recordings and Manipulations, Machine Learning Tools for Neuroscience, Measuring and Modeling Behavior, and High-throughput, High-content Cell-based Assays. Analysis of Dr. Lu's recent publications (2024-2025) reveals a strong trend toward integrating microfluidics with advanced computational methods: Development of deep learning frameworks for biological image analysis Advanced neuron tracking and functional imaging techniques Non-invasive characterization of 3D organoid cultures Sophisticated neuromechanical modeling of locomotion Microfluidic temperature control systems for in vivo studies Label-free imaging pipelines for neural development Dr. Lu's significant professional honors include: Cecil J. "Pete" Silas Chair of Chemical & Biomolecular Engineering Love Family Professorship The Lµ Fluidics Group actively mentors students and postdocs, currently accepting new postdoctoral researchers. The lab receives substantial funding for interdisciplinary projects at the engineering-biology interface, with research implications spanning fundamental biological understanding to therapeutic development. The group operates within Georgia Tech's School of Chemical & Biomolecular Engineering, with specialized facilities for microfluidic device fabrication, biological experimentation, and advanced imaging, maintaining strong collaborative ties across engineering, neuroscience, and biological disciplines.
Prof. Marcy Zenobi-Wong is a Full Professor at ETH Zurich's Department of Health Sciences and Technology, specializing in biofabrication and tissue engineering. Her research focuses on cartilage regeneration using advanced biomaterials, including nanofilm coatings and 3D printing techniques. She holds patents in tissue engineering and has pioneered methods like filamented light (FLight) biofabrication for creating anisotropic tissues. Her academic journey includes a B.Sc. from MIT (1985), M.Sc. and Ph.D. from Stanford (1987, 1990), followed by postdoctoral work at the University of Michigan. She leads the Biofabrication Group at ETH, developing therapies for joint repair and regenerative medicine. Courses taught include Biomedical Engineering and Materials and Mechanics in Medicine . Research highlights include engineered hydrogels for cartilage protection, CRISPR-driven gene editing in chondrocytes, and biohybrid neural interfaces. Her work bridges material science, cell biology, and clinical applications, with a focus on translational medicine. Collaborative projects involve creating elastic cartilage grafts for microtia reconstruction and volumetric printing of complex tissue constructs.
University of California , Santa Barbara (UCSB)United States
Megan Valentine is a Professor of Mechanical Engineering at the University of California, Santa Barbara (UCSB), affiliated with the College of Engineering. She leads an interdisciplinary research group focused on biological and bioinspired materials, investigating how forces are generated and transmitted in living systems to design responsive synthetic materials. Her work bridges engineering, physics, chemistry, and biology. Education: PhD in Physics from Harvard University, MS in Physics from the University of Pennsylvania, and BS in Physics from Lehigh University. Affiliations include the California NanoSystems Institute (CNSI), Materials Research Laboratory (MRL), Neuroscience Research Institute, and the Center for Stem Cell Biology and Engineering. Research interests span soft material mechanics, bioengineering, and systems biology, with applications in marine-inspired materials, mechanobiology, and soft robotics. Her lab employs advanced experimental techniques to study biophysical and biochemical mechanisms in living systems and translate them into engineered materials capable of self-healing, movement, and environmental responsiveness. Notable awards include the NSF Early CAREER Award, Fulbright Scholarship, and election as Fellow of the American Physical Society and American Institute for Medical and Biological Engineering. Her contributions emphasize creativity, collaboration, and diversity, with a focus on addressing societal challenges through interdisciplinary innovation.
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.
Dr. Yamin Zhang (张亚敏) holds a Presidential Young Professorship as an Assistant Professor in the Department of Chemical & Biomolecular Engineering at the National University of Singapore (NUS), College of Engineering. She leads the Zhang Group which focuses on interdisciplinary research at the intersection of electrochemistry, materials science, and biomedical engineering. 07/2023 – 01/2024: Research Associate, Northwestern University 02/2021 – 06/2023: Postdoctoral Fellow, Northwestern University 08/2016 – 12/2020: Ph.D., Chemical Engineering, Georgia Institute of Technology 09/2012 – 07/2016: B.S., Chemical Engineering, Tianjin University; B.S., Finance (Double Major), Nankai University Dr. Zhang's research centers on developing advanced electrochemical strategies for next-generation medical devices (implantable, bioresorbable, and wearable) and sustainable energy solutions. Her work bridges bioelectronics , battery technology , and medical therapeutics , with particular emphasis on creating devices that can safely dissolve in the body after serving their purpose. Key areas include bioresorbable optoelectronic systems for electrotherapy, self-powered drug delivery platforms, and eco-safe battery technologies that can harmlessly resorb in biological environments. Analysis of Dr. Zhang's publication record reveals a clear trajectory from fundamental battery chemistry (2021-2022) toward increasingly sophisticated medical applications (2023-2025). Her recent work demonstrates mastery in integrating multiple functionalities into single bioresorbable platforms, as evidenced by her Nature (2025) paper on millimeter-scale optoelectronic systems for electrotherapy and Cell Biomaterials (2025) paper on wireless bioelectronic devices. The research shows strong interdisciplinary collaboration with leading institutions including Northwestern University and Georgia Tech. AHA Early Faculty Independence Award (2023) MIT ChemE Rising Stars (2022) Sigma Xi Best PhD Thesis Award (2021) Chinese Government Award for Outstanding Students Abroad (2021) A*STAR MTC Young Individual Research Grants (YIRG) (2025) Early Career Board Member for ACS Applied Materials & Interfaces (2025) Dr. Zhang has secured significant research funding including the AHA's Second Century Early Faculty Independence Award as Principal Investigator (2023) and the A*STAR MTC Young Individual Research Grant (2025). Her group serves on advisory boards for Cell Biomaterials and ACS Applied Materials & Interfaces. The Zhang Group at NUS maintains active collaborations with Northwestern University researchers including the Rogers group, with whom she has co-authored multiple high-impact publications in Nature, Science, and PNAS. Current research focuses on advancing battery technology and developing sophisticated electrochemical strategies for medical devices with an overarching focus on healthcare innovation and environmental sustainability.
Dr. Saree Alnaghy is an Honorary Associate Professor at the University of Wollongong's Faculty of Engineering and Information Sciences, affiliated with the Centre for Medical Radiation Physics. She holds a Bachelor of Medical and Radiation Physics (Honours) and a PhD in Physics from the University of Wollongong (2009–2017). Her research focuses on advanced medical imaging and radiation therapy technologies, including photon counting detectors, dosimetry systems, and robotic motion phantoms for quality assurance. Key research areas include: Development of novel X-ray detectors for radiotherapy guidance High-resolution dosimetry techniques using silicon and polymer-based systems Integration of real-time imaging in radiation therapy Robotic systems for motion management in oncology Her work has been supported by grants such as 'Sharper Targeting, Brighter Future' (2024) and 'Bringing Colour to Radiotherapy' (2021–2025). She currently supervises PhD and MRes students on projects involving photon counting CT scanners and radiotherapy imaging. Alnaghy also serves as a Radiation Oncology Medical Physics Registrar at the Nelune Comprehensive Cancer Centre.
Adrien Desjardins is a Professor at the University of British Columbia, jointly appointed in the Department of Mechanical Engineering and Department of Electrical and Computer Engineering within the Faculty of Applied Science. He joined UBC in 2024 after serving as a Full Professor at University College London from 2019-2024, following 13 years on faculty there. His educational background includes a B.Sc. from UBC (2001) and a Ph.D. from MIT and Harvard University (2007). Dr. Desjardins' research program focuses on interdisciplinary development of imaging and sensing modalities and autonomous robotics with marine and biomedical applications. His work integrates photonics, ultrasound, machine learning, and robotics to create innovative diagnostic tools and sensing systems, particularly in optical coherence tomography, diffuse optical spectroscopy, and photoacoustic imaging. His publication record reveals an evolution from foundational neuroimaging work (2001) toward increasingly sophisticated optical systems culminating in breakthroughs like ultrasensitive optical microresonators for ultrasound sensing (2017), demonstrating consistent innovation in biomedical optics with growing emphasis on machine learning integration and real-world applications. His scientific contributions have been recognized through prestigious awards: Research Chair from the Royal Academy of Engineering Healthcare Technologies Challenge Award from EPSRC Starting grants from ERC, EPSRC, and Royal Society World Economic Forum Young Scientist (2015) UCL Provost Teaching Prize (2013) Dr. Desjardins actively mentors graduate students and secures major research funding through competitive grants, with current openings for January/September 2025 intakes. His program involves close industry collaboration indicating strong translational focus, though specific lab names aren't mentioned. The interdisciplinary nature of his work suggests teams spanning engineering, computer science, and medical disciplines working on next-generation imaging systems for healthcare and marine exploration.
