جستجوی استاد راهنمای دانشگاهی

Hutan Ashrafianمشاهده پروفایل

استاد

• Artificial Intelligence in Medicine
• Metabolic Surgery
• Health Policy
• +۴ مورد دیگر

Professor Hutan Ashrafian is a clinician-scientist and surgeon at the University of Leeds Business School, holding dual roles as Professor of Research Impact and Senior Research Fellow at Imperial College London. His expertise spans AI in healthcare, metabolic surgery, and ancient history. He pioneered STARD-AI and QUADAS-AI guidelines for AI diagnostics, collaborated on AI-driven breast cancer screening with Google and NHS, and led global health policy initiatives. Ashrafian’s work bridges medicine, history, and philosophy, including his contributions to understanding historical figures’ medical conditions, such as King Tutankhamun’s epilepsy. He has authored over 550 publications, 12 books, and holds a PhD in computational physiology and an MBA with distinction. Awards include the Hunterian Prize and Wellcome Trust Fellowship. His research also explores AI ethics, quantum physics paradoxes, and art-based medical diagnostics. Education: PhD in Computational Physiology (Imperial College London) MBA (Warwick Business School) MD (University College London) Bachelor of Science in Immunology (University College London) Research Interests: Ashrafian’s work spans: AI in Medicine: Diagnostic algorithms, guideline development (STARD-AI/QUADAS-AI), and ethical frameworks. Metabolic Surgery: Bariatric interventions, gut microbiome, and obesity treatments. Ancient History: Medical analyses of historical figures (e.g., Tutankhamun, Julius Caesar) and art-based pathology identification. Philosophy: AI rights (AIONAI law), temporal paradoxes, and the Simulation Argument. Awards: Royal College of Surgeons Arris and Gale Lectureship Hunterian Prize Wellcome Trust Research Fellowship Advising & Innovation: Supervised >50 PhD students, co-founded Oxford Medical Products (weight loss tech), and serves as CSO at Flagship Pioneering’s Preemptive Health division. He advises on NHS digital transformation and global health policy. Labs/Teams: Leads AI initiatives at Imperial’s Institute of Global Health Innovation and collaborates with Google, NICE, and international institutions on health tech solutions.

Christos Faloutsosمشاهده پروفایل

استاد

• Data Mining
• Graph Mining
• Fractals and Power Laws
• +۳ مورد دیگر

Christos Faloutsos is the Fredkin Professor of Computer Science at Carnegie Mellon University, with a courtesy appointment in Electrical and Computer Engineering. He holds a B.Sc. from the National Technical University of Athens and M.Sc./Ph.D. from the University of Toronto. His research focuses on data mining, graph analysis, fractals, and database systems. Notable contributions include foundational work on R-trees, graph mining laws (e.g., Kronecker graphs), and applications in medical imaging, network security, and fraud detection. Key projects include PEGASUS (petascale graph mining), fraud detection in online auctions (NetProbe), and tools for human trafficking analysis (TrafficVis). He has led NSF-funded projects on tensor mining, network anomaly detection, and bioinformatics. Over 300 refereed publications highlight his contributions across databases, data mining, and networks. Awards include the KDD Best Paper (2005, 2016), SIGMOD Test-of-Time Award, and recognition as a top nurturer in IT. His lab collaborations span the Parallel Data Lab (PDL), Machine Learning Department, and Computational Biology.

Jimeng Sunمشاهده پروفایل

استاد

• Artificial Intelligence
• Healthcare Analytics
• Drug Discovery
• +۵ مورد دیگر

Dr. Jimeng Sun is a Health Innovation Professor at the Siebel School of Computing and Data Science and Carle Illinois College of Medicine at the University of Illinois Urbana-Champaign. Co-founder of Keiji AI , he leads groundbreaking research at the intersection of artificial intelligence and healthcare, actively deploying clinical AI systems and developing frameworks like PyHealth and Therapeutics Data Commons . His research spans four major areas: Clinical AI Systems : Developing interpretable models (e.g., RETAIN) for patient similarity, temporal event prediction, medication recommendation, and clinical outcome forecasting Drug Discovery : Creating molecular optimization frameworks, drug-target interaction models, and AI-driven platforms Clinical Trials : Pioneering patient-trial matching, outcome prediction, and optimization frameworks using deep learning and graph neural networks Biosignal Analysis : Advancing sleep staging, seizure classification, and automated EEG/Cardiac monitoring systems With over 500 top-tier publications (including in Nature , NEJM AI , and leading AI conferences) and an h-index of 99, his work has been recognized with the Top 100 AI Leaders in Drug Discovery and Advanced Healthcare award. He maintains active collaborations with institutions like Massachusetts General Hospital , Medidata Solutions , and OSF Healthcare . His recent publications reveal a strong focus on: Reinforcement learning applications in medical data analysis Large language model adaptation for clinical tasks Knowledge graph integration with AI systems Synthetic data generation for healthcare Multi-modal learning in clinical contexts Explainable AI for medical applications Dr. Sun's lab ( Sunlab ) emphasizes practical impact over theoretical work, actively collaborating with hospitals and healthtech companies. He welcomes contributions from clinicians, researchers, and industry partners through initiatives like his AI for Health webinar series .

• Bioelectronics
• Nanotechnology
• CMOS Technology
• +۱۲ مورد دیگر

Sandro Carrara is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he leads the Bio/CMOS Interfaces (BCI) laboratory. He is affiliated with the School of Engineering (STI), the Institute of Electrical Engineering (SCI-STI-SC), and the Integrated Systems Laboratory (LSI). His academic leadership spans teaching, doctoral supervision, and editorial roles in major journals including IEEE Sensors Journal and BioNanoScience. Education: Diploma in Electronics, National Technical Institute of Albenga, Italy Master in Physics, University of Genoa, Italy PhD in Biochemistry and Biophysics, University of Padua, Italy His research focuses on the integration of biological systems with CMOS technology, particularly in the development of nanoscale biosensors for health monitoring. Key areas include memristive biosensors, wearable and implantable sensors, electrochemical detection, and therapeutic drug monitoring. His work bridges electronics, nanotechnology, and biomedicine to enable point-of-care diagnostics and personalized medicine. His recent publications (2023–2025) show a strong trend toward sustainable printed electronics, machine learning for biosensing, in-memory computing for cancer diagnostics, and remote health monitoring. These works appear in high-impact journals such as IEEE Sensors Journal , Nanoscale , and Biosensors and Bioelectronics: X . Scientific Awards: IEEE Fellow (2015) IEEE Sensors Council Technical Achievement Award (2016) Distinguished Lecturer, IEEE Sensors Council (2017) Best Paper Award, IEEE MeMeA Symposium (2020) Multiple Gold and Bronze Leaf Prizes at PRIME and IEEE conferences Best Poster Awards at EMBEC and Nano-Tera meetings He actively advises PhD students and leads research projects involving CMOS-based biosensors, wireless implants, and smart sensor systems. His lab collaborates widely across disciplines and institutions, focusing on real-world applications in oncology, neurology, and environmental health. He has also contributed to the development of battery-free wearable devices, optical power transfer systems, and IoT-enabled telemedicine platforms. Laboratories and Teams: Bio/CMOS Interfaces (BCI) Laboratory, EPFL Integrated Systems Laboratory (LSI), EPFL Collaborations with IEEE Sensors Council and Circuits and Systems Society Editorial leadership in IEEE Sensors Journal and BioNanoScience

• Medical Physics
• Radiation Oncology
• Medical Imaging
• +۳ مورد دیگر

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 Desjardinsمشاهده پروفایل

استاد

• Imaging and sensing
• Robotics
• Machine learning
• +۶ مورد دیگر

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.

• Neural Interfaces
• Micro/Nano Electro Mechanical Systems (MEMS)
• Biosystems & Computational Biology
• +۳ مورد دیگر

Michel M. Maharbiz is a Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley. He leads research on miniaturized bioelectronic interfaces, including neural dust implants and cyborg insects. He holds affiliations with the Berkeley Sensor & Actuator Center (BSAC), Center for Neural Engineering & Prostheses (CNEP), and SWARM Lab. His education includes a Ph.D. in EECS from UC Berkeley (2003) and a B.S. in EE from Cornell University (1997). Maharbiz's research integrates MEMS, ultrasonic systems, and synthetic biology to develop wireless neural interfaces, implantable sensors, and biohybrid devices. Key focus areas are neural dust technology for peripheral nerve recording, magnetoelastic strain sensors for medical applications, and electrochemical biosensing using bacterial flagellar motors. His publications emphasize neural interfaces, ultrasonic implants, and biomedical monitoring. Recent articles explore ultrasonic power delivery (2025), radiation detectors for oncology (2025), and fracture-healing smart plates (2019). Trends include miniaturization of wireless implants, closed-loop therapeutic systems, and novel biomaterials. Scientific Awards: McKnight Technological Innovations in Neuroscience Award (2017) Chan-Zuckerberg Biohub Investigator (2017) NSF CAREER Award (2009) MIT TR10 Top Emerging Technology (2009) Bakar Fellows Spark Award (2012) He directs the Maharbiz Lab, advancing neural dust and bioelectronic interfaces. Projects include impedance-based fracture monitoring, carbon fiber neural arrays, and hernia repair sensors. Funding includes NSF and industry partnerships for implantable device development.

Joel Gohمشاهده پروفایل

دانشیار

• Health services and systems
• Transportation, logistics and supply chains
• Operations research
• +۶ مورد دیگر

Joel Goh is Associate Professor at the Department of Analytics and Operations, NUS Business School, National University of Singapore. He serves as Director of the J.Y. Pillay Comparative Asia Research Centre (under NUS Global Asia Institute) and PhD Program Director at the Institute of Operations Research and Analytics (IORA). Previously, he was Assistant Professor at Harvard Business School (2014-2017) and Visiting Scholar (2017-2022). BSc, MSc, PhD in Operations, Information, and Technology from Stanford University His research focuses on healthcare analytics (preventing health conditions, hospital operations, frailty assessment), supply chain analytics (digital business models, platform leakage), and service platform operations (hospital-at-home programs, incentive design). He co-created the Robust Optimization Made Easy (ROME) software. Recent publications analyze workplace psychological safety (2024), hospital-at-home models (2024), and platform leakage dynamics (2023). His work spans 18+ journals with 740+ citations for burnout cost studies (2022) and 606+ citations for physician well-being research (2017). Teaching Honors : 2023: Best MBA Teaching & Skinner Innovation Award 2021: NUS Annual Teaching Excellence Award 2020: Early Career Research Excellence Award & 40 Under 40 Best MBA Professors Advising & Grants : Served as PhD Program Director. Received NUS Start-Up Grant R-314-000-110-133 (2021) and Humanities & Social Sciences Fellowship (2021). Editorial roles include Associate Editor at Management Science , Manufacturing & Service Operations Management , and Senior Editor at Production and Operations Management .

Aleksandar Jeremicمشاهده پروفایل

دانشیار

• Biomedical Signal Processing
• Statistical Signal Processing
• Biometrics
• +۷ مورد دیگر

Aleksandar Jeremic is an Associate Professor in both the Electrical & Computer Engineering department and the McMaster School of Biomedical Engineering at McMaster University. His research focuses on biomedical signal processing, statistical signal processing, and biometrics, with applications in healthcare and biomedical systems. He holds a Dipl. Ing. from the University of Belgrade, and an M.S. and Ph.D. from the University of Illinois at Chicago. His expertise spans physiological signal analysis (e.g., ECG/EEG), medical imaging, and machine learning for biomedical applications. He has authored over 50 technical articles and two book chapters, and has been recognized with a teaching award from the McMaster Electrical and Computer Engineering Society (2018). He supervises graduate students in both theoretical and applied research areas. Dr. Jeremic teaches advanced courses such as Biomedical Signal Modeling and Processing and Advanced Probability and Random Processes , emphasizing practical applications of signal processing in healthcare. His work includes clinical implementations like neonatal seizure monitoring software and microwave imaging for breast cancer detection.

Michael McAlpineمشاهده پروفایل

استاد

• 3D Printing
• Nanotechnology
• Biomedical Engineering
• +۴ مورد دیگر

Michael McAlpine is a Professor in the Mechanical Engineering department at the University of Minnesota . He also holds affiliations with the Biomedical Engineering and Electrical and Computer Engineering departments. His research focuses on 3D printing functional materials & devices , Nanoscale inks , Biomedical devices , Bioelectronics , and Flexible Microsystems . Research Interests : 3D Printing, Biomedical Engineering, Nanotechnology, Flexible Electronics, Microfluidics Labs : ME 361/363 Contact : mcalpine@umn.edu , (612) 626-3303, ME 117 Recent Research Trends include 3D Printed Biomedical Devices , Flexible Electronics , and Bioprinting Applications . His work spans from Spinal Organoid Formation to Programmable Drug Release Capsules . Scientific Award : Circulation Research 2020 Best Manuscript Award

Christopher Kananمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Deep Learning
• Continual Learning
• +۵ مورد دیگر

Christopher Kanan is a tenured Associate Professor of Computer Science at the University of Rochester, leading the AI Initiative within the Hajim School of Engineering & Applied Sciences. He holds secondary appointments in Brain and Cognitive Sciences, the Goergen Institute for Data Science and AI (GIDS-AI), and the Center for Visual Science. His research focuses on deep learning systems for artificial general intelligence (AGI), including continual learning, medical computer vision, and visual question answering. Previously, he was an Associate Professor at RIT’s Carlson Center for Imaging Science and a leader at Paige.AI, contributing to the FDA-cleared Paige Prostate system. Kanan earned his PhD from UC San Diego, completed postdoctoral work at Caltech, and worked at NASA JPL. Education: PhD in Computer Science, UC San Diego MS in Computer Science, University of Southern California Bachelor’s in Philosophy and Computer Science, Oklahoma State University Research Interests: Kanan’s work spans foundational AI capabilities like continual learning, medical imaging (pathology and radiology), multi-modal reasoning, and cognitive science-inspired models. His lab develops bias-robust AI systems and applies deep learning to healthcare and fusion research. Articles Trends: His recent work emphasizes out-of-distribution generalization, foundation models in pathology, and stability in continual learning. Key themes include AI applications in healthcare, model robustness, and neuroscience-inspired algorithms. Awards: NSF CAREER Award Senior Member, AAAI and IEEE DoE and NSF grants totaling $5M+ DARPA/ARL awards Advising & Grants: Mentored over 10 PhD students, including Robik Shrestha and Usman Mahmood. Secured grants for AI in nuclear fusion and medical imaging. Led RIT’s Center for Human-aware AI (CHAI) as Associate Director. Labs & Teams: Heads the University of Rochester AI Initiative, collaborates with Paige.AI, and leads teams advancing AI in pathology and robotics. His lab’s KLab (klab.cis.rit.edu) focuses on vision and learning systems.

David Ericksonمشاهده پروفایل

استاد

• Global Health Technology
• Medical Diagnostics
• Microfluidics
• +۵ مورد دیگر

David Erickson is the SC Thomas Sze Director and Sibley College Professor at Cornell University's Sibley School of Mechanical and Aerospace Engineering. He also holds a joint professorship in the Division of Nutritional Sciences. His research focuses on global health technologies, medical diagnostics, microfluidics, photonics, nanotechnology, and energy systems. He previously served as Associate Dean of Engineering for Research and Graduate Programs. Erickson leads the NIH-funded PORTENT Center for Point-of-Care Technologies in Global Health and has co-founded companies like Dimensional Energy and VitaScan to commercialize diagnostic and energy technologies. Education: B.Sc., Mechanical Engineering, University of Alberta (1999) M.A.Sc., Mechanical Engineering, University of Toronto (2001) Ph.D., Mechanical Engineering, University of Toronto (2004) Postdoctoral Scholar, Electrical Engineering, California Institute of Technology (2005) Research Interests: Erickson’s work spans global health diagnostics , nanobio applications , and clean energy innovation . He develops portable medical devices for low-resource settings, including smartphone-integrated diagnostic tools for malaria, iron deficiency, and cancer. His lab also pioneers photothermal reactors for CO2 conversion into sustainable fuels. Key areas include: Point-of-care testing for infectious diseases and nutritional deficiencies Nanofluidic and optofluidic technologies for biomolecular analysis Solar-driven energy systems for carbon-neutral fuels Awards: Presidential Early Career Award for Scientists and Engineers (2011) Fellowships from the Optical Society, ASME, and Canadian Academy of Engineering Carbon X-Prize Finalist (2019) for Dimensional Energy’s CO2-to-fuel technology Grants & Industry Collaboration: Erickson’s research is funded by NIH, NSF, ARPA-E, DOE, and USAID. His lab’s innovations have spun off start-ups addressing global health and energy challenges. Notable projects include: - Portable cancer diagnostics in sub-Saharan Africa using mobile phone-based systems - Solar-powered CO2 conversion reactors tested in Wyoming and Arizona Labs & Teams: The Erickson Lab collaborates with the Cornell Atkinson Center for Sustainability and the McGovern Center for Entrepreneurship. Key initiatives include the PORTENT Center and the Dimensional Energy CO2-to-fuel project.

Burak Ozdoganlarمشاهده پروفایل

استاد

• Manufacturing Processes
• Biomedical Engineering
• Materials Science
• +۷ مورد دیگر

Burak Ozdoganlar is a Ver Planck Endowed Chair Professor of Mechanical Engineering at Carnegie Mellon University (CMU) and Associate Director of the Engineering Research Accelerator. He holds courtesy faculty positions in Biomedical Engineering and Materials Science and Engineering. Ozdoganlar earned his Ph.D. in Mechanical Engineering from the University of Michigan (1999), M.S. degrees from Ohio State University (1993, 1995), and a B.S. in Aeronautical Engineering from Istanbul Technical University (1991). Ph.D., Mechanical Engineering, University of Michigan (1999) MS, Mechanical Engineering, Ohio State University (1995) MS, Aeronautical and Astronautical Engineering, Ohio State University (1993) BS, Aeronautical Engineering, Istanbul Technical University (1991) Ozdoganlar’s research focuses on multi-scale manufacturing processes (macro/micro/nano), precision engineering , structural dynamics , and modal testing , with applications in biomedical device fabrication , microneedle arrays , soft electronics , and 3D ice printing for vascular networks. His work bridges computational modeling with experimental validation. Recent scientific awards include the 2023 AIMBE College of Fellows induction, ASME Fellow (2019), and NSF CAREER Award (2006). He served as interim CTO of the Advanced Robotics for Manufacturing (ARM) Institute and chaired the ASME-MED Manufacturing Equipment Technical Committee. Ozdoganlar leads projects in scalable manufacturing for implantable medical devices , bioelectric medicine , and wearable robotics . His lab develops 3D ice-printed vascular templates for tissue engineering and liquid metal circuits for soft electronics, funded by institutions like the Manufacturing Futures Institute and ARPA-H.

Kelly Arnoldمشاهده پروفایل

دانشیار

• Biomedical Computation and Modeling
• Drug Delivery and Therapeutics
• Systems Immunology
• +۵ مورد دیگر

Kelly Arnold is an Associate Professor in the Department of Biomedical Engineering at the University of Michigan. Her research integrates systems engineering principles with immunology to investigate variability in immune responses across infection, vaccination, and injury, with a focus on computational modeling and clinical translation. Research Focus Systems-level immune response modeling Vaccination and antibody functionality Vaginal microbiome-host interactions Chronic lung disease progression Computational serology and proteomics Recent Work Her 2025 studies examine SARS-CoV-2 vaccination responses in cancer patients and computational frameworks for vaginal probiotics. Earlier works (2024-2007) span COPD progression, lupus fibrosis, HIV susceptibility, and tissue engineering for fertility preservation. Methodologies include proteomic profiling, network modeling, and microfluidic systems.

Anantha Chandrakasanمشاهده پروفایل

استاد

• Energy-Efficient Circuits
• Integrated Systems
• AI Hardware Security
• +۳ مورد دیگر

Anantha Chandrakasan is the Vannevar Bush Professor of Electrical Engineering and Computer Science at MIT, serving as Dean of the MIT School of Engineering and Chief Innovation and Strategy Officer. His research focuses on energy-efficient integrated circuits, medical devices, and AI hardware security. He leads the MIT Energy-Efficient Circuits and Systems Group, developing systems for biomedical applications, wireless communication, and quantum computing. He holds appointments at MIT's Microsystems Technology Laboratories and has contributed to collaborations like the MIT-Takeda Program in AI-driven healthcare and a partnership with GlobalFoundries for energy-efficient AI chips. His work spans implantable drug delivery systems, conformable ultrasound patches, and secure edge computing architectures. Chandrakasan's innovations include ultra-low-power circuits for IoT devices, cryptographic processors for post-quantum security, and AI accelerators for edge applications. He emphasizes interdisciplinary research bridging electrical engineering with biomedical and quantum fields, supported by leadership roles in MIT's strategic initiatives. His contributions to energy-efficient computing have led to advancements in wearable health monitors, batteryless sensors, and secure communication protocols for medical devices. Ongoing projects include THz integrated systems and AI-enhanced analog circuit design optimization.