جست‌وجوی استاد و پژوهشگر

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.

Zhongliang Jiangمشاهده پروفایل

پژوهشگر

• Medical Robotics
• Image Processing
• Robotic Learning
• +۳ مورد دیگر

Dr. Zhongliang Jiang is a senior research scientist and leader of the Robotics and Ultrasound team (RobUSt) at the Chair of Computer Aided Medical Procedures (CAMP) at Technische Universität München. He holds a Ph.D. in computer sciences (summa cum laude) and has authored/co-authored over 40 top-tier publications in robotics and medical imaging. His research focuses on robotic ultrasound systems, medical image processing, and robotic learning. Education: Ph.D. in Computer Sciences, TUM (2022, summa cum laude) M.Eng. in Harbin Institute of Technology (2017) Research Assistant at SIAT (2017-2018) Research Interests: Medical Robotics: autonomous robotic ultrasound systems Image Processing: RGB-D/ultrasound segmentation, registration Robotic Learning: reinforcement/imitation learning Robotic Control: MPC, shared control, human-robot interaction Professional Contributions: Associate Editor for ICRA 2024/2025 Guest Editor for IEEE TRO special issue on Robot-Assisted Medical Imaging Main organizer of RAMI workshops at ICRA (2023-2025) Awards: MICCAI 2023 Best Paper Runner-up Gold Medal for Master's Thesis (2017) Lab & Teaching: Leading the RobUSt team developing advanced robotic ultrasound solutions Teaching courses like Computer Aided Medical Procedures and Medical Augmented Reality Supervised over 15 Master/PhD projects in robotic ultrasound and medical imaging

Benjamin Busamمشاهده پروفایل

پژوهشگر

• 3D Computer Vision
• Multi-Modal Sensor Fusion
• Collaborative Robotics
• +۶ مورد دیگر

Dr. Benjamin Busam is a Senior Research Scientist at the Technical University of Munich , affiliated with the Chair for Computer Science Applications in Medicine under Prof. Nassir Navab. Starting September 2025, he will hold the Professorship for Photogrammetry and Remote Sensing at TUM. His career includes leadership roles at FRAMOS Imaging Systems and Huawei Research in London. Education: Mathematics (TUM), Mathematics and Physics (ParisTech, University of Melbourne), PhD in Mathematics (TUM, 2014) His research focuses on 3D computer vision , multi-modal sensor fusion , and their applications in collaborative robotics and augmented reality . He specializes in projective geometry , 6D pose estimation , and neural radiance fields , with a particular emphasis on photometrically challenging environments. Recent publications highlight advancements in 3D scene understanding , neural rendering , and medical imaging , often leveraging machine learning and vision-language models . His work has been recognized through awards like the EMVA Young Professional Award (2015) and Innovation Pioneer of the Year (2019) , along with multiple Outstanding Reviewer distinctions at leading conferences. Dr. Busam has supervised numerous PhD and MSc students on topics including 6D pose estimation , medical augmented reality , and robotic ultrasound , collaborating with institutions like MIT , École Polytechnique , and University of Padova .

Xiaofeng Liuمشاهده پروفایل

استادیار

• Artificial Intelligence
• Deep Learning
• Medical Imaging
• +۵ مورد دیگر

Xiaofeng Liu is an Assistant Professor at Yale University School of Medicine in the Departments of Radiology & Biomedical Imaging and Biomedical Informatics & Data Science. He is also an Associate Member at the Broad Institute of MIT and Harvard. Previously, he held faculty positions at Harvard Medical School and research roles at Massachusetts General Hospital and Beth Israel Deaconess Medical Center. PhD in Mechatronics from University of Chinese Academy of Sciences Dual Bachelor's degrees in Automation (Wang-Daheng Elite Class) and Communication from University of Science and Technology of China His research integrates trustworthy AI, medical imaging, and data science to improve diagnosis, prognosis, and treatment monitoring for neurological disorders, cancer, and cardiovascular diseases. Key focus areas include domain adaptation techniques, diffusion models, and interpretable AI systems. Led special issues in IEEE Transactions on Pattern Analysis and Medical Image Analysis Developed novel frameworks like Ordinal UDA and Memory-Consistent Adaptation Scientific accolades include the Trailblazer R21 Award (NIBIB), OpenAI Research Award, and National Artificial Intelligence Research Resource Pilot Award. He serves as Associate Editor for IEEE Transactions on Neural Networks and Learning Systems and actively contributes to MICCAI and NIH review panels. His lab at Yale (XLiu Lab) investigates neural basis of intelligence to inspire AI development, with applications in brain tumor segmentation, cardiac imaging, and cross-modal medical diagnostics.

Sonja Paus-Buzinkمشاهده پروفایل

استادیار

• Human Factors
• Ergonomics
• Usability
• +۸ مورد دیگر

Sonja Paus-Buzink is an Assistant Professor in Human Factors at TU Delft’s Faculty of Industrial Design Engineering, specializing in the Human-Centered Design department. Her research focuses on integrating human factors/usability evaluation into medical device and healthcare service design, emphasizing inclusive design perspectives. She teaches courses on human factors, usability, and medical device regulation, supervising students in research and graduation projects. Academic Background: PhD from TU Delft (Medisign Research Group), co-funded by Catharina Hospital, focusing on patient safety in image-based surgical procedures and VR/AR simulation tools. Postdoctoral work on surgical skillslabs and scientific coordination of the European Laparoscopic Surgical Skills Program. Previously a Managing Human Factors Specialist at UL-Wiklund R&D, advising medical device manufacturers on regulatory compliance. Research Interests: Human factors, ergonomics, medical device design, patient safety, inclusive design, surgical training, and healthcare technology. Her work bridges clinical, engineering, and psychological disciplines to enhance healthcare outcomes. Awards: Summa Cum Laude MSc in Industrial Design Engineering (TU Delft). Best IDE Graduate of the Year award at TU Delft. Grants & Collaborations: Collaborations with medical institutes, simulator companies, and organizations like the European Association for Endoscopic Surgery (EAES). Her research emphasizes cross-disciplinary teamwork to address challenges in surgical training and medical device usability. Labs/Teams: Engaged with TU Delft’s Medisign research group and skillslab initiatives. Active in developing tools for surgical training and patient safety in operating rooms.

• Computer Vision
• Medical Image Analysis
• Retinal Image Analysis
• +۷ مورد دیگر

Emanuele (Manuel) Trucco is a Professor of Computing and holds the NRP Chair of Computational Vision in the School of Science and Engineering at the University of Dundee. He is also an Honorary Clinical Researcher at NHS Tayside and previously served as an Adjunct Professor at the Chinese Academy of Sciences (2018–2021). His research is centered on computational vision and medical image analysis, particularly in retinal imaging and its applications in systemic disease detection. PhD, Electronic Engineering, University of Genoa (1990) MSc, Electronic Engineering, University of Genoa (1984) Manuel Trucco's research focuses on computer vision and medical image analysis , with a strong emphasis on retinal image analysis for early detection of diseases such as diabetes, cardiovascular conditions, stroke, dementia, and neurodegenerative disorders. He co-directs the VAMPIRE (Vessel Assessment and Measurement Platform for Images of the Retina) initiative, a collaborative effort between the Universities of Dundee and Edinburgh. This platform enables automated, multi-modal analysis of retinal images and has been used in biomarker studies across the UK and internationally. His work integrates deep learning , artificial intelligence , and biomedical engineering to develop non-invasive, scalable diagnostic tools. Industrial collaborations include Canon Medical, OPTOS plc, NIDEK, and Epipole plc, while institutional partners include the Royal College of Ophthalmologists and the UK Biobank Eye and Vision Consortium. Recent publications highlight a strong trend in using AI and deep learning to extract clinical insights from retinal images, including predicting cardiovascular outcomes in diabetic patients, estimating biological age, and analyzing retinal vasculature changes under physiological stress. His work bridges computer science, ophthalmology, and public health, contributing to precision medicine and health equity. His scientific contributions have been recognized through fellowships: FRSA (Fellow of the Royal Society of Arts) FIAPR (Fellow of the International Association for Pattern Recognition) Trucco has led or co-led major research projects, including a £7M NIHR grant on precision medicine for diabetes (Dundee-Chennai), a £1.1M EPSRC grant on vascular dementia biomarkers (PI), the 3M-Euro ITN "REVAMMAD", and several PhD studentships sponsored by OPTOS, NIDEK, SINAPSE, and Toshiba. He has served on the organizing and program committees of major international conferences such as MICCAI and the European Conference on Computer Vision. He is a key member of the VAMPIRE research team and the UK Biobank Eye and Vision Consortium , contributing to large-scale data analysis efforts in vision and systemic disease. His work is at the forefront of AI-driven healthcare innovation, with real-world applications in early disease detection and personalized medicine.

Natalia Imad Khalafمشاهده پروفایل

استادیار

• Pancreatic Cancer
• Gastroenterology
• Epidemiology
• +۳ مورد دیگر

Natalia Imad Khalaf, MD, MPH, FACP is an Assistant Professor in the Department of Medicine at Baylor College of Medicine with dual appointments as Clinical Investigator in the Clinical Effectiveness and Population Health Program and Core Faculty in the Health Policy, Quality & Informatics Program at the Center for Innovations in Quality, Effectiveness and Safety (IQuESt) at Michael E. DeBakey VA Medical Center. Her academic trajectory spans clinical gastroenterology, epidemiology, and health services research with focus on cancer outcomes. Her educational foundation includes: BA in Biological Sciences from Rice University (2007) MD from Baylor College of Medicine (2011) Internal Medicine Residency and Chief Medical Residency at Baylor College of Medicine (2014-2015) Gastroenterology & Hepatology Fellowship at Brigham and Women's Hospital (2018) MPH in Epidemiology from Harvard T.H. Chan School of Public Health (2018) Dr. Khalaf's research program centers on pancreatic cancer epidemiology, with emphasis on early detection biomarkers (particularly new-onset diabetes), metabolic risk factors, and healthcare system interventions. Her work integrates clinical gastroenterology with population health methodologies to address diagnostic delays, racial disparities in treatment, and implementation of evidence-based guidelines in gastrointestinal cancers. She actively develops risk prediction tools using health informatics and deep learning approaches. Analysis of her recent publications reveals a concentrated focus on pancreatic cancer pathophysiology and outcomes, with significant contributions to understanding pre-diagnostic metabolic changes, emergency presentation consequences, and diabetes-cancer linkages. Her colorectal cancer work examines screening adherence barriers and medication risk associations, while quality improvement research targets guideline implementation for gastric intestinal metaplasia. Her scientific recognition includes: AGA Academy of Educators Elected Member (2018) Bob Parsons Inaugural Fellow in Pancreatic Cancer Research (2017-2018) American Gastroenterological Association Early Career Investigator Recognition (2017) Soma Weiss Award for Clinical Teaching Excellence (2017) Dean of Medical Education Outstanding Resident Teacher Award (2013) Phi Beta Kappa Honor Society (2007) Dr. Khalaf directs multiple federally funded research initiatives including: VA Career Development Award: Health Informatics Approaches to Improve Early Diagnosis of Pancreatic Cancer ($1.09M, 2022-2026) National Academy of Sciences: Clinical Quality Measures for Gastrointestinal Cancers (2022-2027) Gordon and Betty Moore Foundation: Implementing Digital Quality Measures (2024-2025) American Pancreatic Association Young Investigator Grant (2019-2021) She operates within the IQuESt research ecosystem at the Michael E. DeBakey VA, leveraging the Clinical Effectiveness and Population Health Program infrastructure for her work on cancer diagnostic excellence, veteran health outcomes, and implementation science projects targeting gastrointestinal cancer care pathways.

Alan Kuntzمشاهده پروفایل

استادیار

• Robot Motion Planning
• Autonomous Systems
• Robot Design Optimization
• +۴ مورد دیگر

Alan Kuntz is an Assistant Professor at the University of Utah's Kahlert School of Computing (KSoC) and a core member of the Robotics Center. He leads the interdisciplinary Kuntz Research Lab, focusing on robotics and computational methods with medical applications, particularly in healthcare and surgery. His work spans robot motion planning, autonomous systems, and robot design optimization. Education: Ph.D. in Computer Science from the University of North Carolina at Chapel Hill, with research in the Computational Robotics Research Group. Previously a postdoctoral scholar at Vanderbilt University's Medical Engineering and Discovery Lab. Research interests include surgical robotics, continuum robots, needle steering, and medical device design. Recent projects include autonomous needle navigation, continuum lung staplers, and metamaterial-based robots. His team has published extensively on topics like kinematic modeling, uncertainty quantification, and medical intervention systems. Notable awards include the 2022 IEEE Access Best Video Award for his group's work, and mentoring over 15 students through the University of Utah's Undergraduate Research Opportunities Program. The Kuntz Lab actively collaborates on clinical applications, presenting at top conferences like IROS, Hamlyn Symposium, and ISMR. Labs/Teams: Directs the Kuntz Research Lab, known for its innovative medical robotics projects. The lab's work has been featured in Forbes and other media outlets for breakthroughs like in vivo needle steering demonstrations.

Sharib Aliمشاهده پروفایل

استادیار

• Biomedical Image Analysis
• Computer Vision
• Machine Learning
• +۱۲ مورد دیگر

Dr. Sharib Ali is a Lecturer (Assistant Professor) in the School of Computer Science at the University of Leeds, Faculty of Engineering and Physical Sciences. He is affiliated with the Leeds Cancer Research Centre and actively contributes to research in biomedical image analysis and computer vision. His work bridges cutting-edge AI with clinical applications, particularly in endoscopy and surgical technologies. PhD in Medical Image Analysis, University of Lorraine, France MSc in Computer Vision (by research), University of Burgundy, France Dr. Ali's research focuses on biomedical image analysis , computer vision , and machine learning , with applications in early cancer detection , computational endoscopy , and 3D reconstruction . He develops robust algorithms for segmentation, registration, depth estimation, and mosaicking, using both classical mathematical models and deep learning. His work emphasizes translational research and generalisability in real-world clinical settings. The recent publications highlight a strong trend in generalisability assessment , multi-modal data fusion , and AI benchmarking in endoscopy. His work spans from foundational algorithm development to clinical deployment, including federated learning , mixed reality in surgery , and multi-centre datasets , addressing key challenges like bias, data imbalance, and privacy. Dr. Ali has co-supervised multiple DPhil/PhD students and currently supervises several PhD candidates at the University of Leeds, University of Oxford, and Tec de Monterrey. He is actively involved in securing research funding and leading projects such as Leveraging multi-modality data for targeted biopsy and Federated learning in healthcare . He is a founding member of NAAMII, Nepal, where he volunteers to train students from LMICs. He also organizes international research initiatives including the EndoCV and P2ILF challenges at MICCAI, and serves on program committees and as a reviewer for journals like Nature Communications and Medical Image Analysis . His research is conducted within interdisciplinary teams, collaborating with clinicians from Oxford NHS University Hospitals, neuroscientists at Forschungszentrum Jülich, and engineers across Europe. He leads the development of open tools and datasets to advance the field of endoscopic computer vision.

• Artificial Intelligence in Medicine
• Wearable Sensors
• Medical Imaging
• +۳ مورد دیگر

Mozziyar Etemadi, MD, PhD, is an Assistant Professor at Northwestern University, holding dual appointments in the Feinberg School of Medicine (Department of Anesthesiology) and the Mccormick School of Engineering . His research focuses on integrating artificial intelligence with wearable technology to address critical challenges in clinical care, particularly in cardiology, gastroenterology, and maternal health. He leads projects in the Institute for Augmented Intelligence in Medicine and Northwestern University Clinical and Translational Sciences Institute (NUCATS) . **Education**: BS and MS from Stanford University (2008–2009); PhD and MD from University of California, San Francisco (2013–2016). Postdoctoral training included Computer Science at UC Berkeley (2014) and Anesthesiology residency at Northwestern (2021). Board-certified in Anesthesiology. **Research**: Develops AI-driven tools for non-invasive monitoring (e.g., wearable sensors for heart failure, pulmonary pressure estimation) and diagnostic systems in radiology and gastroenterology. Key areas include reducing racial bias in clinical AI, improving radiologist efficiency, and global health applications like fetal ultrasound in low-resource settings. **Awards**: Notable recognitions include Forbes 30 Under 30 in Science (2011) , CIMIT Prize for Primary Care Innovation (2012) , and a Best Paper Award at EICS (2015) . **Industry Ties**: Collaborates with Cardiosense and other entities, focusing on translational AI solutions for clinical challenges. His work balances academic innovation with real-world healthcare impact.

Mette Kalagerمشاهده پروفایل

استاد

• Cancer Epidemiology
• Colorectal Cancer Screening
• Health Economics
• +۵ مورد دیگر

Mette Kalager is a Professor at the Department of Health Management and Health Economics within the Faculty of Medicine at the University of Oslo. Her research focuses on cancer epidemiology, colorectal cancer screening, and health economics, with extensive contributions to understanding overdiagnosis in cancer screening and optimizing colonoscopy practices. She maintains an active research program with numerous high-impact publications in leading medical journals. Her primary research interests center on cancer screening effectiveness, particularly in colorectal cancer prevention. Dr. Kalager's work explores the balance between benefits and harms of screening programs, with special attention to overdiagnosis and the development of risk prediction models. She has made significant contributions to understanding the relationship between adenoma detection rates and subsequent cancer risk, as well as the impact of artificial intelligence on colonoscopy quality. Her research portfolio demonstrates a consistent focus on evidence-based approaches to cancer prevention and healthcare decision making. Analysis of her recent publications reveals a strong emphasis on methodological approaches to evaluating cancer screening programs, with increasing integration of artificial intelligence applications in endoscopy. Her work spans epidemiological modeling, clinical trials, systematic reviews, and health policy analysis, consistently addressing critical questions about the effectiveness and efficiency of cancer prevention strategies. The research demonstrates a trajectory toward more personalized approaches to cancer screening based on individual risk assessment. Dr. Kalager leads or participates in multiple significant research projects including COLONIZE (focusing on Clostridioides difficile infection treatment), EPoS (European Polyp Surveillance), EndoBRAIN International, I-SCAN (Scandinavian study on IBD and cancer), NordICC (Nordic-European study on colorectal cancer prevention), and several others addressing gastrointestinal diseases, cancer risk, and healthcare interventions. Her collaborative approach is evident through extensive co-authorship with researchers across Europe and beyond.

Samir Mardiniمشاهده پروفایل

استاد

• Craniofacial surgery
• Facial paralysis and reanimation surgery
• Facial transplant
• +۷ مورد دیگر

Dr. Samir Mardini is Chair of the Division of Plastic and Reconstructive Surgery at Mayo Clinic in Rochester, Minnesota, where he leads a team of fourteen plastic surgeons and hundreds of providers and Allied Health staff. A globally recognized expert in craniofacial surgery and facial paralysis and reanimation, Dr. Mardini was instrumental in establishing Mayo Clinic's groundbreaking face transplant program and led the team that performed the institution's first face transplant. Dr. Mardini completed his plastic surgery residency at Georgetown University Medical Center, followed by specialized craniofacial and reconstructive microsurgery fellowships at Chang Gung Memorial Hospital in Taiwan, where he also worked as an academic surgeon for two years before joining Mayo Clinic. His educational journey reflects a commitment to mastering advanced techniques across international settings. Dr. Mardini's research focuses on facial nerve studies, facial allotransplantation, facial anatomy, regenerative medicine, cleft and craniofacial diseases, and 3D imaging/virtual surgery planning. His clinical work spans craniofacial surgery for children and adults, cleft lip and palate repair, facial reanimation, facial plastic surgery, facial trauma, and complex reconstructive procedures. He has particular expertise in restoring function and aesthetics for patients with facial paralysis. Analysis of Dr. Mardini's recent publications reveals a strong emphasis on innovation in facial transplantation, virtual surgical planning, and craniofacial reconstruction. His scholarly output demonstrates consistent productivity with significant contributions across plastic surgery, transplant medicine, and medical imaging disciplines. The thematic continuity in his work shows a sustained focus on improving outcomes for patients with complex facial conditions. Teacher of the Year for Plastic Surgery (two consecutive years) Teacher of the Year for Surgery and Surgical Sub-Specialties at Mayo Clinic 2025 Gold Telly Award for Derek Pfaff Face Transplant documentary 2025 Small Grands Program Award from Mayo Clinic's Division of Surgical Research 2024 William ReMine Lectureship Award from the Priestley Society 2019 Skoog Lectureship 2011 Godina Traveling Fellowship Award As an educator, Dr. Mardini served as Program Director for the Plastic Surgery Residency for eight years, establishing Mayo Clinic's first Integrated Plastic Surgery Residency program that graduates four residents annually. He has edited six peer-reviewed journals and authored over 190 peer-reviewed articles. His humanitarian commitment is evident through over 30 international volunteer missions where he performed surgery for more than 700 children with cleft and craniofacial conditions. Dr. Mardini leads the Mayo Clinic Face Transplant Program, which represents the culmination of his expertise in craniofacial surgery, microsurgery, and facial reanimation. His approach emphasizes holistic, respectful, and attentive care that addresses both functional and aesthetic concerns, regularly collaborating with physicians across specialties to provide comprehensive treatment for patients with facial differences.

Lin Maمشاهده پروفایل

استاد

• Optical Measurement Techniques
• Laser Sensors
• Non-Intrusive Thermal Measurements
• +۴ مورد دیگر

Lin Ma is a Professor in the Department of Mechanical Engineering at the University of Virginia. His research focuses on 4D diagnostics and thermal-fluid systems, including novel optical measurement techniques for combustion and propulsion studies. He holds a Ph.D. from Stanford University (2006), an M.S. from Stanford (2001), and a B.S. from Tsinghua University (2000). Key research areas include laser-based diagnostics, tomography, non-intrusive measurements in harsh environments, and thermal management of energy systems. His work emphasizes 3D flow visualization and combustion analysis using advanced imaging techniques like VLIF and tomographic chemiluminescence. Notable awards include the NSF Career Award (2009) and the Air Force Summer Faculty Fellowship (2014-2016). His research has been applied to gas turbine exhaust characterization, battery thermal management, and high-speed combustion diagnostics in supersonic environments. Collaborations involve developing algorithms for 3D reconstruction and error correction in turbulent flow measurements.

Michael R Abernمشاهده پروفایل

دانشیار

• Urologic Oncology
• Prostate Cancer Biomarkers
• Quantitative Imaging
• +۳ مورد دیگر

Michael R. Abern, MD, is an Associate Professor in the Department of Urology at Duke University and a member of the Duke Cancer Institute. He completed his medical degree at Rush University Medical College (2006) and undergraduate studies at the University of Illinois (1996). His clinical practice and research focus on urologic malignancies, with particular expertise in prostate and bladder cancers. Dr. Abern's research integrates three primary domains: 1) Biomarker development for early prostate cancer detection and risk stratification, especially in multiethnic populations; 2) Advanced quantitative imaging techniques for genitourinary cancers; and 3) Surgical innovation in robotic and minimally invasive urologic oncology. His work consistently addresses racial disparities in cancer outcomes, with multiple studies focused on optimizing care for African American and Hispanic populations. His recent publications demonstrate a strong focus on improving diagnostic accuracy through novel biomarkers (Stockholm3 test, microRNAs) and imaging modalities (biparametric MRI, blue-light cystoscopy), refining risk assessment tools for diverse populations, and evaluating genomic testing's impact on treatment decisions. Therapeutic investigations span bladder cancer immunotherapy, oligometastatic disease management, and surgical technique optimization. Dr. Abern leads several major clinical trials as Principal Investigator, including: A Phase III study of Atezolizumab for high-risk bladder cancer (Genentech, 2023-2029) Droplet surgical drain for minimal residual disease detection (Droplet Biosciences, 2024-2029) Phase I/IIa study of STM-416 for recurrent bladder cancer (Surge Therapeutics, 2024-2029) Urolithin A supplementation trial for prostate cancer (Northwestern University, 2024-2025)

Philippe Poignetمشاهده پروفایل

استاد

• Surgical Robotics
• Medical Robotics
• Robotic Systems
• +۷ مورد دیگر

Philippe Poignet is a Professor at the University of Montpellier, affiliated with the Institut Universitaire de Technologie (IUT) and conducting research at the LIRMM (Laboratory of Informatics, Robotics, and Microelectronics of Montpellier). He served as Director of LIRMM from July 2015 to October 2023 and co-heads the IRP with Stanford University since 2025. His work focuses on Surgical Robotics, with a particular emphasis on medical device development, control systems, and biomedical applications. Co-founder of startup ACUSURGICAL (retinal surgery robotics) Scientific collaborator with STERLAB (flexible ureteroscopy robotics) Co-organized Summer School on Surgical Robotics (SSSR) for 20 years His research spans medical robotics , control theory , and biomedical imaging , with applications in needle steering, tissue interaction, and surgical precision. Recent publications highlight advances in soft tensegrity design , model predictive control , and multi-modality imaging registration . Scientific recognition includes: Best Paper Award at ARK’22 Prix de l’Innovation de l’I-Site MUSE (2020) Chevalier des Palmes Académiques (2019) He supervises doctoral students in projects related to flexible robotics , bioimpression , and robotic shoulder surgery , with collaborations across Europe and industry partners like CARANX Medical and CEDRAT Technologies.