Find Academic Supervisors

Mary S. DietrichView profile

Professor

• Biostatistics
• Nursing Science
• Medical Statistics
• +7 more

Dr. Mary S. Dietrich is a Professor of Statistics & Measurement at Vanderbilt University School of Nursing. She holds affiliations with Biostatistics and Hearing & Speech departments. Her career began in 2006, combining statistical collaboration with academic computing and psychiatric neuroimaging expertise. She has advised Belmont University’s FNP program, fostering nursing science integration with statistical methods. Education: PhD in Statistics & Measurement (Vanderbilt), MS (Fort Hays State), BS (Bethel College) Her research focuses on advanced statistical methodologies in nursing and biomedical sciences, including group-based trajectory modeling, propensity score methods, and innovative applications in clinical trials. She actively collaborates on projects addressing lymphedema management, pediatric palliative care, and neuroimaging biomarkers for Alzheimer’s risk. Dr. Dietrich has led/co-investigated over 20 grants since 2014, including NIH-funded studies on labor disparities, cochlear implant technology, and human-animal interactions in pediatric oncology. Awards: Multiple Dean’s Awards (Vanderbilt Nursing), Hardy Wilcoxon Dissertation Award She contributes to editorial efforts advocating for evidence beyond p-value thresholds. Her work bridges statistical rigor with clinical relevance across disciplines such as audiology, oncology, and maternal health.

• Machine Learning
• Medical Imaging
• Orthopaedic Technology
• +3 more

Dr. Yuan Chai is a Researcher affiliated with the Kolling Institute of Medical Research and the Faculty of Medicine and Health at the University of Sydney. He serves as President of the Australia China Scholar Network. His work focuses on integrating machine learning, medical imaging, and 3D printing to advance orthopaedic surgical techniques and personalized medical solutions. Dr. Chai holds a Ph.D. in Medicine from the Australian National University (2019) and has conducted studies at the Pennsylvania State University in 3D printing technology. Research Interests: Machine learning applications in medical imaging, surgical planning, 3D modeling for orthopaedic implants, and precision cutting tools for patella surgery. Current projects include automated landmark detection models for surgical reports, accuracy analysis in 3D pre-operative planning, and digital twin models for predicting surgical outcomes. Publications span topics like pelvic tilt measurement, customized implant design, and laser polishing of 3D-printed materials. Notable awards include a 2023 speaking role at the Australia-China Emerging Leaders' Summit and finalist recognition in the Young Australia China Alumni Award (2020). Education: PhD (Medicine, ANU, 2019), Studies at Penn State (3D Printing) Awards: 6 major recognitions including Dean’s List (2014) and Best Laboratory Paper awards (2016, 2018) Labs/Teams: Active contributor at Kolling Institute; leads Australia-China Scholar Network initiatives

• Multimodal Deep Learning
• Adaptive and Contextual AI
• Natural Language Processing
• +3 more

Dr. Ruchit Agrawal is an Assistant Professor of Computer Science and Head of Computer Science Outreach at the University of Birmingham Dubai. Previously, he held roles including Postdoctoral Research Scientist at the University of Oxford, Marie-Curie Researcher at Queen Mary University of London, and AI Researcher at FBK, Italy. His research focuses on Multimodal Deep Learning, Adaptive AI, NLP, and Clinical Machine Learning. He earned a Ph.D. from Queen Mary University of London and M.S. and B.Tech degrees from IIIT Hyderabad. Education: Ph.D. in Computer Science (Queen Mary University of London), M.S. in Computer Science (IIIT Hyderabad), B.Tech. in Computer Science (IIIT Hyderabad). Research interests include AI-driven healthcare solutions, contextualized machine learning systems, and cross-lingual NLP. His work spans healthcare informatics, music informatics, and machine translation. He has collaborated on projects like MIP-Frontiers and contributed to advancements in multimodal stuttering detection and stock price prediction models. Professional roles also include software development stints at Google Summer of Code and teaching at IIIT Hyderabad. His outreach initiatives aim to promote computer science education and accessibility.

• Orthopedic Surgery
• Spine Surgery
• Minimally Invasive Surgery
• +4 more

Dr. Ram Kiran Alluri is an Clinical Assistant Professor at the Keck School of Medicine, University of Southern California , specializing in Orthopaedic Spine Surgery at the USC Spine Center . His clinical focus includes cervical spine surgery , minimally invasive techniques , and robotic-assisted procedures for adult spinal deformity and complex revision surgery . Undergraduate & Medical Education: University of California Los Angeles (UCLA) Residency: Orthopaedic Surgery at USC Fellowship: Minimally Invasive & Adult Spinal Deformity at Hospital for Special Surgery Dr. Alluri's research emphasizes clinical outcomes analysis and navigational technology in spine surgery. With over 80 peer-reviewed publications and 130+ conference presentations , his work spans topics like AI in medical education , spin bias in systematic reviews , and robotic surgery efficiency . Key awards include the SMISS Young Surgeon Grant and AAOS Best Poster Award . He holds active memberships in AAOS , NASS , and AO Spine .

Wouter WilsonView profile

Assistant Professor

• Orthopaedic Biomechanics
• Cartilage Mechanics
• Finite Element Modeling
• +2 more

Wouter Wilson is a part-time Assistant Professor in the Orthopaedic Biomechanics group at TU/e, where he supervises PhD students in biomechanics and finite element modeling. His research examines cartilage mechanics, orthopedic implants, and tissue engineering solutions. He holds an MSc in Mechanical Engineering and PhD from TU/e, with previous industry experience at GKN/Fokker Landing Gear as Engineering Manager. Current research focuses on computational biomechanics of spinal interventions, biomaterial development, and implant optimization. Publications demonstrate expertise in patient-specific modeling, mechanical testing of engineered tissues, and implant performance analysis. Research consistently addresses clinical translation challenges in orthopedics through experimental and computational approaches. Currently at Sioux Technologies as Senior Group Lead while maintaining academic affiliations.

• Biomedical Engineering
• Orthopaedic Surgery
• Medical Imaging
• +3 more

Riaz Khan is an Adjunct Professor at the University of Western Australia (UWA), affiliated with the School of Physics, Maths and Computing and the Department of Computer Science and Software Engineering. His research focuses on interdisciplinary applications of technology in healthcare, particularly in orthopaedic surgery, biomedical engineering, and medical imaging. He has contributed to advancements in surgical techniques, pain management, and rehabilitation technologies through collaborative projects. Key research areas include total knee arthroplasty optimization, precision bone shaping via laser ablation, smartphone-based motion tracking for post-surgical recovery, and analgesia protocols for orthopaedic patients. He has co-authored over 27 peer-reviewed publications and contributed to a Cochrane Review on patella resurfacing techniques. Dr. Khan has secured research funding, including a grant from Healthway for a smoking cessation initiative linked to hospital admissions (2009–2010). His work aligns with UN Sustainable Development Goals related to good health and well-being. Collaborations span biomedical optics, surgical innovation, and clinical outcome measurement.

Danial RoshandelView profile

Research Fellow

• Ocular Surface Disorders
• Limbal Stem Cell Transplantation
• Dry Eye Disease
• +3 more

Roles & Affiliations: Danial Roshandel holds the position of Adjunct Senior Research Fellow at the University of Western Australia (UWA) Medical School and the Centre for Ophthalmology and Visual Science (affiliated with the Lions Eye Institute). His academic journey includes roles as an Assistant Professor at Shahid Beheshti University of Medical Sciences (2015–2018) and Consultant Ophthalmologist at Kamkar Hospital (2014–2015). Primary University: The University of Western Australia Medical School: UWA Medical School Research Centre: Centre for Ophthalmology and Visual Science Education: Doctor of Philosophy (PhD) in Ophthalmology, UWA (2018–2022) Specialist in Ophthalmology, Shahid Beheshti University of Medical Sciences (2010–2014) Doctor of Medicine (MD), Golestan University of Medical Sciences (2003–2010) Research Interests: Focus on ocular surface disorders, limbal stem cell transplantation, dry eye disease, and genetic eye diseases. Key areas include biobanking for congenital aniridia (2022–present), retinitis pigmentosa progression monitoring (2018–2021), and corneal neovascularization (2014–2018). Publications & Research Trends: Recent work emphasizes stem cell therapies, adaptive optics imaging, and genetic predisposition studies. Notable contributions include studies on limbal stem cell differentiation and clinical applications of induced pluripotent stem cells. Awards: University Postgraduate Award (2018) Professional Activities: Serves as a peer reviewer for Scientific Reports , Retina , and Molecular Vision . Active in professional organizations like the Iranian Society of Ophthalmology and the Islamic Republic of Iran Medical Council. Labs & Collaborations: Collaborates with the Ocular Tissue Engineering Laboratory and the Lions Eye Institute. Research networks span Australia, Iran, and international partners in adaptive optics and genetic studies.

• Robotic Surgery
• Artificial Intelligence in Surgery
• Surgical Training
• +3 more

Andrew Ng serves as a Clinical Assistant Professor of Neurology (Clinician Educator) at the University of Southern California, focusing on the integration of artificial intelligence and robotics into surgical practice. His clinical educator role emphasizes advancing surgical training methodologies and performance assessment systems. His primary research interests include: Robotic surgery systems and implementation Artificial intelligence applications in surgical performance analysis Telesurgery frameworks and safety protocols Surgical training feedback mechanisms Urological and neurological surgical outcomes Objective assessment of surgical skills Analysis of his 2022-2025 publications reveals a dominant focus on AI-driven surgical performance metrics, particularly in robotic prostatectomy. His work establishes critical links between intraoperative technical skills and long-term patient outcomes, with significant contributions to nerve-sparing quantification and real-time feedback systems. The research consistently bridges computer vision, machine learning, and clinical surgical practice to develop predictive models for recovery metrics. Dr. Ng actively contributes to surgical consensus statements through organizations like the Society of Robotic Surgery, developing standardized frameworks for telesurgery implementation and surgical gesture analysis. His collaborative work spans engineering teams for AI tool development and clinical teams for surgical outcome validation, positioning him at the forefront of surgical technology translation.

• Hip and Knee Replacement
• Robotic-Assisted Surgery
• Computer-Assisted Navigation Technologies
• +3 more

Daniel A. Oakes, MD, is a Professor of Clinical Orthopaedic Surgery at the Keck School of Medicine of USC and serves as Director of the USC Joint Replacement Program. With expertise in knee and hip replacement/reconstruction, he pioneered robotic total knee surgery at Keck Medical Center in 2018 and focuses on computer-assisted navigation technologies, porous metal implants, and infection prevention. Harvard Medical School graduate Mayo Clinic fellowship (recipient of Mark B. Coventry Award) Dual expertise in clinical practice and translational research His research spans robotic surgery outcomes , implant longevity , and gene therapy for bone repair (notably AAV-based delivery systems). Publications from 2000-2025 reflect evolving priorities in joint replacement, including pandemic-era surgical trends and biofilm disruption technologies. Recognized as a Top Doctor by multiple organizations, he has received teaching excellence awards and served as Joint Replacement Fellowship Director. Current work emphasizes 3D-printed scaffolds , non-cemented stems , and metal artifact reduction MRI for prosthetic evaluation.

Mamoun T. MardiniView profile

Assistant Professor

• Data Science
• Wearables
• Health Informatics
• +3 more

Mamoun T. Mardini is an Assistant Professor at the Institute on Aging , University of Florida. His research focuses on leveraging data science, wearable technologies, and machine learning to address challenges in gerontology and healthcare. Education : Ph.D. Computer Science (2018), University of North Carolina M.S. Computer Engineering (2013), American University of Sharjah B.S. Computer Engineering (2009), Jordan University of Science and Technology Research Interests : Dr. Mardini’s work emphasizes: Development of AI-driven frailty assessment tools for surgical patients Applications of smart wearables for monitoring mobility and pain in older adults Machine learning models for predicting cardiovascular outcomes and disparities Analysis of social determinants of health using real-world data Key Contributions : His studies include: Pioneering work on reducing unnecessary TEE procedures using AI Development of the ROAMM smartwatch platform for ecological momentary assessment Investigations into racial disparities in healthcare outcomes using ML Awards : No awards explicitly mentioned in the provided data. Labs/Teams : Active in the Division of Epidemiology and Data Science in Gerontology (EDGE) .

Linus OhlssonView profile

Researcher

• Cardiovascular Medicine
• Medical Imaging
• Computed Tomography
• +3 more

Linus Ohlsson is a Research intern physician and PhD-student at Linköping University Hospital and Linköping University. He is affiliated with the Department of Health, Medicine and Caring Sciences (HMV), specifically within the Division of Diagnostics and Specialist Medicine (DISP) and the Unit of Cardiovascular Sciences. His primary research explores computed tomography and visualization techniques to better understand the heart during mechanical assisting pump therapy for advanced heart failure patients. He has also conducted significant research on medical education, particularly on revitalizing pedagogy in medical problem-based learning curricula and enhancing students' understanding of cardiac physiology through 4D visualization techniques. Ohlsson completed his medical degree (MD) from Linköping University in 2024 and has held various positions including Research intern Physician at Linköping University Hospital, Junior Physician at the Department of Cardiothoracic Surgery and Department of Clinical Physiology, and Chairman of the CMIV Research School. He served as a Visiting Scientist at the CT Clinical Innovation Centre at Mayo Clinic in 2024. His publications focus on echocardiographic hemodynamic monitoring in HeartMate 3 therapy, haemodynamic significance of extrinsic outflow graft stenoses, and educational approaches in medical training. His work has appeared in journals such as ESC Heart Failure, European Heart Journal, and Clinical Anatomy. Ohlsson is actively involved in the Network for Medical Image Science and Visualization (CMIV), the CMIV-Research School, the Cardiovascular Imaging and Modelling research cluster (CIM), and the Circulation and Metabolism research group (CircM), contributing to interdisciplinary research that bridges medical practice and technological innovation.

Dana KulicView profile

Professor

• Human-Robot Interaction
• Robot Learning
• Human Motion Analysis
• +3 more

Dana Kulic is a Professor in the Department of Electrical and Computer Systems Engineering at Monash University. She is also a Global Innovation Research Visiting Professor at the Tokyo University of Agriculture and Technology and the August-Wilhelm Scheer Visiting Professor at the Technical University of Munich. Her research focuses on developing autonomous systems for human-robot interaction (HRI), emphasizing safety, continuous learning from demonstrations, and rehabilitation technology. She co-founded the Adaptive Systems Lab at the University of Waterloo and co-led the NSERC Canadian Robotics Network. Her work addresses challenges in collaborative robotics, including safety quantification, non-expert learning, and rehabilitation applications. Projects include 'Natural Interaction Strategies for Long-Term Robot Use for Elderly Care' and 'Intelligent Robotics for Pharmaceutical Formulation Development.' Key research interests include human motion analysis, robot learning, and HRI. Recent studies explore auditory assistance for gait modification, contingent autonomy in uncertain environments, and multimodal communication for multi-robot systems. Her contributions align with UN Sustainable Development Goals, particularly in healthcare and innovation. Dr. Kulic has led multiple industry-collaborative grants, such as strategic projects in collaborative assembly and rehabilitation automation. She actively participates in interdisciplinary initiatives, including public engagement through events like 'Living with Robots' and media contributions on robotic limitations. Her laboratories, including the Waterloo Robohub, focus on advancing robotic capabilities through experimental methodologies and ethical frameworks. Current projects emphasize adaptive systems, shared autonomy, and robotic applications in healthcare and industrial settings.

Dema GovallaView profile

Visiting Assistant Professor

• Medical Devices
• Artificial Intelligence
• Sensor Design
• +2 more

Dr. Dema Govalla is a Visiting Assistant Professor in Electrical and Computer Engineering at University of Nevada, Las Vegas. Her research focuses on medical device development with expertise in haptic feedback systems for robotic surgery. Research areas include biosymbiotic interfaces, tactile feedback mechanisms for minimally invasive procedures, and AI-assisted surgical systems. Publications demonstrate consistent focus on improving human-machine interactions in medical contexts through sensor technology innovations. Expert areas include: Research and Development of Medical Devices, Integrated Circuit Design, Digital Signal Processing, Artificial Intelligence, Sensor Design, Human-robot Interaction and Python Development.

William R. TaylorView profile

Professor

• Biomechanics
• Musculoskeletal Engineering
• Orthopedics
• +7 more

Prof. Dr. William R. Taylor is a Professor of Movement Biomechanics at ETH Zürich's Department of Health Sciences and Technology, where he also serves as the Head of the Department and Deputy Head of the Institute for Biomechanics. His primary focus is on developing medical engineering concepts to assess musculoskeletal deficits and movement pathologies, with applications in clinical decision-making and targeted therapies. He has pioneered techniques such as the REFRAME approach for knee implant design evaluation and dynamic videofluoroscopy for joint analysis. William R. Taylor holds a Ph.D. in Biomedical Engineering from the University of Bath (1999). His academic journey includes postdoctoral research at the Biomechanics Research Lab, Prince of Wales Hospital, Sydney, Australia, and leadership roles at the Julius Wolff Institute, Charité – Universitätsmedizin Berlin (2001–2012). His research interests span biomechanics of aging, Parkinson’s disease gait analysis, spinal alignment in scoliosis, and wearable sensor technologies. He leads the Laboratory for Movement Biomechanics, which develops innovative solutions for musculoskeletal and neurological conditions, including wheelchair steering systems and fall prevention interventions for the elderly. Prof. Taylor has received prestigious awards, including the European Society of Biomechanics SM Perren Award (2022) and ISB Clinical Biomechanics Award (2021). His work has produced over 160 peer-reviewed journal contributions, emphasizing interdisciplinary collaboration between engineering, clinical neuroscience, and data science. Current projects include optimizing subthalamic nucleus DBS for Parkinson’s gait improvement, assessing stress-related low back pain in occupational settings, and validating spinal alignment models like ScolioSIM. He also explores the impact of electrode placement, sensor technologies, and machine learning in functional outcome predictions.

Jiwei ZhaoView profile

Associate Professor

• Semiparametric Statistics
• Missing Data Analysis
• Causal Inference
• +10 more

Jiwei Zhao is an Associate Professor at the University of Wisconsin-Madison, jointly appointed in the Department of Statistics (School of Computer, Data & Information Sciences) and the Department of Biostatistics & Medical Informatics (School of Medicine & Public Health). He leads the Zhao Research Group, focusing on statistical and machine learning methods for biomedical data analysis. His work is supported by multiple NIH and NSF grants, including an NIH R01 project on patient-reported outcomes in vocal fold paralysis and a Distinguished Research Fellows Program at UW-Madison. Dr. Zhao earned his PhD in Statistics from UW-Madison in 2012 under Dr. Jun Shao. Prior to his current position, he was a Postdoctoral Researcher at Yale University (2012-2013) and held Assistant and Associate Professor roles at SUNY Buffalo (2014-2020). His academic leadership includes serving as Associate Editor for journals like the Annals of Applied Statistics and Scandinavian Journal of Statistics , and as Area Chair for AISTATS (2024-2025). His research interests span semiparametric methodologies, missing data analysis, causal inference, and domain adaptation. Key applications include patient-reported outcomes, electronic health records, clinical trials, and studies on aging, mental health, and cancer. His group collaborates with institutions like the Data Science Institute, Institute on Aging, and Center for Demography of Health and Aging. Recent work emphasizes efficient parameter estimation under privacy constraints, robust learning in nonignorable missing data scenarios, and leveraging machine learning for medical imaging and genetic studies. He actively recruits researchers across postdocs, PhD, and undergraduate levels to join his team.