Find Academic Supervisors

• AI in Healthcare
• Electronic Health Records Analysis
• Biomedical Time Series Analysis
• +6 more

Dr. Kezhi (Ken) Li is an Associate Professor of AI in Healthcare at the Institute of Health Informatics, University College London (UCL). He leads the AI for Health research group and has established himself as a leading expert in applying artificial intelligence to solve complex problems in healthcare, with over 130 publications in leading journals (total impact factor greater than 400). Dr. Li earned his Doctor of Philosophy from Imperial College of Science, Technology and Medicine in 2013, followed by research positions at the Medical Research Council (2015-2017), University of Cambridge (2014-2015), and Royal Institute of Technology (KTH) (2013-2014). His academic journey reflects a consistent trajectory from technical AI research toward increasingly healthcare-focused applications. Dr. Li's research focuses on solving physiological, medical, clinical, and operational problems in healthcare using AI techniques. His specific expertise includes AI in healthcare using electronic health records (EHR), biomedical time series analysis using monitors/wearables, diabetes management, large language models (LLM) in healthcare (especially mental health), patient flow optimization, and digital health with federated learning. His work bridges the gap between cutting-edge AI methodologies and practical healthcare applications, with a strong focus on improving patient outcomes and healthcare system efficiency. Analysis of Dr. Li's publication history reveals a strong emphasis on diabetes management technologies, particularly blood glucose prediction systems using advanced neural network architectures. More recently, his work has expanded into mental health applications of large language models, blockchain-based federated learning for healthcare data, and mortality prediction in critical care settings. His research demonstrates a clear evolution from purely technical AI development toward increasingly clinically impactful applications, with growing emphasis on explainability, privacy preservation, and real-world implementation challenges. Dr. Li has received numerous prestigious awards recognizing his contributions to healthcare AI: Best Application Award of IEEE Global Blockchain Conference (2025) Fellow of British Computer Society (2025) Fellow of the Royal Society for Public Health (2024) Healthcare Partnership of the Year category at the London Higher Awards (2024) ECR Promising Project Award (2023) Gallivan Award finalists (2022) Stylianos Kalaitzis PhD Award Winner (2022) HDR UK Team of the Year (COVID-19) Award (2021) As an educator, Dr. Li serves as the Director of MRes study (AI-enabled Healthcare Systems) at UCL. He leads multiple key modules including Healthcare Artificial Intelligence Journal Club, Dissertation in Artificial Intelligence Enabled Healthcare, and Advanced Machine Learning for Healthcare. His supervision extends across dissertation projects and junior researchers in his AI for Health group. His research has been supported by various grants, including those from HDR UK, focusing on translating AI innovations into practical healthcare solutions. Dr. Li leads the AI for Health research group (https://ai4hucl.github.io/ai4h_webs/), which comprises researchers with diverse expertise in machine learning, healthcare systems, and clinical domains. The group maintains strong collaborations with healthcare providers and industry partners to ensure their research addresses real-world healthcare challenges and can be effectively translated into clinical practice.

Riccardo RaheliView profile

Professor

• Telecommunications
• Digital Signal Processing
• Wireless Communications
• +5 more

Riccardo Raheli is a Full Professor at the University of Parma , Department of Engineering and Architecture, with a career spanning over three decades in Information and Communication Technologies (ICT). He has served as Chair of the Councils for Telecommunications and Communication Engineering programs, and as representative of the University of Parma in CNIT and its Members' Assembly. Education: Laurea in Electronic Engineering (University of Pisa, 1983), M.Sc. in Electrical and Computer Engineering (University of Massachusetts, 1986), Postgraduate Diploma (Scuola Superiore Sant'Anna, 1987) Key Roles: President of Degree Councils (2002-2018), CNIT Committee Member (2000-2005), Editorial Board member for IEEE Transactions, Springer and MDPI journals His research bridges telecommunications , digital signal processing , and healthcare applications , producing extensive international publications and industrial patents. He has co-authored monographs including Detection Algorithms for Wireless Communications (Wiley, 2004) and LDPC Coded Modulations (Springer, 2009). Recent article trends show interdisciplinary work in automotive stress monitoring (IoT/Matlab-based systems), video processing for healthcare (neonatal seizures, respiratory monitoring), and acoustic field control (microphone virtualization, personal sound zones). His work spans machine learning applications in automotive systems, stochastic acoustic modeling , and power-line communications . Scientific Leadership : Co-Chair for IEEE conferences (ICC 2010, GLOBECOM 2011, ISPLC 2020) Editorial roles in 7+ international journals Grants & Collaborations : Led industrial patents in communications systems Coordinated CNIT Technical Reports series (2025) He teaches Wireless Communications and Digital Signals Laboratory , emphasizing Matlab/Simulink proficiency. His laboratory sessions focus on practical implementation of signal processing algorithms, requiring full software installation on personal devices.

Wolfgang NejdlView profile

Professor

• Web Science
• Information Retrieval
• Artificial Intelligence
• +4 more

Prof. Dr. Wolfgang Nejdl is a Professor at the Institute for Data Science within the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover. He serves as Executive Director of the L3S Research Centre and Leibniz Forschungszentrum Inclusive Citizenship. Web Science Information Retrieval Artificial Intelligence Deep Learning His recent research focuses on AI applications in medicine , multimodal data fusion , and ethical AI systems . Projects include CAIMed (AI in Causal Medicine) and DAISEC (AI & Cybersecurity). His publications span conferences like AAMAS, WWW, and SIGIR. Notable awards include membership in the National Academy of Science and Engineering (acatech) . Former students hold positions at institutions like Stanford, TU Dresden, and ETH Zürich. Current projects involve climate resilience AI , federated learning for healthcare , and quantum-inspired data science .

David AckerleyView profile

Professor

• Enzymes
• Synthetic biology
• Microbiology
• +4 more

Professor David Ackerley (Victoria University of Wellington) is a leading microbiologist and enzyme engineer specializing in directed evolution of bacterial enzymes for biotechnological applications. As Biotechnology Programme Director since 2006, he lectures in foundational courses like BTEC101 and BTEC201. Academic rank: Professor of Biotechnology Institutional affiliation: Victoria University of Wellington Research focus areas: Microbial Biotechnology, Drug Discovery, Synthetic Biology His research employs Darwinian evolutionary principles to engineer enzymes with enhanced activities, particularly targeting non-ribosomal peptide synthetases and nitroreductases for antibiotic development and cancer therapy. Recent work explores metagenomic domain substitution in pyoverdine biosynthesis and Purpuramine R from marine sponges. Key publications demonstrate innovations in metagenomic library construction , CRISPR screening for regeneration genes, and structural characterization of engineered enzymes. His team has developed NTR 2.0 , a high-efficacy nitroreductase for targeted cell ablation. Current research projects include: Clean solutions from dirty genes: Plastic-degrading enzyme discovery Engineering enzymes for CAR T-cell-chemotherapy synergy Repurposing niclosamide against Gram-negative superbugs Grants from the Health Research Council of New Zealand, Royal Society of New Zealand, and Cancer Society of NZ support his work. Collaborations span biomedical research, synthetic biology, and environmental applications.

• 3D Biofabrication
• Bioprinting
• Biosensors
• +7 more

Professor Will Wenmiao Shu is the Hay Chair in Biomedical Engineering and Director of Research at the Department of Biomedical Engineering, University of Strathclyde. He has held positions at prestigious institutions including University of Cambridge (PhD), Heriot-Watt University (Lecturer/Reader), and Stanford University (Visiting Position). His work focuses on 3D biofabrication , bioprinting , and regenerative medicine . PhD in Electrical Engineering & Nanoscience, University of Cambridge His research pioneered the first bioprinting of human embryonic stem cells and induced pluripotent stem cells, enabling animal-free drug testing and 3D printed organs . Current projects include 3D Bioprinting of Vascularised Hepatic Cancer Models and BIOME: Bioplastic Injection-moulding Optimisation . Recent publications address nanometrology and soft tissue resection simulations , reflecting his interdisciplinary approach. Awards include dual Best Presentation Prizes in 2024 for work on microvascular networks and animal-free research. Editorial Board Member, IOP Biofabrication Journal Board Director, International Society for Biofabrication (ISBF) Founding Member (emeritus), Royal Society of Edinburgh’s Young Academy

• X-ray Physics
• Synchrotron Radiation
• Medical Imaging
• +5 more

Benedikt Günther is a research scientist at the Technical University of Munich (TUM) working within the Chair of Biomedical Physics led by Prof. Dr. Franz Pfeiffer. His research focuses on the Munich Compact Light Source (MuCLS), a laboratory-scale inverse Compton X-ray source that provides synchrotron-like radiation for biomedical applications. Günther plays a key role in developing, optimizing, and characterizing this innovative technology, contributing to both its fundamental physics and practical medical applications. His primary research interests center around X-ray physics and imaging techniques, particularly laser enhancement cavities for inverse Compton X-ray sources, X-ray microscopy, dynamic phase-contrast imaging, and X-ray spectroscopy. Günther's work bridges fundamental physics with practical medical applications, developing instrumentation that brings synchrotron-quality imaging to conventional laboratory settings. His research has significant implications for improving medical diagnostics while making advanced imaging techniques more accessible. Analysis of Günther's publication record reveals a consistent focus on advancing compact X-ray source technology and its applications. His work demonstrates expertise in both theoretical modeling and experimental implementation, with publications spanning instrument development, imaging techniques, and specific medical applications. The research shows progression from fundamental source characterization to increasingly sophisticated biomedical applications, particularly in breast imaging, dental diagnostics, and materials science. 2019 Best Poster Award at the combined meeting of the 68th Denver X-ray Conference (DXC) & 25th International Congress on X-ray Optics and Microanalysis (ICXOM) for 'Full-Field Structured Illumination Super-Resolution X-ray Transmission Microscopy' Günther regularly presents his work at major international conferences including the International Particle Accelerator Conference, High-Brightness Sources and Light-driven Interactions Congress, and specialized X-ray imaging meetings. His research is conducted within the Munich Compact Light Source facility, a collaborative project involving physicists, engineers, and medical researchers working to develop laboratory-scale synchrotron technology for widespread biomedical use.

Nezihe Merve GürelView profile

Assistant Professor

• Machine Learning
• Computer Science
• Pattern Recognition
• +4 more

Nezihe Merve Gürel is an Assistant Professor in Computer Science at Delft University of Technology (TU Delft), affiliated with the Pattern Recognition & Bioinformatics Group within the Intelligent Systems Department of the Faculty of Electrical Engineering, Mathematics and Computer Science. Her research focuses on developing robust, reliable, and efficient machine learning methods with enhanced reasoning capabilities, bridging theoretical rigor and practical applications. She emphasizes data-centric approaches to improve ML systems. Education: PhD in Computer Science from ETH Zurich, MSc from EPFL (Switzerland). Research Interests: ML robustness, reliability, reasoning, data-centric ML, federated learning, and explainable AI. Her recent work includes certified robustness for retrieval-augmented models and time-efficient learning algorithms. She has contributed to the Journal of Data-centric Machine Learning Research as an executive editor and served as a reviewer for top ML conferences (NeurIPS, ICML, ICLR). She previously held roles at IBM Research, Stanford University's Human-Centered AI Lab, and Westlake Institute for Advanced Study. Her awards include the Generation Google Scholarship and Cisco Research Funding . Scientific Awards : Generation Google Scholarship (2021) Cisco Research Center University Funding Labs & Teams : She leads research in the Pattern Recognition Laboratory at TU Delft and collaborates with international institutions like Stanford and Westlake Institute for Advanced Study.

Pia VogelView profile

Professor

• ATP Synthase
• Multidrug Resistance
• Ryanodine Receptor
• +5 more

Pia Vogel is a Professor in the Department of Biological Sciences at Southern Methodist University (SMU), where she leads research on nucleotide-binding proteins using Electron Spin Resonance spectroscopy and molecular modeling. Her work focuses on elucidating structural mechanisms in ATP synthase, multidrug resistance transporters, and calcium channels with biomedical applications in cancer therapy and neurodegenerative diseases. Education: Ph.D., University of Kaiserlautern Dr. Vogel's research program investigates three interconnected domains: the rotary mechanics of FoF1-ATP synthase (particularly the external stalk subunit b-dimer), the structural basis of multidrug resistance in P-glycoprotein and MRPs, and ATP-regulated calcium release via ryanodine receptors. Her laboratory employs site-specific spin labeling, ESR spectroscopy, and computational modeling to resolve protein dynamics and interactions at molecular resolution, contributing to understanding energy transduction in ATP synthase and mechanisms of drug resistance. Analysis of her 15 most recent publications (2020-2025) reveals a dominant focus on developing and characterizing P-glycoprotein and BCRP inhibitors to overcome chemotherapy resistance in cancer. These studies integrate computational screening, ATPase assays, and cell-based models to evaluate inhibitor efficacy, with emerging applications in Alzheimer's research through amyloid-β transport studies. The work demonstrates consistent methodological synergy between biophysical characterization and therapeutic development. Dr. Vogel maintains an active research group supported by sustained funding, evidenced by continuous publication output and laboratory infrastructure. Her team employs multidisciplinary approaches spanning biophysics, biochemistry, and computational biology to address fundamental questions in membrane protein function. Her laboratory facilities in DLSB 221 include specialized Electron Spin Resonance instrumentation and dual Linux computing clusters for molecular dynamics simulations. The research environment supports collaborative projects extending her work into cancer therapeutics and neurodegenerative disease mechanisms through partnerships with clinical and computational researchers.

Muhannad S. BakirView profile

Professor

• Heterogeneous Integration
• Electrical and Photonic Interconnects
• Thermal Modeling for Electronics
• +3 more

Muhannad S. Bakir is the Dan Fielder Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology, and Director of the 3D Systems Packaging Research Center . His research focuses on heterogeneous integration , electrical/photonic interconnects , thermal modeling , and electronics for healthcare , with over 180 publications and 12 U.S. patents. Research areas include: Advanced cooling and power delivery for emerging systems Biosensor-CMOS integration 2.5D/3D IC packaging Polylithic integration technology Nanofabrication for microsystems Scientific accolades include: 2018 IEEE EPS Exceptional Technical Achievement Award 2013 Intel Early Career Faculty Honor Award 2012 DARPA Young Faculty Award 2011 IEEE CPMT Outstanding Young Engineer Award Best paper awards at IEEE ECTC, IITC, and CICC 2020 Georgia Tech Doctoral Thesis Advisor Award His lab explores integrated 3D systems with emphasis on co-design of thermal, power, and electrical networks for machine learning and healthcare applications.

Omer T InanView profile

Assistant Professor

• Biomedical Engineering
• Medical Devices
• Physiological Monitoring
• +7 more

Omer T Inan is the Regents Entrepreneur Endowed Chair and Assistant Professor at the School of Electrical and Computer Engineering (ECE) at Georgia Institute of Technology. His work bridges biomedical engineering and wearable technology, focusing on non-invasive physiological monitoring for chronic disease management. He holds a Ph.D. in Electrical Engineering from Stanford University (2009) and previously worked at Countryman Associates (2007-2013) as Chief Engineer, developing professional audio systems. Education: B.S., M.S., Ph.D. in Electrical Engineering, Stanford University (2004-2009) His research interests include medical devices for home-based cardiovascular monitoring, musculoskeletal sound analysis, and neuromodulation of stress responses. He has pioneered technologies for heart failure patients, PTSD treatment, and osteoarthritis diagnostics. Recent publications highlight innovations in AI-driven cardiac parameter estimation, motion artifact removal in seismocardiograms, and multimodal stress tracking via wearables. His work spans biomedical signal processing, clinical translation, and portable diagnostic systems. Scientific Awards 2024 IEEE Fellow 2023 IEEE Distinguished Lecturer 2023 American College of Cardiology Fellow 2022 American Institute for Medical and Biological Engineering Fellow 2021 Academy Award for Technical Achievement (The Oscars) 2018 ONR Young Investigator Award 2018 NSF CAREER Award At Georgia Tech, Inan leads the Inan Research Lab, which develops technologies for physiological monitoring and modulation. Projects include musculoskeletal sound analysis for joint health, non-invasive cardiovascular sensing, and neuromodulation to treat PTSD via vagal nerve stimulation.

• Neuromorphic Computing
• Memristor-Based Architectures
• Energy-Efficient AI Hardware
• +7 more

Said Hamdioui serves as a full Professor in the Department of Computer Engineering within the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. His research focuses on cutting-edge hardware architectures for neuromorphic computing and energy-efficient AI acceleration, with particular emphasis on memristor-based systems, emerging memory technologies, and fault-tolerant designs for edge applications. His research interests span Neuromorphic Computing , Memristor-Based Architectures , and Energy-Efficient AI Hardware , addressing critical challenges in hardware security, computation-in-memory, and reliable edge AI deployment. Recent work demonstrates significant advancements in RRAM/FeFET testing methodologies, spiking neural network implementations, and spin wave computing alternatives to traditional CMOS. His publications reveal strong trends toward real-world deployment of brain-inspired hardware with practical constraints like power efficiency, testability, and security. Award highlights include: DATE'20 Best Paper Award DFT'21 Outstanding Student Paper ETS 2021 Best Paper Award LATS 2018 & 2022 Best Paper Awards Professor Hamdioui actively contributes to the research community through editorial roles at IEEE Transactions on VLSI Systems , IEEE Design & Test , and Journal of Electronic Testing from 2017-2018. His leadership in multi-partner projects like CONVOLVE and NEUROKIT2E demonstrates strong industry-academia collaboration for edge AI solutions. Current work shows increasing focus on practical deployment challenges including in-field fault monitoring, security vulnerabilities in neuromorphic systems, and realistic brain simulation frameworks.

Arti K. RaiView profile

Professor

• Intellectual Property Law
• Patent Law
• Biotechnology
• +6 more

Arti K. Rai is the Elvin R. Latty Professor of Law and Co-Director of the Center for Innovation Policy at Duke Law School. She is an internationally recognized expert in Intellectual Property Law , Biotechnology , Administrative Law , and Health Law , with research funded by NIH, NSF, Arnold Ventures, and other institutions. Her work spans peer-reviewed journals like Science , New England Journal of Medicine , and Nature Biotechnology . Recent articles focus on AI challenges in patent law , biologics manufacturing patents , orphan drug policies , and data privacy in medical information commons . She has served in federal advisory roles, including the Department of Commerce and the National Academies’ Forum on Drug Discovery . Key themes in her research include trustworthiness in data-sharing systems , participant-centric governance , and legal frameworks for biomedical innovation . Her policy work addresses drug pricing , patent reform , and government licensing authority .

Todd D. MurpheyView profile

Professor

• Computational Dynamics and Control
• Human-Swarm Interaction
• Algorithmic Matter
• +10 more

Dr. Todd D. Murphey is a Professor of Mechanical Engineering at Northwestern University's Robert R. McCormick School of Engineering and Applied Science. He serves as Director of Transformative Research and Director of the Master of Science in Robotics Program at Northwestern, leading initiatives in computational dynamics, control systems, and robotics. His work bridges engineering, neuroscience, and biomedical applications, with a focus on developing systems that interact effectively with humans and their environments. Dr. Murphey received his Ph.D. in Control and Dynamical Systems from the California Institute of Technology in 2002, with a thesis titled "Control of Multiple Model Systems." Prior to that, he earned a B.S. in Mathematics, summa cum laude, from the University of Arizona in 1997. Dr. Murphey's research centers on computational methods in dynamics and control, with applications spanning neuroscience, health science, robotics, and automation. His work in the Interactive & Emergent Autonomy Lab focuses on computational models of embedded control, biomechanical simulation, dynamic exploration, and hybrid control. The group develops mathematical approaches that lead to orders of magnitude improvement in computational efficiency for real-time implementation. Key application areas include assistive exoskeleton control, stabilization of energy networks, bio-inspired active sensing, entertainment robots, robotic exploration, and software-enabled stroke rehabilitation. Analysis of Dr. Murphey's recent publications reveals a strong emphasis on human-swarm interaction, algorithmic matter, and control of cyber-physical systems in uncertain environments. His work increasingly integrates information theory with physical systems, exploring how both autonomous and biological systems interact with environments to learn and improve behaviors. Recent trends show growing applications in rehabilitation technology, with particular focus on human-machine interaction in biomedical devices and embodied intelligence. Dr. Murphey has received numerous honors and awards for his contributions to robotics and engineering: Named Director of Transformative Research at Northwestern University (2025) Appointed IEEE Robotics and Automation Society Vice President of Publication Activities (2022) Co-recipient of Best Paper Award for IEEE Transactions on Robotics (2020) Appointed to Air Force Scientific Advisory Board (2019) Recipient of ABB Best Student Paper Award for CPL-SLAM research (2019) Cole-Higgins Award from Northwestern Engineering (2015) Dr. Murphey has supervised numerous graduate students including Taosha Fan, Giorgos Mamakoukas, and Ian Abraham, with research spanning robotic exploration using electrosense and mechanical contact, human-in-the-loop control, and shared control for rehabilitation devices. His lab has secured significant funding from the National Science Foundation, DARPA, and industry partners including Siemens and Ekso Bionics, supporting research in algorithmic matter, emergent behavior, and human-swarm collaboration. The Interactive & Emergent Autonomy Lab, led by Dr. Murphey, investigates how both autonomous systems and biological systems interact with their environments to learn and improve behaviors. Current projects include active learning and data-driven control, active perception in human-swarm collaboration, algorithmic matter and emergent computation, control for nonlinear and hybrid systems, cyber physical systems in uncertain environments, harmonious navigation in human crowds, information maximizing clinical diagnostics, reactive learning in underwater exploration, robot-assisted rehabilitation, and software-enabled biomedical devices. The lab collaborates with researchers across Northwestern and institutions including Georgia Tech, MIT, and industry partners.

Alexandra Piotrowski-DaspitView profile

Assistant Professor

• Gene Therapy
• Biomaterials
• Nanoparticle Delivery
• +3 more

Dr. Alexandra Piotrowski-Daspit is an Assistant Professor in the Biomedical Engineering department and Internal Medicine – Pulmonary and Critical Care Medicine at the University of Michigan Medical School. She is a chemical/biological engineer with expertise in polymeric biomaterials for gene therapies, focusing on in vivo behavior of delivery vehicles and strategies to optimize biodistribution. Education: Ph.D. in Chemical/Biological Engineering Her research bridges polymer chemistry, gene delivery, and translational medicine, emphasizing in utero interventions and pulmonary targeting. Key areas include nanoparticle surface engineering, macrophage decoys, and computational pharmacokinetic modeling. Recent publications highlight systemic in utero gene editing for cystic fibrosis, poly(amine-co-ester) nanoparticle tunability, and mucosal vaccination platforms. She also explores miRNA therapies for congenital diaphragmatic hernia and triplex-forming PNAs for CFTR correction. PhRMA Foundation Awardee (2024) Her work involves interdisciplinary collaborations, DEI initiatives, and translational projects from postdoc foundations in W. Mark Saltzman’s lab. Labs like Saltzman and SCGE teams support her research.

Daniel SageView profile

Lecturer

• Biomedical Imaging
• Image Processing
• Deep Learning Applications
• +5 more

Daniel Sage is a Lecturer and Scientific Advisor at École polytechnique fédérale de Lausanne (EPFL) , affiliated with the Biomedical Imaging Laboratory (LIB) under the College of Engineering (STI) and School of Life Sciences (SV) . He specializes in bioimage informatics , structured-illumination microscopy , and deep learning applications for biomedical imaging. His work spans algorithm development for single-molecule localization microscopy (SMLM) , fluorescence imaging , and 3D reconstruction . His research group has developed open-source tools like FlexSIM for light inhomogeneity correction, DeepImageJ for integrating deep learning in ImageJ, and Steer'n'Detect for orientation-accurate template detection. His publications focus on correcting multiple-blinking artifacts in PALM, optimal transport metrics for SMLM evaluation, and contextual feature analysis for xenograft cell classification. He mentors PhD students and contributes to interdisciplinary education through courses such as Bioimage Informatics and Fundamentals of Image Analysis , emphasizing practical software solutions and Java programming for bioimage processing. His collaborations include institutions like Howard Hughes Medical Institute and Centre National de la Recherche Scientifique (CNRS) .