Find Academic Supervisors

• Biomedical Image Processing
• Medical Image Analysis
• Bioimaging Sciences
• +4 more

James Duncan is the Ebenezer K. Hunt Professor of Radiology and Biomedical Engineering, and Professor of Biomedical Engineering at Yale University's School of Medicine. He leads the Department of Biomedical Engineering as Department Chair and holds joint appointments in Diagnostic Radiology and Electrical Engineering. His research focuses on biomedical image processing, model-based image analysis, and medical imaging technologies. Notably, he pioneered techniques for anatomical object segmentation using Bayesian strategies and deformable motion tracking in cardiac imaging. Education: PhD from University of Southern California (1982), MS from UCLA (1975), BSEE from Lafayette College (1973). Research interests include medical image segmentation, motion tracking, image-guided surgery, and AI-driven medical imaging solutions. His team developed foundational methods for MRI/SPECT analysis and cardiac biomechanics modeling. Over 176 publications demonstrate his expertise in machine learning applications for healthcare, with recent work in domain adaptation, diffusion models, and low-dose imaging techniques. Awards include IEEE Fellow (2000), NIH BRP grants, and multiple R01 grants. His lab collaborates widely, advancing translational imaging technologies and interdisciplinary engineering-medicine initiatives. Major grants include sustained NIH funding since 1993. He mentors interdisciplinary teams and chairs the Yale Biomedical Imaging Institute. Current projects address AI in diagnostic imaging, cancer immunotherapy monitoring, and personalized cardiac modeling.

• Cardiology
• Cardiovascular Disease Prevention
• Electrophysiology
• +4 more

Dr. Aravinda Thiagalingam serves as a Senior Lecturer at the Westmead Clinical School of the University of Sydney and is a Principal Investigator at the Westmead Applied Research Centre. His clinical specialty is Cardiology, with extensive research focused on cardiovascular disease prevention and management through innovative digital health approaches. Dr. Thiagalingam's research interests primarily center around cardiovascular disease prevention, particularly through mobile health interventions and digital technologies. His work demonstrates a strong emphasis on text messaging programs for cardiovascular disease management, atrial fibrillation treatment, diabetes care, and hypertension monitoring. He has pioneered research in ECG-gated retinal vessel analysis as a novel cardiovascular risk assessment tool and has explored clinician-developed applications to improve adherence to evidence-based guidelines. His publications reveal a consistent focus on leveraging technology to enhance patient outcomes in high-risk cardiovascular populations. Analysis of his recent publications shows a clear trajectory toward integrating artificial intelligence and machine learning into cardiovascular risk prediction and patient management. His work spans clinical trials of digital interventions, systematic reviews of emerging technologies, and novel applications of existing medical devices. The research demonstrates particular strength in mobile health applications for chronic disease management, with significant contributions to understanding how digital tools can improve medication adherence, patient education, and self-monitoring in cardiovascular care. Dr. Thiagalingam has supervised research students including Shehane Mahendran, whose project focuses on cardiovascular disease prevention in high-risk populations. His collaborative network is extensive, frequently working with researchers like Chow C, Kovoor P, and Thiagalingam A on various cardiovascular research initiatives. His work has been supported by numerous research grants focused on digital health interventions for cardiovascular disease management. As Principal Investigator at the Westmead Applied Research Centre, Dr. Thiagalingam leads a research team focused on developing and evaluating innovative approaches to cardiovascular disease prevention and management. His laboratory work includes testing novel medical devices, developing digital health applications, and conducting clinical studies to evaluate the effectiveness of technology-based interventions in real-world settings.

Ina GanguliView profile

Professor

• Labor Economics
• Economics of Science and Innovation
• Immigration Policy
• +3 more

Ina Ganguli is a Professor of Economics at the University of Massachusetts Amherst and Director of the UMass Computational Social Science Institute. She holds affiliations with multiple prestigious institutions including the National Bureau of Economic Research (NBER), Institute of Labor Economics (IZA), and the Laboratory for Innovation Science at Harvard University. Her research focuses on labor economics, the economics of science and innovation, immigration policy, and gender disparities in labor markets. Ganguli earned her PhD from Harvard University, MPP from the University of Michigan, and BA from Northwestern University. She has held roles as a Fulbright Scholar in Ukraine and a U.S. Embassy Policy Specialist in Russia, Azerbaijan, and Tajikistan. Notable awards include the Russian National Prize in Applied Economics (2018) and honorable mention for the Upjohn Dissertation Award. Her research explores topics such as scientific collaboration dynamics, gender career trajectories in global law firms, and the impact of migration on knowledge transfer. Recent work examines the effects of historical immigration policies, pandemic-driven skill acquisition, and the consequences of war on scientific infrastructure in Ukraine. Key contributions include analyzing patent interference data to trace knowledge spillovers and studying how grant competitions influence social entrepreneurship. She has co-authored influential papers on the mobility of elite scientists and the role of cognitive similarity in fostering innovation through collaboration. Awards: Russian National Prize (2018), Upjohn Honorable Mention Labs/Teams: Leads UMass Computational Social Science Institute, affiliated with Harvard's LISH and J-PAL Grants: Research supported by NBER, IZA, and IFP

Sachin JogView profile

Research Fellow

• Process Modeling
• Optimization
• Sustainable Chemical Processes
• +3 more

Dr. Sachin Jog is a researcher at ETH Zürich, affiliated with the Department of Chemistry and Applied Biosciences and working within the Professorship for Chemical Systems Engineering. His research focuses on sustainable process systems engineering, with particular emphasis on developing innovative modeling and optimization techniques for chemical processes. His educational background includes: Doctoral Degree from ETH Zürich (2021-2025) under Prof. Gonzalo Guillén Gosálbez Master of Science in Process Engineering from ETH Zürich (2019-2021) Bachelor of Chemical Engineering from Institute of Chemical Technology (ICT), Mumbai (2015-2019) Dr. Jog's research interests span several critical areas in modern chemical engineering: Hybrid modeling techniques combining first-principles and data-driven approaches Optimization of integrated chemical clusters with heat, mass, and power integration Accounting for renewable energy intermittency in chemical process design Multi-objective optimization considering both economic and environmental metrics Sustainable process design aligned with Sustainable Development Goals (SDGs) His recent publications demonstrate a strong progression from fundamental modeling approaches to their application in specific sustainable chemical processes like methanol production from CO2. His work consistently bridges traditional chemical engineering with modern sustainability requirements, showing how renewable carbon technologies can be designed for true sustainability rather than focusing solely on climate change mitigation. Dr. Jog's scientific contributions include: Development of hybrid modeling methodologies for process optimization Frameworks for sustainable process design incorporating SDGs Optimization approaches for integrated chemical clusters using renewable energy His research is supported by the Swiss National Science Foundation (SNF) through the 'Bayesian symbolic learning to aid in the design of sustainable chemical clusters (LEARN-D)' project. Dr. Jog works within the Chemical Systems Engineering group at ETH Zürich, contributing to research on sustainable chemical processes and systems engineering approaches for the chemical industry's decarbonization.

Ioanna LykourentzouView profile

Associate Professor

• Collaborative Systems
• Crowd Systems
• Machine Learning
• +5 more

Ioanna Lykourentzou is an Associate Professor at Utrecht University, leading the Collaborative Technologies Lab and coordinating Computing Science Master's and Information Sciences Honors Bachelor's programs. She holds a PhD and ECE degree from the National Technical University of Athens. Her research focuses on collaborative systems, combining computational science (machine learning, optimization) with social sciences (team dynamics, personality assessment). Education background includes a PhD and ECE degree from National Technical University of Athens. She has held postdoctoral and visiting roles at Carnegie Mellon University, INRIA Nancy-Grand Est, and Henri Tudor. Research interests span computational team formation, Human-AI collaboration, and cultural heritage accessibility. Recent work includes projects on GenAI in education (NWO Take-off grant), algorithmic team formation for game development (EU MSCA funding), and ethical AI frameworks. Active in open science initiatives as an Open Software Fellow and Ethics Review Board member. Key collaborations include MIT-Netherlands Seed Fund projects on Human-AI design, and interdisciplinary work in digital humanities through Utrecht's AI in Cultural Inquiry SIG. Her lab hosts researchers like Pedro Zambon (MSCA fellow) and Heleen Kerstholt (AI-enabled teamwork).

• Cognitive Science
• Virtual Reality
• Pediatrics
• +5 more

Veronica Weser, PhD, is a Research Scientist in General Pediatrics at Yale School of Medicine and a member of the Center for Immersive Technologies. She holds a PhD in Cognitive Psychology from the University of Virginia, with postdoctoral training in VR applications. Her work focuses on leveraging virtual reality (VR) and gaming technologies to address public health challenges, particularly in adolescent health and pediatric care. Education: PhD in Psychology, University of Virginia (2018) MA in Psychology, University of Virginia (2016) BA in Cognitive Science, Vassar College (2012) Research Interests: Dr. Weser specializes in applying VR to create impactful health interventions. Key areas include: E-cigarette prevention through immersive gaming HIV/STI prevention for Black adolescent girls Support systems for adolescents with cancer Neonatal infection control strategies Publications: Her 15+ peer-reviewed articles span VR navigation optimization, tool embodiment theories, and health behavior interventions. Recent work includes evaluating VR-based support groups for cancer patients and analyzing barriers to infection prevention in neonatal units. Awards: 2019 Oculus Launch Pad Award for VR game development 2013 Fulbright Fellowship for dyslexia research in Japan Advising & Grants: Active in interdisciplinary teams, she collaborates with clinicians, educators, and technologists. Current projects include NIH-funded studies on multiplayer health games and VR infection prevention training for NICU staff. Labs & Teams: Based at the XR Pediatrics lab, she leads development of health-focused VR applications. Collaborates with the Yale Center for Immersive Technologies to advance translational research.

Lara Perez-FelknerView profile

Professor

• Educational Equity
• STEM Education Policy
• Sociology of Education
• +3 more

Dr. Lara Perez-Felkner is a Professor of Higher Education and Sociology at Florida State University (FSU) within the College of Education, Health, and Human Sciences. She holds affiliations with the Department of Sociology and the Center for Postsecondary Success. Her work focuses on mechanisms shaping access and persistence in underrepresented fields, particularly in STEM education and postsecondary pathways for marginalized groups. Education: Ph.D. and M.A. from the University of Chicago; B.A. from Wesleyan University. Leadership Roles: Co-Team Lead for AAAS SEA Change, Director of FSU’s NSF ADVANCE team (INCREASE), and former Co-Chair of the Latin* Faculty and Staff Collective. Research Interests: Dr. Perez-Felkner examines racial-ethnic, gender, and socioeconomic disparities in higher education, with a focus on STEM equity. Her work integrates developmental and sociological perspectives to propose systemic interventions. Key themes include institutional policies, mentorship, and curricular reforms to support underrepresented students. Publications highlight interventions to reduce gender gaps in computing and engineering, the role of community colleges in STEM degree attainment, and policy briefs advocating for equitable STEM pathways. Her work has been featured in Review of Educational Research , International Journal of STEM Education , and Science News for Students . Awards: Includes FSU’s Transformation through Teaching Award (2014), multiple Hardee Center Mentor Awards, and recognition as a SERN Mid-Career Fellow. Grants: Supported by NSF, Gates Foundation, Spencer Foundation, and others. Teaching & Mentoring: Courses include Sociology of Education and Student Development Theory. She has mentored dozens of students in collaborative research, emphasizing inclusive pedagogy and institutional change.

Zoey Zhiyu ChenView profile

Assistant Professor

• Artificial Intelligence
• Natural Language Processing
• Healthcare Technology
• +3 more

Zoey Zhiyu Chen is an Assistant Professor in the Department of Computer Science at the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas. Her research focuses on advancing artificial intelligence, particularly in natural language processing (NLP), healthcare technology, financial technology, and dialogue systems. She explores the application of large language models (LLMs) in critical domains such as mental health therapy, cognitive behavior therapy (CBT), and finance, emphasizing robustness and ethical considerations. Key research areas include hypothesis discovery, rule learning, patient simulation for mental health training, and improving medical predictions through multimodal data analysis. Her work also addresses challenges in retrieval-augmented models, agentic search optimization, and zero-shot dialogue state tracking. Chen’s contributions span theoretical advancements in AI reasoning and practical applications in societal domains like law and healthcare. Her articles highlight trends in leveraging LLMs for clinical support, financial analysis, and improving human-AI interaction through preference learning and function calling mechanisms. She advocates for responsible AI development, as seen in studies on energy efficiency benchmarks (Hulk) and domain-specific robustness (RobustFin).

Mohammad Amin MoridView profile

Assistant Professor

• Healthcare Informatics
• Machine Learning
• Predictive Analytics
• +4 more

Dr. Mohammad Amin Morid serves as an Assistant Professor in the Department of Information Systems and Analytics at Santa Clara University's Leavey School of Business since 2018, teaching undergraduate and master's level Information Systems courses while maintaining active research collaborations with healthcare and financial institutions. His academic foundation includes a Ph.D. in Information Systems from the University of Utah (2018), complemented by an M.S. in Electronic Commerce and B.S. in Software Engineering from Amirkabir University of Technology (Tehran Polytechnic). Dr. Morid's research program centers on healthcare predictive analytics through machine learning , with specialized expertise in temporal patient data analysis from electronic health records and medical claims. His interdisciplinary work bridges biomedical informatics and information systems, extending to fraud detection in banking and personalized recommender systems, demonstrating methodological versatility while maintaining healthcare as his primary application domain. Analysis of his recent publications reveals dominant trends in deep learning for medical time series, cost prediction, and medical image analysis—particularly in orthopedics—with strong representation in premier venues like the Journal of Biomedical Informatics and AMIA conferences. His work consistently addresses real-world clinical and operational challenges through sophisticated data modeling. Through applied projects with hospitals, insurers, and banks, Dr. Morid translates theoretical research into practical healthcare analytics solutions. While specific grant mechanisms aren't detailed in public sources, his sustained industry partnerships indicate successful project acquisition and implementation capacity across the healthcare-finance analytics spectrum.

Simrita SinghView profile

Assistant Professor

• Healthcare Operations
• Data-Driven Optimization
• Artificial Intelligence in Healthcare
• +7 more

Simrita Singh is an Assistant Professor in the Department of Information Systems & Analytics at Leavey School of Business. Her research integrates cutting-edge technology, data-driven analytics (e.g., deep learning), and traditional optimization techniques to enhance cost efficiency and access in service systems, with a focus on healthcare and retail operations. Education: B.Tech in Electronics and Communication Engineering from Indian Institute of Technology, Roorkee; M.S. and Ph.D. in Operations Management from The Kellogg School of Management, Northwestern University. Her work explores innovations like computer-aided triage (CADt), clinical decision support systems (CDSS), big data analytics on healthcare claims, digital twins, and personalized connected care. Publications appear in top journals such as PLOS Medicine , Nature Scientific Reports , and BMJ Open , with ongoing reviews in leading management journals. Recent articles highlight her focus on AI integration in healthcare pathways (2024), priority queuing for clinical workflows (2024), Medicaid service access (2022), differential diagnosis modeling (2022), and simulation studies on tuberculosis diagnosis in India (2020, 2019). Her prior experience includes roles as a business analyst at JP Morgan and an independent consultant for Indian educational institutes.

Mohammad MiralinaghiView profile

Assistant Professor

• Smart Cities
• Connected and Automated Vehicles
• Electric Vehicles
• +5 more

Mohammad Miralinaghi is an Assistant Professor in the Civil, Architectural, and Environmental Engineering Department at Illinois Institute of Technology (Illinois Tech), part of the Armour College of Engineering. His research focuses on smart cities, connected/automated vehicles, electric vehicles, and sustainable transportation systems. He holds a Ph.D. from Purdue University, an M.S. in Transportation Systems Engineering from the University of Alabama, and two M.S. and a B.S. from Sharif University of Technology. His expertise includes transportation infrastructure design, tradable credit schemes, and congestion pricing. Recent work explores AI-driven solutions for autonomous vehicle decision-making (XAI), robust design of electric vehicle charging networks, and reinforcement learning for infrastructure scheduling. He has published widely in journals such as Transportation Research Part D , European Journal of Operational Research , and Computer-Aided Civil and Infrastructure Engineering . Key projects include optimizing project scheduling to minimize user/business impacts and designing frameworks for electric vehicle adoption. His research addresses emerging technologies like CAVs (connected and automated vehicles), emphasizing equity, resiliency, and sustainability in urban systems.

• Stroke Medicine
• Neurointerventional Radiology
• Endovascular Therapy
• +4 more

Pieter Jan van Doormaal is a Researcher in the Department of Radiology & Nuclear Medicine at Erasmus MC, a leading medical center in the Netherlands. His work focuses on advanced imaging techniques and endovascular treatments for stroke patients, with particular expertise in cerebral angiography and thrombectomy procedures. Dr. van Doormaal's research interests center on improving outcomes for acute ischemic stroke patients through innovative endovascular therapies. His work spans neurointerventional radiology , medical imaging analysis , and stroke treatment optimization . He investigates the relationship between procedural techniques and patient outcomes using metrics like the Modified Rankin Scale, with special attention to large vessel occlusions and brain ischemia mechanisms. His recent publications demonstrate a strong trend toward integrating advanced computational methods with clinical stroke care. Several studies focus on AI-assisted decision making for endovascular therapy, cost-effectiveness analyses of stroke treatment systems, and technical innovations in cerebral angiography. His work appears in high-impact journals including The Lancet, reflecting significant contributions to the field of interventional neuroradiology. Dr. van Doormaal actively collaborates with major international stroke research networks as evidenced by his participation in the ESCAPE-NEXT multicenter trial. His research output shows substantial external interest, with multiple publications being picked up by news outlets and discussed on academic social media platforms.

Jerker BjörkqvistView profile

Professor

• Sustainable Computing
• Energy-Efficient Algorithms
• Artificial Intelligence
• +12 more

Jerker Björkqvist is a Professor in the Department of Information Technology at Åbo Akademi University, Faculty of Natural Sciences and Technology. His research focuses on sustainable computing, energy-efficient algorithms, and data-driven green transitions in industrial and marine contexts. He leads key projects such as DAZE, WSTAR, and CASEMATE, contributing significantly to zero-emission technologies. His research interests span Sustainable Computing , Energy-Efficient Algorithms for AI , Edge Computing , Marine Technology , and Industrial Sustainability . His work integrates computer science with environmental engineering to support the UN’s Sustainable Development Goals, especially in climate action and responsible innovation. The recent publications reflect a strong trend in applying data analytics and optimization techniques to reduce emissions in maritime and industrial systems. Key themes include digital twins, ultra-reliable communication, and maturity models for sustainability, showing an interdisciplinary blend of computer science, engineering, and environmental science. Jerker Björkqvist actively supervises Master’s students and contributes to academic service through organizing seminars and delivering keynote speeches. He is involved in educational initiatives such as capstone projects and engineering education reform, particularly focusing on the role of AI in practice. He is a principal investigator in multiple externally funded projects including: DAZE (Data Analytics for Zero Emission Marine) – Business Finland WSTAR (Wasa Zero Emission Data Centre) – Academy of Finland CASEMATE – Business Finland FAST – Finnish Software Engineering Doctoral Network These projects involve collaboration with industry and academic partners across Finland. He is associated with research teams and labs focused on sustainable computing and digital transformation, including the WSTAR research group and the DAZE consortium. These teams work on real-world implementations of green IT and marine decarbonization technologies.

• Radiomics
• Artificial Intelligence in Radiology
• Medical Imaging
• +7 more

Jan-Jaap Visser is a researcher in the Department of Radiology & Nuclear Medicine at Erasmus MC, Rotterdam, Netherlands. He is actively contributing to the advancement of medical imaging through research in radiomics, artificial intelligence, and diagnostic imaging technologies. His research interests center on the application of artificial intelligence in radiology, with a focus on radiomics, MRI, CT imaging, and computer-aided diagnosis systems. He explores how AI can improve diagnostic accuracy, support clinical decision-making, and enhance patient understanding of radiological findings. Recent publications highlight his work in deep learning for brain metastasis analysis, GPT-4 for patient comprehension of radiology reports, AI in musculoskeletal tumor imaging, radiomics practice guidelines, and validation of commercial CAD systems for lung nodule detection. These works reflect a strong trend toward integrating AI into clinical radiology workflows with attention to validation and standardization. No scientific awards were mentioned in the provided text. Jan-Jaap Visser has supervised academic work, as indicated by the 'Supervised Work (2)' tag, though specific student names are not listed. He collaborates extensively with researchers across institutions and contributes to national and international initiatives in radiological informatics. There is no mention of specific grants, but his publication output suggests active research funding. He is involved in research networks related to radiomics and AI in imaging, likely participating in collaborative teams focused on medical image analysis and informatics at Erasmus MC.

Maria Helenowska-PeschkeView profile

Associate Professor

• Architectural Design
• Parametric Modelling
• Digital Fabrication
• +3 more

Dr. Maria Helenowska-Peschke is an Associate Professor at the Department of Visual Arts, Faculty of Architecture, Gdańsk University of Technology. Her research focuses on parametric design, digital fabrication, and the integration of technology in architectural education. She holds a PhD in arts studies (1999) and a habilitation in engineering (2018). Her work explores the impact of digital tools on architectural practice, including energy modeling for sustainable housing and blended learning methodologies. Notable publications include analyses of parametric design trends, energy-efficient housing, and digital workshop innovations. She leads projects like the 'Parametric-Algorithmic Paradigm in Architecture' funded by MNiSW grants. Teaching focuses on computer techniques and hybrid educational models. Contact: mhelen@pg.edu.pl, Office: Gmach Główny - room 353.