Find Academic Supervisors

• Artificial Intelligence
• Health Informatics
• Knowledge Graphs
• +4 more

Prof. Zhisheng Huang is a Visiting Professor at the Faculty of Science, Vrije Universiteit Amsterdam. His research focuses on AI-driven solutions for healthcare challenges, particularly leveraging knowledge graphs for mental health analysis, biomedical informatics, and social media monitoring. He actively contributes to UN Sustainable Development Goals related to health and well-being (SDG 3). Key Research Areas: Knowledge graphs for dietary nutrition and disease analysis Suicide risk detection via social media (e.g., "Tree Hole" project) Medical Q&A systems for geriatric diseases AI applications in mental health diagnostics His work integrates ontology engineering, machine learning, and big data analytics to address complex health issues. Notable projects include the KG4NH knowledge graph and hypertension early warning systems. Collaborations span international institutions, focusing on interdisciplinary health informatics solutions. Recent Focus: Exploring microbiota-gut-brain axis relationships, depression etiology, and family dynamics in postpartum mental health. His research bridges computational methods with clinical practice to improve healthcare outcomes.

• Medical Robotics
• Biomechanical Modeling
• Medical Imaging
• +3 more

Ferdinand van der Heijden is an Associate Professor in Robotics and Mechatronics, specializing in medical robotics and surgical navigation. He holds an external researcher position at Antoni Van Leeuwenhoek Hospital since 2014. His work integrates robotics, biomedical engineering, and artificial intelligence to address challenges in surgical precision, diagnostic imaging, and patient outcomes. Research focuses include developing advanced imaging techniques for pleural diseases, improving laparoscopic camera accuracy, and leveraging AI for medical diagnostics. He has contributed to over 160 publications, with recent emphasis on pleural plaque quantification, crowd-sourced deep learning for hemorrhage detection, and personalized surgical models. He has supervised 11 academic works, though specific student names are not listed. His collaborations span global institutions, addressing topics like diabetic foot thermography and prostate intervention robotics. Notable projects include the MIRIAM robot for MR-guided needle interventions and biomechanical tongue modeling for post-surgery functional prediction. Key contributions include innovations in image-guided surgery tools, AI-driven diagnostic frameworks, and 3D visualization techniques for surgical planning. His work aligns with UN Sustainable Development Goals related to health and well-being (SDG 3).

Winston ChongView profile

Academic

• Interventional Neuroradiology
• Machine Learning
• Artificial Intelligence
• +5 more

Winston Chong is an Adjunct Clinical Professor at the Department of Neuroscience , Monash University . His research focuses on Interventional Neuroradiology , Artificial Intelligence , Machine Learning , and Neurovascular Diseases . He leads projects such as "The Holy Grail: Non-thrombogenic intravascular stents" and "Bringing personalized aneurysm rupture predictions to the patient" , emphasizing precision medicine and medical device innovation. His work spans clinical applications like adrenal vein sampling for primary aldosteronism and deep learning models for aneurysm diagnosis. He collaborates internationally and has published extensively on cerebral aneurysm rupture risk, stroke intervention protocols, and hemodynamic analysis. Chong is actively involved in training guidelines for endovascular stroke interventions and advancing AI-driven diagnostic tools in neurology. Current projects include optimizing tertiary care for primary aldosteronism diagnosis and developing thrombosis-resistant vascular stents. He accepts PhD students focusing on improving MS diagnosis via machine learning.

Bethany ContrerasView profile

Assistant Professor

• Applied Behavior Analysis
• Autism Spectrum Disorders
• Skill Acquisition
• +5 more

Bethany Contreras is an Assistant Professor in the Department of Psychology at the University of Nevada, Reno (UNR), within the College of Science. She holds a PhD in Disability Disciplines (Applied Behavior Analysis) from Utah State University (2017) and a postdoctoral fellowship at the University of Missouri. Her expertise spans behavioral interventions for neurodevelopmental disabilities, particularly autism spectrum disorders, focusing on skill acquisition, response variability, and parent/teacher training. Education: B.S. Biology, Arizona State University, 2008 M.S. Applied Behavior Analysis & Organizational Behavior Management, Florida Institute of Technology, 2012 PhD Disability Disciplines (Emphasis in ABA), Utah State University, 2017 Research focuses on optimizing behavioral interventions for children with autism, including reinforced variability in problem-solving, efficient skill acquisition methods, and promoting independent language/play skills. She also studies effective instruction techniques in higher education. Certified as a Board Certified Behavior Analyst at the Doctoral level (BCBA-D). Her work emphasizes practical applications, such as training paraprofessionals and parents via technology-aided methods. Recent research explores cultural competency in ABA service delivery and ethical frameworks in behavior analysis.

• 3D Graphics
• Computer Vision
• Perceptual Quality Assessment
• +5 more

Fakhri Torkhani is affiliated with the University of La Rochelle, specifically the Department of Information Systems and Technology (ISIT) within the College of Science and Technology. His research focuses on perceptual quality assessment of 3D meshes, including static and dynamic models, and the development of objective metrics for evaluating geometric distortions. He has presented work on perceptual selection of optimal viewpoints for 3D textured scenes, published at the 15th IAPR International Workshop on Document Analysis Systems (DAS 2022). Active in academic events, he has participated in conferences such as CICLing 2019, CORIA-RJCRI 2024, and multiple editions of the Science Festival. He is also involved in interdisciplinary initiatives like the CircularSeas project and the MIRES Federation. His contributions span lab seminars, doctoral thesis defenses, and educational outreach activities, including interventions at high schools and workshops on digital humanities. He has contributed to projects like NewsEye (winner of CLEF-HIPE-2020) and collaborated in events related to AI4Industry, software preservation, and advanced networks. His work bridges computational methods with perceptual analysis in 3D modeling and multimedia applications.

Vitaly SchetininView profile

Senior Lecturer

• Computational Intelligence
• Machine Learning
• Statistical Analysis
• +5 more

Dr Vitaly Schetinin is a Senior Lecturer in Computing and Information Systems at the University of Bedfordshire's School of Computer Science and Technology. He holds a PhD in Computer Science (Computational Intelligence) from 1997 and has held post-doctoral roles at the Universities of Jena (Germany) and Exeter before joining Bedfordshire in 2005. Research: His work spans Computational Intelligence, Machine Learning, Bayesian Modelling, and applications in medical informatics, risk assessment, and pattern recognition. Notable projects include Bayesian models for trauma survival prediction and EEG-based newborn brain maturity assessment funded by the Leverhulme Trust and EPSRC. Teaching: He teaches modules in Computational Intelligence, Data Mining, Robotics, and Statistics across undergraduate and postgraduate programs. He actively supervises research projects at all academic levels. Grants: Awarded £82,500 from the Leverhulme Trust (2009–2012) for newborn brain maturity research and EPSRC funding for radio wave propagation studies (2008–2009). Publications: Over 50 peer-reviewed articles focus on machine learning applications in healthcare, finance, and engineering. Recent work includes adaptive Bayesian learning frameworks and deep learning for medical imaging. Professional Engagement: Reviews for IEEE journals (Pattern Analysis, Neural Networks, Biomedical Engineering) and serves on technical committees for international conferences including IEA-AIE and KES.

• Creative Technologies
• Games User Research
• Ergogenic Aids
• +6 more

Dr. Pooya Soltani is a Senior Lecturer at Staffordshire University's Digital, Tech, Innovation & Business School. His research bridges game technology with healthcare, sports performance, and human behavior analysis. He holds a PhD in Sports Sciences (Biomechanics and Human Energetics) from the University of Porto, and MSc/BSc degrees from Shiraz University. Key research areas include mixed reality technologies' impact on human behavior, VR applications in rehabilitation, and exergaming for diabetes management. He has secured significant grants, including Marie Skłodowska-Curie Actions (2018) and Collège de France Postdoctoral Funding (2018-2019). Teaching focuses on serious games, military game design, and project management. His work has been featured in BBC, Bloomberg, and Daily Mail, emphasizing public engagement in technology-driven health solutions. Professional highlights include: Designed VR-based training programs for motor control and deception analysis Developed exergame policies adopted by the Brazilian Society of Diabetes Conducted workshops on tech integration for SMEs and creative enterprises Recipient of Whatuni Student Choice Awards 2023 for Facilities & Social Inclusion Current roles include academic leadership, operational management, and enterprise activities, alongside ongoing research in hyper-realistic avatars and their behavioral impacts.

Vinhthuy PhanView profile

Associate Professor

• Computer Science Education
• Bioinformatics
• Data Science
• +3 more

Dr. Vinhthuy Phan is an Associate Professor and Associate Chair of the Department of Computer Science at the University of Memphis, where he has been since 2003. He earned a PhD in Computer Science from Stony Brook University and a Bachelor's in Mathematics and Computer Science from Brandeis University. His research focuses on computer science education, bioinformatics, and data science. He develops active-learning tools such as Code4Brownies and GEM to enhance teaching and learning in programming and data science. His work in bioinformatics includes computational methods for analyzing genomic data, while his data science research applies machine learning to education and healthcare contexts. Dr. Phan also explores financial aid optimization strategies to improve access to higher education. Education: PhD, Computer Science, Stony Brook University, 2003 Bachelor's, Mathematics and Computer Science, Brandeis University Research Interests: Dr. Phan's interdisciplinary work bridges computer science education and bioinformatics. In education, he designs strategies for personalized instruction using active learning and in-class exercises. In bioinformatics, he develops methods to analyze sequencing data and bacterial identification. His data science efforts integrate machine learning into both fields. He has created platforms like icHET for visualizing genomic data and tools for peer feedback in introductory courses. Publications: His recent work highlights trends in active learning, computational methods for microbiome analysis, and educational policy. Key themes include improving student performance through in-class interventions, optimizing financial aid systems, and advancing genomic sequence analysis techniques. Grants & Labs: Dr. Phan's research is supported by grants focused on educational innovation and bioinformatics. He leads projects involving student teams in developing educational technologies and bioinformatics tools. His lab collaborates on initiatives like MetaBIDx for microbiome research and financial aid optimization frameworks.

• Public Health
• Epidemiology
• Health Services Research
• +4 more

Hoang Van Minh is an Adjunct Associate Professor at UMass Chan Medical School with a focus on Population and Quantitative Health Sciences, Division of Epidemiology. He is affiliated with the Hanoi University of Public Health and has contributed extensively to tobacco control, public health policy, and epidemiological studies in Vietnam. Education: MD from Hanoi Medical University, MPH and PhD from Umeå International School of Public Health, Sweden. Research Interests: Public Health, Epidemiology, Tobacco Control, Health Systems, Non-communicable Diseases (NCDs), Health Policy, and Social Determinants of Health. His work spans smoking cessation, salt consumption trends, dengue prediction models, and health equity in minority populations. Article Trends: His publications from 2003–2025 emphasize public health interventions in Vietnam, with key themes in tobacco policy, NCDs, environmental health, and health systems research. Recent work includes machine learning applications for disease forecasting and pandemic impact assessments. Networks: Collaborates with institutions like T.H. Chan School of Medicine and engages in policy-relevant research. His work has been cited in PubMed Central and discussed in social media, reflecting its public health impact.

Michael WanView profile

Researcher

• Computer Vision
• Infant Health Monitoring
• Medical Image Analysis
• +2 more

Dr. Michael Wan is a Research Scientist at Northeastern University's Institute for Experiential AI (Roux Institute), specializing in computer vision and machine learning applications for infant health. His research includes video-based infant sleep-wake classification, respiration estimation, and early detection of torticollis via postural symmetry analysis. He holds a PhD in Mathematical Logic from UC Berkeley and previously led computer vision teams in the Augmented Cognition Lab. Current projects focus on non-invasive monitoring of neurodevelopmental cues, including non-nutritive sucking patterns and crib safety enhancement through hazard detection algorithms. His work emphasizes scalable, equitable AI solutions for pediatric healthcare.

Atiyeh VaezipourView profile

Research Fellow

• Human-Computer Interaction
• Digital Health
• Virtual Reality in Rehabilitation
• +3 more

Dr. Atiyeh Vaezipour holds an honorary research fellow appointment at the RECOVER Injury Research Centre, University of Queensland, and works as a human factors researcher at Google Maps for Automotive. She earned a PhD in Human-Computer Interaction from Queensland University of Technology. Her research focuses on innovative technology solutions in two core areas: driving behavior safety and digital health interventions using virtual reality in rehabilitation. Her expertise spans mobile health applications, wearable devices for disability support, and telemedicine feasibility studies. Key research interests include: Design of in-vehicle HMIs for eco-safe driving VR-based psychological therapy for driving anxiety and phobia Mobility solutions for visually impaired populations Health technology evaluation methodologies Recent work highlights include: Analysis of driving behavior in functional neurological disorder patients Systematic reviews on conversational AI in healthcare and wearable navigation systems Feasibility studies for telerehabilitation programs Current affiliations include: RECOVER Injury Research Centre Google Maps for Automotive Her research contributes to advancing: Safety-critical transportation systems Digital health innovation adoption Accessibility technologies

• Neuro-Engineering
• Brain-Computer Interfaces
• Cognitive Neuroscience
• +5 more

Dr. Jia Liu is a Research Fellow at the Centre for Biomedical Sensing and Informatics , affiliated with the School of Biomedical Engineering at the University of Sydney . As a member of the University of Sydney Nano Institute , her work bridges neuro-engineering, brain-computer interfaces, and physiological signal analysis. Research Fellow, School of Biomedical Engineering, University of Sydney Member, University of Sydney Nano Institute Research Interests: Cognitive Enhancement through physiological signal analysis Advanced Brain-Computer Interface (BCI) development Neuro-Engineering applications in real-world scenarios Mobile Brain/Body Imaging (MoBI) system design Human orientation skills and therapeutic interventions Cognitive workload and physical fatigue interplay Publication Trends: Recent work focuses on graph neural networks for drowsiness detection, ERP-based inattentional blindness classification, and virtual global landmakr applications in spatial learning. Her methods integrate MoBI systems, VR, and real-time signal processing. Scientific Contributions: Published in prestigious journals (Nature Group, IEEE Transactions) Pioneering work on cognitive workload assessment using optical tomography Developed parameter-sharing neural networks for human state estimation Erratum corrections demonstrating rigorous research methodology Laboratory Affiliation: Works within the Centre for Biomedical Sensing and Informatics , leveraging interdisciplinary approaches to translate neuro-engineering research into practical applications.

• Political Communication
• Computational Methods
• Digital Propaganda
• +2 more

Dr Aliaksandr Herasimenka is a political communication scholar at the Oxford Internet Institute, University of Oxford. As a Research Fellow with the Oxford Martin Programme on Misinformation, Science, and Media, he investigates how political groups and governments use AI and social media for campaigning and public opinion manipulation. His research examines: Digital propaganda and communication in authoritarian states Computational methods for tracking narrative circulation Organizational impacts of digital technologies on political campaigning Crisis-related misinformation during events like the Ukraine war Dr Herasimenka teaches social data science, journalism, and digital research methods across multiple institutions including University of Oxford and University of Westminster.

• Public Health
• Epidemiology
• Health Education
• +3 more

Dr. Nayani Rajapaksha is a Visiting Research Student at the School of Public Health, University of Queensland. Her research focuses on public health, epidemiology, and disaster management in Sri Lankan contexts, with a strong emphasis on dengue prevention, mHealth applications, and pandemic modeling. Fields of Interest: Public Health, Epidemiology, mHealth, Disaster Management, Health Education, Infectious Disease Prevention Email: r.rajapaksha@uq.edu.au Her work spans epidemiological modeling (SEIR/SEIRD models for dengue and COVID-19), disaster resilience in healthcare systems , and mHealth interventions for maternal nutrition and community health. She collaborates extensively with researchers in Sri Lanka and Australia, addressing policy implementation and behavioral change strategies. Article trends highlight her expertise in computational disease modeling, community-based dengue prevention, and health system adaptation during pandemics. Key subfields include vector-borne disease control , public health policy , and digital health communication .

Yesenia Aponte-MeléndezView profile

Researcher

• Sociology
• Public Health
• Substance Abuse
• +5 more

Yesenia Aponte-Meléndez is a Researcher at the Institute for Society, Psychology, and Health (ISPH), affiliated with The New School for Social Research . Her work bridges sociology and public health, focusing on technology-delivered interventions for substance use disorders and infectious disease prevention among people who inject drugs. Co-founded El Punto en la Montaña, a syringe exchange program in Puerto Rico Conducts qualitative and clinical research on HIV/Hepatitis C syndemics and harm reduction Specializes in migrant Puerto Rican health disparities in NYC and Puerto Rico Her research explores the intersection of social class , gender , and prescription opioid misuse , combining mixed-methods approaches with policy-oriented outcomes. Recent work addresses xylazine-fentanyl overdoses and healthcare cost barriers in syringe service programs. Publications demonstrate a longitudinal focus on digital health solutions in methadone maintenance treatment and behavioral therapy for substance use disorders. Key sub-fields include harm reduction infrastructure, syndemic theory, and stigma mitigation in medical systems.