Find Academic Supervisors

Laurens Debo is the C.V. Starr Professor of Operations Management and Area Chair in the Operations and Management Science Department at Tuck School of Business, Dartmouth College. He holds a PhD (2002) and MSc (2000) from INSEAD, France, and dual MSc degrees in Operations Management (1995) and Electrical Engineering (1994) from Université Catholique de Louvain, Belgium. Prior to Tuck, he taught at Carnegie Mellon University and the University of Chicago Booth School of Business. Research Interests: Debo specializes in service operations, strategic consumer behavior, and discretionary service management. His work explores how consumer decisions shape service demand and how providers optimize service delivery in contexts where value increases with service duration. Recent focus areas include queueing systems, tipping behavior, and pandemic-era retail operations. Awards & Editorial Roles: He received the MSOM Meritorious Service Award (2008, 2010) and served as associate editor for Management Science , Manufacturing & Service Operations Management , and Operations Research . He currently edits Production and Operations Management and advises the IIE Transactions . Grants & Impact: NSF-funded research has informed his work on discretionary service design and retail safety protocols during pandemics. His tipping behavior studies have been featured in WSJ , Harvard Business Review , and Marketplace . Labs & Collaborations: Collaborates with global institutions like MIT, Stanford, and the Chinese Academy of Sciences on behavioral operations projects. Active in presenting at leading business schools including Wharton, Kellogg, and INSEAD.

• Operations Management
• Supply Chain Management
• Operations Strategy
• +5 more

Andrew B. Nobel is the Robert Paul Ziff Distinguished Professor of Statistics and Operations Research and Professor of Biostatistics at the University of North Carolina at Chapel Hill (UNC). He holds affiliations with the Lineberger Comprehensive Cancer Center and the Computational Genomics Program. His research focuses on statistical genomics, machine learning, network analysis, and inference from dynamical systems. Nobel has collaborated extensively with researchers in Biology, Computer Science, Genetics, and Mathematics. Dr. Nobel earned his PhD in Electrical Engineering from Stanford University (1992), an MS from Stanford (1988), a Certificate of Study in Mathematics from Cambridge University (1986), and a BS in Electrical Engineering from Cornell University (1985). He has taught courses ranging from undergraduate discrete mathematics to advanced graduate-level theoretical statistics and machine learning. His research interests include developing methodologies for analyzing complex biological and network data, with applications to cancer genomics, systems biology, and medical informatics. Recent work emphasizes optimal transport methods for network analysis and statistical approaches for genomic data integration. Awards: Elected Fellow of the Institute of Mathematical Statistics (2008) National Science Foundation CAREER Grant (1995) Beckman Institute Fellow (1992–1995) Churchill Scholar (1985–1986) Dr. Nobel serves on the editorial board of the Journal of the Royal Statistical Society, Series B and has previously contributed to the Annals of Statistics and IEEE Transactions on Information Theory . His work bridges theoretical statistical foundations with practical applications in public health and biomedical research.

• Statistical Genomics
• Machine Learning
• Network Analysis
• +3 more

Ron Z. Goetzel, PhD, MA, is a Senior Scientist and Director of the Institute for Health and Productivity Studies (IHPS) at the Johns Hopkins Bloomberg School of Public Health. His work bridges academia, business, and healthcare policy to advance health and productivity management (HPM), return-on-investment (ROI), and workplace wellness programs. Previously, he held faculty positions at Emory and Cornell Universities. Education: PhD (1982), MA (1975), and BS (1972) from New York University and City College of New York. Research Interests : Workplace health promotion, ROI of wellness programs, health risks, applied social psychology, and prevention strategies. His work emphasizes translating research into actionable policies and programs for employers and healthcare systems. Recent Article Trends : Focus on pandemic impacts on worker mental health, workplace stress management, and tools like the CDC Worksite Health ScoreCard. His studies explore how organizational practices and policies influence health outcomes and business performance. Awards : Woodward Lecture Award (2002) Award for Excellence in Value Purchasing (2008) Mark Dundon Research Award (2011) Editor’s Choice Article, American Journal of Health Promotion (2019) Leadership & Grants : Directs IHPS, leading projects funded by CDC, World Bank, IMF, and RWJF. Projects include developing mental health strategies, health accountability dashboards, and evidence-based wellness programs. Labs/Teams : Oversees IHPS, a collaborative hub for health-productivity research, and contributes to initiatives like the CDC’s Worksite Health ScoreCard and the WHO’s Total Worker Health® programs.

• Workplace Health Promotion
• Health Economics
• Health Risk Management
• +3 more

Garth V. Crosby is an Associate Professor at Texas A&M University's Department of Engineering Technology and Industrial Distribution within the College of Engineering. He is also affiliated with the Multidisciplinary Engineering program. His research focuses on IoT and IIoT security, cyber-physical systems, and STEM education innovation. Crosby holds a Ph.D. in Electrical Engineering from Florida International University (2007), an M.S. in Computer Engineering, and a B.S. in Electronics (Applied Physics) from the University of the West Indies. His work spans cybersecurity frameworks for emerging technologies, including blockchain-based federated learning, post-quantum cryptography, and IoT threat mitigation. He has contributed to educational advancements through online lab design and faculty efficacy studies in hybrid learning environments. Crosby's recent publications emphasize securing robotic IoT systems, supply chain blockchain applications, and ransomware evasion techniques using generative AI. His research portfolio includes over 40 peer-reviewed articles in journals like IEEE Transactions and conferences such as ASEE and FiCloud. Key themes include volunteer cloud reliability models (ProTrust), edge computing security, and educational technology evaluation. Crosby's interdisciplinary approach bridges engineering systems with pedagogical innovation, addressing both technical and human factors in modern technological challenges.

• Internet of Things (IoT)
• Industrial Internet of Things (IIoT)
• Cyber-physical Systems Security
• +5 more

Peter Kedron is an Associate Professor in the Department of Geography at the University of California, Santa Barbara (UCSB), and a member of the Center for Spatial Data Science. Previously, he held faculty positions at Arizona State University (2018–2023), Oklahoma State University (2016–2018), and Ryerson University (2012–2016). He earned his Ph.D. in Geography from SUNY Buffalo, an MA in Economics from the University of Michigan, and BAs in Economics and Psychology from SUNY Buffalo. His research focuses on spatial analytical methods, particularly replication in geographic research, and improving evidence accumulation through statistical approaches. Key areas include computational reproducibility, spatial causal inference, and the integration of replication into GIScience education. He has published over 55 peer-reviewed articles and been consistently funded by the National Science Foundation (NSF). Dr. Kedron emphasizes bridging spatial data science with policy relevance, addressing challenges in urban inequality, environmental conservation, and healthcare accessibility. His work often employs cutting-edge techniques like digital twins, machine learning, and multi-source remote sensing to address complex spatial problems. He has supervised over 20 graduate students and post-doctoral scholars, fostering a collaborative environment. Notable contributions include frameworks for reproducible geospatial research and studies on urban-rural disparities, wildfire risk, and renewable energy sector dynamics. Labs/Teams: Active in UCSB’s Center for Spatial Data Science and collaborates with interdisciplinary teams on projects funded by NSF and industry partnerships.

• Spatial Analysis
• Economic Geography
• GIScience
• +3 more

Robin Murphy is the Raytheon Professor of Computer Science and Engineering at Texas A&M University, affiliated with the College of Engineering. She holds dual Fellowships from IEEE and ACM. Her research focuses on disaster robotics, human-robot interaction, and emergency informatics. She leads the Humanitarian Robotics and AI Laboratory (formerly CRASAR), a nonprofit deploying robots in disasters since 1995. Key contributions include pioneering rescue robotics, developing standards for field robotics, and advancing AI for emergency response. Education: PhD, M.S., and B.M.E. in Computer Science from Georgia Institute of Technology (1992, 1989, 1980). Awards include Fast Company's Most Influential Women (2011), AUVSI Al Aube Award, and TIME's Innovators in AI. She has participated in over 27 disaster responses, including 9/11, Hurricane Katrina, and the Fukushima nuclear crisis. Current projects include marine robotics for mass casualty events and ethical frameworks for responsible robotics. Research emphasizes field-deployable systems, human-robot teaming, and heterogeneous robotics. Notable work includes the 'Survivor Buddy' robot for trapped victims and UAV-UAV cooperation for structural inspection. Grants include NSF, DOE, and industry partnerships. Labs: Humanitarian Robotics and AI Lab, Roboticists Without Borders.

• Artificial Intelligence
• Disaster Robotics
• Human-Robot Interaction
• +5 more

Dr. Hannah Carter is a Professor of Medicine at the University of California San Diego (UCSD), affiliated with the School of Medicine and the Department of Biomedical Informatics. She specializes in computational modeling of tumor genomics, focusing on how DNA mutations influence cellular processes and cancer development. Her research integrates high-dimensional genomic data to identify cancer drivers and improve precision medicine approaches. Education: MEng in Electrical and Computer Engineering (University of Louisville, 2004), PhD in Biomedical Engineering (Johns Hopkins University, 2012). Research interests include cancer genomics, bioinformatics tool development, and the application of network approaches to oncology. Key projects include NIH-funded studies on tumor mutation stratification and immune surveillance disruption in cancer. Publications span computational methods for variant analysis (e.g., CHASM toolkit) and mechanistic studies linking genomic changes to cellular behavior. Her work has been recognized through awards like the NIH Early Independence Award (2013) and the Azrieli Global Scholar distinction (2017). Labs and affiliations include the Division of Biomedical Informatics and Division of Medical Genetics at UCSD. She leads collaborative initiatives on genomic variation impacts in pancreatic beta cells and cancer-immune interactions.

• Computational Biology
• Cancer Genetics
• Genomics
• +3 more

Mary S Feldman, DO, is an Associate Professor of Neurology at the Geisel School of Medicine, Dartmouth College. She holds leadership roles as Director of the Neurology Residency Program at Dartmouth-Hitchcock and Co-Director of the Movement Disorders Center and Parkinson's Disease Center of Excellence. Her research focuses on Parkinson's disease, telemedicine applications in neurological therapy, and rare neurological disorders. She has contributed to studies on deep brain stimulation optimization, machine learning in disease characterization, and pharmacological interventions for Parkinson's-related symptoms. Her work bridges clinical practice and innovation, including randomized controlled trials evaluating treatments for movement disorders and constipation management. She also engages in medical education research, particularly in assessment methodologies for workplace learning. Feldman's publications span topics from neurodegenerative mechanisms to clinical trial outcomes, reflecting her dual expertise in patient care and translational research. She actively collaborates with institutions like Dartmouth-Hitchcock Medical Center and affiliated hospitals, contributing to multidisciplinary efforts in neurology and medical education.

• Parkinson's Disease
• Neurology
• Movement Disorders
• +4 more

Dr. Kuo-Ting (Tim) Huang is an Assistant Professor at the University of Pittsburgh’s School of Computing and Information. His research focuses on digital/health inequalities and community-based technology interventions targeting marginalized groups, with a focus on immersive technologies like VR/AR to address health disparities. He holds a PhD in Media and Information from Michigan State University. Dr. Huang’s work examines how emerging digital divides exacerbate health literacy gaps and explores solutions using technologies such as virtual reality. He emphasizes designing interventions to improve health outcomes for vulnerable populations, including older adults and racial minorities. His contact information includes timhuang@pitt.edu and an office at Room 616 in the Information Sciences Building. His research portfolio spans topics like telehealth adoption, AI literacy, and social media’s role in mental health. While no formal awards are listed, his work consistently addresses critical issues in health equity and technology access. Dr. Huang’s advising and grants are not explicitly detailed here, though his projects likely involve collaborations with healthcare and community organizations. He is affiliated with the School of Computing and Information’s broader initiatives in technology for social good.

• Digital Inequalities
• Health Inequalities
• Community-Based Technology Interventions
• +3 more

Agata Rozga is a Principal Research Scientist at the Georgia Institute of Technology's School of Interactive Computing, specializing in computational behavioral science. She leads translational research for the NSF-funded AI-CARING Institute, focusing on AI technologies to support aging in place. Additionally, she directs the Technology Core of Emory’s Cognitive Empowerment Program, integrating sensors and AI into care networks for individuals with Mild Cognitive Impairment (MCI). Her work bridges computing and psychology to develop tools for behavioral monitoring in autism and neurological conditions. Dr. Rozga’s research has been funded by NSF, NIH, and the Simons Foundation. Key areas include longitudinal analysis of communication behaviors in autism, particularly language development, and AI-driven systems for cognitive decline monitoring. She previously served as Head of Product at Diligent Robotics, optimizing service robots for clinical settings, and collaborated with Behavior Imaging to advance telehealth autism diagnostics. Her academic affiliations include the GVU Center at Georgia Tech, emphasizing human-centered computing. Awards and grants include NSF and NIH funding for projects addressing autism and MCI. She actively deploys health technologies in real-world settings, combining quantitative and qualitative methods to assess impacts on patients and caregivers.

• Computational Behavioral Science
• Machine Learning
• Developmental Health
• +4 more

Dr. Yongqun He is a Professor at the University of Michigan Medical School with primary affiliation in the Unit for Laboratory Animal Medicine (ULAM) and joint appointments in the Department of Learning Health Sciences and Department of Microbiology and Immunology. He holds affiliations with the Rogel Cancer Center, MIDAS, and other institutions. He earned his D.V.M. from Jiangxi Agricultural University (China) and Ph.D. in Biomedical and Veterinary Sciences from Virginia Tech (USA). His research focuses on computational medicine, ontology development, vaccinology, and microbiology. He pioneered Vaccine Informatics, developed tools like VO, Ontobee, and Ontofox, and contributed to Kidney Precision Medicine through ontologies like KTAO. He has mentored numerous students and serves on NIH review panels, international conferences, and advisory boards. His work includes over 300 publications, with recent topics on ontology-based vaccine design, AI applications, and kidney disease modeling. Education: D.V.M. (1991), M.S. Veterinary Medicine (1996), Ph.D. Biomedical Sciences (2000) from China Agricultural University and Virginia Tech. Research: Integrates AI, ontology, and bioinformatics to study vaccines, pathogens, and kidney diseases. Services: NIH grant reviewer, organizer of international ontology workshops (VDOS, CELLS), and editorial board member for journals like Frontiers in Cellular and Infection Microbiology .

• Computational Medicine
• Bioinformatics
• Ontology Development
• +8 more

Dr. Heejun Kim is an Assistant Professor at the University of North Texas. He holds a Ph.D. from the University of North Carolina at Chapel Hill, an M.S. from the University of Illinois Urbana-Champaign, and a B.S. from Yonsei University. His research focuses on Text Mining, Machine Learning, Information Retrieval, Health Informatics, and Geographic Information Science. His work bridges computational methods with societal challenges, particularly in public health and social media analysis. Key research interests include analyzing health information credibility on social media, pandemic-related social dynamics, and designing sociotechnical systems for underprivileged communities. Dr. Kim’s recent studies investigate racial discrimination discourse on platforms like YouTube, mental health support mechanisms among college students, and the impact of information literacy on health decisions. His publications reflect a focus on pandemic-era social behaviors, digital health communication, and algorithmic solutions for biomedical literature analysis. Notable works include studies on anti-Asian hate speech during the pandemic and the role of social networks in Black American college students’ connections.

• Text Mining
• Machine Learning
• Information Retrieval
• +2 more

Yea-Jen Hsu is an Associate Research Professor in the Department of Health Policy and Management at the Johns Hopkins Bloomberg School of Public Health. She is actively engaged in health services research with a focus on patient safety, quality improvement, and implementation science. Education: PhD, Johns Hopkins Bloomberg School of Public Health, 2011 MHA, National Yang-Ming University, 2003 BS, National Taiwan University, 2001 Dr. Hsu’s research centers on program evaluation and the application of implementation science to improve healthcare delivery. Her work emphasizes enhancing patient safety culture, reducing healthcare-associated infections, and developing innovative models such as integrating buprenorphine into primary care. She employs rigorous quantitative methods to assess interventions and identify success factors. Her recent publications (2024–2025) reflect a strong focus on patient engagement in pain management, hypertension disparities, infection risk modeling, and electronic health record analytics. These works span high-impact journals in medical quality, internal medicine, and infection control, demonstrating interdisciplinary collaboration and relevance to real-world healthcare systems. Scientific Awards: No awards mentioned in the provided text. Dr. Hsu collaborates extensively with national programs such as the CDC’s Prevention Epicenters and contributes to multi-level interventions aimed at systemic healthcare improvements. While no specific grants or advising roles are listed, her leadership in survey development, data evaluation, and collaborative research indicates active involvement in funded projects. She is not affiliated with a named lab or research team, but her network includes key figures in patient safety and health policy at Johns Hopkins and beyond.

• Health Services Research
• Program Evaluation
• Patient Safety
• +7 more

Thejal Srikumar, MD , is an Assistant Professor of Medicine in the Department of Medical Oncology and Hematology at Yale School of Medicine. She practices at Smilow Cancer Hospital and Yale Cancer Center in New Haven, specializing in gastrointestinal cancers, particularly in young adults and those with genetic predispositions. She is also affiliated with the Center for Gastrointestinal Cancers, the Early Onset Cancer Program, and the Smilow Cancer Genetics & Prevention Program. Education: MD from University of South Florida Morsani College of Medicine; Executive MPH from Yale School of Public Health (Epidemiology & Health Informatics); Residency and Fellowship in Internal Medicine and Hematology/Oncology at Yale, where she served as Chief Resident and Chief Fellow. Her research focuses on gastrointestinal malignancies, early-onset cancers, and the intersection of cancer, obesity, and imaging biomarkers. She has published on topics including CT-based staging, visceral adiposity, and multimodal treatment for gastric cancer. Her work often involves interdisciplinary collaboration with colleagues in surgery, radiology, and public health. Recent publications highlight her dual commitment to clinical oncology and medical education. She has led initiatives on communication skills training, pharmacology curriculum development, and longitudinal wellness programs for hematology/oncology fellows, reflecting her role as Assistant Program Director of the fellowship program. Scientific Awards: No specific awards listed in the provided text. Dr. Srikumar is actively involved in mentoring and teaching, supervising fellows in clinical and didactic settings. She contributes to curriculum development and professional development initiatives. Her work bridges clinical care, research, and education, with a strong emphasis on improving outcomes for high-risk cancer populations and enhancing training for future oncologists. Labs and Teams: She collaborates with the Breast Medical Oncology Group and other oncology research teams at Yale, though she does not lead a standalone lab. Her work is embedded within the clinical and educational infrastructure of the Hematology/Oncology division.

• Medical Oncology
• Hematology
• Gastrointestinal Cancers
• +6 more

David S. Wack is an Associate Professor at the University at Buffalo's Jacobs School of Medicine & Biomedical Sciences, Department of Radiology. His research focuses on medical image analysis and neuroimaging, particularly in auditory processing and parameter estimation from PET, MRI, and CT images. He has held academic positions since 1992, progressing from instructor roles to his current rank. His work includes NIH-funded projects on imaging technologies and collaborations with institutions like Canon Medical Systems and UBNS. Education: PhD in Communicative Disorders and Sciences (SUNY Buffalo, 2010) MA in Applied Mathematics (SUNY Buffalo, 1992) BA in Applied Mathematics and Music Performance (SUNY Buffalo, 1989) Research Interests: Development of parametric maps from medical images Machine learning applications in neuroimaging Neuroimaging of auditory and language processing Dynamic image noise reduction and segmentation algorithms Neural markers of top-down compensation in speech processing Recent Projects: NIH-funded self-collimating SPECT breast tomography system 4D flow MRI for intracranial atherosclerotic disease assessment Machine learning for neuroimage classification Grants & Service: Member of Jacobs School faculty council and UB Faculty Student Association board Editorial roles at Frontiers in Neuroscience (Brain Imaging Methods, Decision Neuroscience) Labs & Teams: Buffalo Neuroimaging Analysis Center Collaborations with UBNS, Canon Medical, and VA Western New York Health Care System

• Artificial Intelligence
• Biomedical Engineering
• Brain Research
• +5 more