Find Academic Supervisors

Carl ThompsonView profile

Professor

• Clinical Decision Making and Judgement
• Implementation Science
• Mixed Methods Evaluation
• +4 more

Professor Carl Thompson is a leading academic in applied health research at the University of Leeds' School of Healthcare within the Faculty of Medicine and Health. His roles include being a registered nurse with extensive NHS experience, from nursing assistant to NHS Trust non-executive director. Previously, he held a personal chair in health sciences at the University of York. His expertise spans clinical decision making, implementation science, and evidence-based healthcare. Research focuses include care home quality improvement, wearable technology applications, and computerised decision support systems. Notable projects include the £2m CONTACT study on Bluetooth wearables for contact tracing in care homes and the STaRQ study examining nurse staffing impacts on care quality. He collaborates internationally with institutions in Australia, the Netherlands, Canada, and the US. Education: DPhil in Social Policy (University of York, 1996), BSc Hons in Social Policy (1st class, 1993), RN qualification (York College of Nursing, 1989). Grants: Secured or collaborated on £20m+ projects from NIHR, MRC, and ESRC. Teaching: Covers medical informatics, decision making, and leadership in healthcare education. Awards: No specific awards listed, though his extensive funding and leadership roles reflect professional recognition. Leadership: Former Director of Research in the School of Healthcare and Pro Dean for Applied Health Research. His research emphasizes 'how people use information in clinical practice and policy making,' with a focus on translating evidence into practice. He advises on national funding panels (NIHR HSDR, Irish Health Research Board) and mentors PhD students in decision science and implementation research. Current initiatives include the Nurturing Innovation in Care Homes (NiCHE Leeds) collaboration and membership in the NIHR Yorkshire and Humber CLAHRC's Improvement Science theme. He actively supports implementation science through visiting professorships at the Universities of Alberta and East Anglia.

Sundaresan JayaramanView profile

Professor

• Smart Textile-based Wearable Systems
• Computer-aided Manufacturing
• Engineering Design
• +8 more

Dr. Sundaresan Jayaraman is a Professor at the School of Materials Science and Engineering, Georgia Institute of Technology, and Founding Director of the Kolon Center for Lifestyle Innovation. His research focuses on converging textiles with computing, notably pioneering the concept of 'Fabric is the Computer.' Key contributions include the Smart Shirt (Wearable Motherboard™), featured in LIFE Magazine and archived at the Smithsonian. He has secured $16M+ in research funding from NSF, DARPA, and industry. His work spans smart textiles, respiratory protection systems, and computer-aided manufacturing. Awards include the 1989 Presidential Young Investigator Award and the 2018 Textile Institute Research Publication Award. He holds ten U.S. patents and serves on editorial and advisory boards for journals like the Journal of the Textile Institute. Professional roles include leadership in National Academies committees on manufacturing and personal protective equipment. Education & Early Career: Dr. Jayaraman’s career began at Software Arts, Inc. (developers of VisiCalc) and Lotus Development Corporation, where he contributed to early spreadsheet and equation-solving software. His PhD research led to TK!Solver, a pioneering equation-solving program. Research Interests: His work bridges engineering and healthcare through smart textiles, wearable biomedical systems, and advanced manufacturing. Current projects address respiratory protection systems, wearable sensor networks, and personalized healthcare technologies. He emphasizes interdisciplinary collaboration to address societal challenges in health, security, and quality of life. Publications & Impact: Over 100 refereed papers and book chapters highlight his contributions to textile informatics, healthcare wearables, and manufacturing automation. Recent articles focus on next-generation respiratory protection devices and continuous fit monitoring systems. Past innovations include the Wearable Motherboard™ and sensor-integrated garments for vital signs monitoring. Awards & Recognition: In addition to his NSF and Textile Institute honors, he received the Georgia Technology Research Leader Award (2000) and Distinguished Alumni Award from A.C. College of Technology (2019). He is a Fellow of the Textile Institute and founding member of IEEE Technical Committees on Biomedical Wearables. Labs & Teams: Leads the Kolon Center for Lifestyle Innovation and collaborates with industry partners on textile-based computing solutions. His lab’s work on 3D-printed respiratory devices and smart garments exemplifies cutting-edge translational research.

Luis NovoaView profile

Associate Professor

• Business Analysis
• Management Science
• Supply Chain Management
• +3 more

Luis Novoa is an Associate Professor in the Department of Computer Information Systems and Business Analytics at James Madison University’s College of Business, where he also contributes to the MBA program. His academic journey includes a Ph.D. in Decision Sciences from The George Washington University (2016), an M.S. and B.S. in Industrial Engineering from Universidad de los Andes (2007 and 2005, respectively). He has held roles such as Assistant Professor at JMU since 2017, Visiting Assistant Professor at The George Washington University (2016–2017), and Instructor at Universidad de los Andes (2007–2011). His research focuses on business analysis, management science, and applied decision analysis under uncertainty, particularly in supply chain management, logistics, education, and healthcare. Notable work includes optimizing automated package sorting systems, developing educational tools like STRATA for operations research assessment, and Bayesian methods for academic motivation analysis in business analytics courses. Recent articles highlight contributions to bike-sharing system decision-making, supply chain curriculum alignment with industry practices, and stochastic optimization in energy systems. His awards include JMU College of Business Distinguished Teacher (2021–2022) and recognition for summer research excellence (2011). Dr. Novoa’s teaching and research emphasize practical applications of analytics, bridging academic theory with real-world challenges in business and public sectors. He has authored or co-authored over 15 peer-reviewed publications spanning operations research, education, and industry case studies.

• Artificial Intelligence
• Recommender Systems
• Information Systems
• +2 more

Dietmar Jannach is a Full Professor at the University of Klagenfurt, Austria, affiliated with the Institute for Artificial Intelligence and Cybersecurity where he leads the Research Group for Information Systems. His academic roles include membership in the university's Senate and Curricular Commissions for Liberal Arts and Information Management. His research spans: Core Areas : Artificial Intelligence, Recommender Systems, and Software Engineering. Methodological Focus : Algorithm reproducibility, fairness in AI, sequential recommendations, and hybrid learning models. Emerging Interests : Generative AI for group decision support, ethical recommender systems, and foundation model applications. Jannach's recent publications critically evaluate reproducibility challenges in AI research, advocate for calibrated recommendations to mitigate bias, and explore agentic paradigms in group recommender systems. He emphasizes real-world validation, with studies on deployment challenges and developer experiences in software processes. He actively contributes to academic governance and mentors through research groups, though specific student advisees are not listed. Contact via Dietmar.Jannach@aau.at .

• Business Analytics
• Operations Research
• Machine Learning
• +5 more

Dr. Hong Ming Tan is a Senior Lecturer at the Department of Analytics and Operations, NUS Business School, and a Research Fellow at the Institute of Operations Research and Analytics (IORA) at National University of Singapore. He holds a PhD in Operations Research and Analytics (2021), MSc in Mathematics (2017), and BSc (Hons) in Applied Mathematics and Economics (2013) from NUS. Doctor of Philosophy, Operations Research and Analytics (2021) Master of Science, Mathematics (2017) Bachelor of Science (Hons), Applied Mathematics and Economics (2013) His research spans Business Analytics , Machine Learning , Operations Research , and Pharmacogenetics . Recent work includes: EcoVal Framework for efficient data valuation in ML Personalized Mental Health through adaptive testing and clustering Antibiotic Resistance modeling using antiresistic strategies CYP2D6 Methylation prediction for precision medicine His publications demonstrate expertise in ML optimization , healthcare informatics , behavioral analytics , and decision science . Current projects include AI-led Smart Data Centre Management and SIA Corp Lab research. He serves as Chair of the Department Finance Committee and advisor to student clubs like Business Analytics Consulting Team. His work addresses real-world challenges in industrial operations, healthcare diagnostics, and educational innovation.

• Database Systems
• Query Optimization
• Index Tuning
• +7 more

Surajit Chaudhuri is a Researcher at Microsoft , with a career spanning decades in database systems and data management . He has received the prestigious SIGMOD Edgar F. Codd Innovations Award (2011) for his contributions to query optimization , index tuning , and data lakes . Research Interests : His work focuses on database tuning , approximate query processing , fuzzy similarity joins , automated data transformations , and machine learning integration for scalable data systems. Recent Publications : In 2025, his research includes Auto-Test for unsupervised error detection in tables, Esc for budget-aware index tuning, and MMTU for multi-task table understanding benchmarks. Earlier works in 2024–2023 address spreadsheet formula recommendation , low-overhead index filtering , and time-series pattern recognition . Scientific Impact : He has co-authored influential papers in SIGMOD , VLDB , and IEEE Transactions , shaping practices in cloud databases , query optimization , and self-service BI . His collaborations span institutions like Microsoft, MIT, and ETH Zurich.

Ahmad FakheriView profile

Professor

• Heat Transfer
• Fluid Mechanics
• Thermodynamics
• +3 more

Ahmad Fakheri is Professor of Mechanical Engineering at Bradley University’s Caterpillar College of Engineering & Technology . He has served the university for more than two decades, including as Interim Associate Provost & Dean of the Graduate School (1996-1998) and Director for Research & Sponsored Programs (1992-1996). A triple alumnus of the University of Illinois at Urbana-Champaign (B.S., M.S., Ph.D., all in Mechanical Engineering), he is an ASME Fellow recognized for exceptional research and service. Education Ph.D., Mechanical Engineering, University of Illinois at Urbana-Champaign M.S., Mechanical Engineering, University of Illinois at Urbana-Champaign B.S., Mechanical Engineering, University of Illinois at Urbana-Champaign Research Interests Dr. Fakheri’s scholarship lies at the intersection of heat transfer , fluid mechanics and thermodynamics , with concentrated effort on heat-exchanger design and optimization . His work employs second-law analysis, entropy-generation minimization and advanced numerical techniques to enhance thermal efficiency and guide sustainable energy-system development. Scientific Awards & Honors Fellow, American Society of Mechanical Engineers (ASME) Outstanding Research Award, Bradley College of Engineering Outstanding Service Award, ASME Process Industries Division NASA Summer Faculty Fellow, NASA Lewis Research Center Caterpillar Fellows Program Research Award Leadership & Service Within ASME he has chaired the Process Industries Division (6,000+ members) and the Manufacturing Technical Group (10,000+ members), served on the Board on Research and Technology Development, and acted as Technical Program Chair for the 2012 ASME International Mechanical Engineering Congress. On campus he has been a member of the University Senate and has led curriculum-reform initiatives. Laboratory & Teaching Dr. Fakheri teaches undergraduate and graduate courses such as Heat Transfer , Advanced Heat Transfer , Advanced Fluid Dynamics and Advanced Computer-Aided Design , integrating computational tools and real-world design projects that connect classroom theory to industrial practice.

Hanan SametView profile

Professor

• Spatial Data Structures
• Geographic Information Systems (GIS)
• Computer Vision
• +3 more

Hanan Samet is a Distinguished University Professor in the Computer Science Department at the University of Maryland, College Park. He holds affiliations with the Center for Automation Research and the Institute for Advanced Computer Studies (UMIACS). His academic journey includes a PhD from Stanford University (1975) in Computer Science, following degrees in Engineering (UCLA) and Operations Research/Computer Science (Stanford). Affiliations: University of Maryland, College Park (since 1975) Roles: Professor, Founding Editor-in-Chief of ACM Transactions on Spatial Algorithms and Systems, Founder of ACM SIGSPATIAL Samet's research focuses on spatial data structures, spatial databases, GIS, computer vision, and information retrieval. His seminal work includes the Foundations of Multidimensional and Metric Data Structures , an award-winning book addressing spatial indexing and query optimization. He pioneered frameworks like NewsStand for map-based news exploration and Coronaviz for pandemic visualization. Key contributions span spatial synonyms for approximate search, SAND spatial browser for digital government, and trajectory analysis systems for aviation safety and urban mobility. His work bridges theory and practice, influencing databases, graphics, and geographic systems. Education: B.S. Engineering, UCLA M.S. Operations Research, Stanford M.S./Ph.D. Computer Science, Stanford Samet has advised numerous students and led NSF-funded projects on spatio-textual data, similarity search, and spreadsheet analysis. His honors include the ACM Paris Kanellakis Award (2011), IEEE Wallace McDowell Award (2014), and UCGIS Research Award (2009). His labs and teams focus on spatial algorithms, visualization, and GIS applications. Notable projects include VASCO (spatial index demo), MARCO (image databases), and CHOLERA (disease tracking).

Tony StockmanView profile

Senior Lecturer

• Human-Computer Interaction
• Auditory Displays
• Data Sonification
• +3 more

Dr. Tony Stockman is a Senior Lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science. His teaching focuses on Database Systems, Interaction Design, and Semi-structured Data Modelling across undergraduate and postgraduate programs. His research interests include Human-Computer Interaction, Auditory Displays, and Data Sonification, with a strong emphasis on accessibility and cross-modal interfaces. Dr. Stockman has contributed to over 100 publications, exploring topics such as biofeedback systems, assistive technologies for visually impaired individuals, and collaborative design methodologies. His work frequently bridges technical innovation with user-centric design principles. Notable projects include the development of non-visual navigation tools like the Audiom web-based map viewer and co-designed haptic wearables for music synchronization. His research also addresses challenges in education technology, such as dyslexia screening through serious games.

Peter SestoftView profile

Professor

• Programming Languages
• Software Development
• Parallel Programming
• +4 more

Peter Sestoft is a Professor at the IT University of Copenhagen (ITU), leading the Computer Science Department since 2017. His primary roles include academic leadership, research in programming languages and software engineering, and teaching. He holds a PhD in Computer Science from the University of Copenhagen (1991) and has held academic positions at institutions like the Royal Veterinary and Agricultural University and the Technical University of Denmark before joining ITU in 1999. His research focuses on programming languages, functional and managed object-oriented languages, parallel programming, compilers, and spreadsheet implementation technologies. He has developed influential tools like the C5 Generic Collection Library for C# and Moscow ML, a Standard ML implementation. His work on Funcalc and Corecalc advanced spreadsheet technology with user-defined functions and efficient recalculation algorithms. Key contributions include over 30 publications, including books on programming language concepts and Java/C# syntax. He has led major research projects such as 'Popular Parallel Programming' (P3) and 'Probabli' for actuarial calculations. His academic service includes roles on national grant committees and international conference organizing committees. Notable advising includes PhD students like Andrzej Wasowski (ITU Professor) and David Christiansen (Director of Haskell Foundation). His work has been recognized through grants exceeding 25 million DKK and collaborations with institutions like Microsoft Research and Harvard University.

Anna FarihaView profile

Assistant Professor

• Data Management
• Human-Centered Systems
• Usability Engineering
• +4 more

Anna Fariha is an Assistant Professor in the Kahlert School of Computing at the University of Utah. She co-leads the Data Management Research Center for Human-centered, Efficient, and Scalable Systems. Her research focuses on enhancing data system usability, explainability, and trustworthiness through algorithmic innovations and practical implementations. She holds a Ph.D. from the Manning College of Information and Computer Sciences at the University of Massachusetts, Amherst, under Prof. Alexandra Meliou. Education: Ph.D. in Computer Science, University of Massachusetts Amherst (2021) Master's in Computer Science, University of Massachusetts Amherst (2020) Undergraduate work in Computer Science, unspecified institution Her research interests include data wrangling tools, constraint discovery, conversational AI for data science, and human-centered database systems. Recent work emphasizes automated data summary recommendations, constraint violation detection, and educational tools for data science programming. Grants & Awards: NSF CIRC: ENS/Grand: POWDER-ENS Award (2024) Stena Center Seed Grant for Fintech Data Analysis (2025) Microsoft Research Dissertation Grant (2020) SIGMOD 2022 Comprehensive Reproducibility Award Teaching: Recently taught Advanced Database Systems , Human-Centric Data Management , and Deep Learning courses at the University of Utah.

Michael CoblenzView profile

Assistant Professor

• Usability of programming languages
• User-centered programming language design
• Type systems for safety
• +6 more

Michael Coblenz is an Assistant Professor in the Computer Science Department at University of California, San Diego. His research focuses on integrating user-centered design into programming language development, creating safer languages for blockchain and scientific computing. He completed his Ph.D. at Carnegie Mellon University under Jonathan Aldrich and Brad A. Myers, followed by a Basili postdoctoral fellowship at University of Maryland. Specializes in usability of programming languages Created Obsidian language for safer smart contracts Developed PLIERS methodology for iterative language design Active in Rust usability and REST API quality research His work bridges programming languages and human-computer interaction, with recent projects including Kale (safer spreadsheets) and climate change-focused programming tools. He has served on program committees for SPLASH, VL/HCC, and HATRA conferences. 2025: Graduate Consortium Co-chair at VL/HCC 2024: HATRA Organizing Chair 2023: Doctoral Symposium Chair at SPLASH

• Supply Chain Coordination
• Spreadsheet Modeling
• Decision Making & Optimization
• +3 more

Professor Michelle Cheong Lee Fong is a full-time faculty member at the School of Information Systems, Singapore Management University. She holds leadership roles as Associate Dean for Post-Graduate Professional Education and Director of the Doctor of Engineering program, and is actively involved in designing educational frameworks for technology-driven learning. Current affiliations: Singapore Management University (School of Information Systems) Research focus: Supply chain coordination, spreadsheet modeling, and educational technology Key courses taught: Computer as an Analysis Tool, Financial Modeling, Process Modeling Her research interests in supply chain coordination span strategic hub location optimization, tactical supplier coordination, and operational transportation planning. She also specializes in spreadsheet modeling for business decision-making, having developed textbook resources and case studies for logistics networks and financial planning. Recent work explores AI's role in digital education, including ChatGPT's impact on assessment design and ethical considerations in AI-driven pedagogy. The articles she has written or co-authored demonstrate expertise in operations research, educational technology, and AI applications. Topics include optimization theory, heuristic algorithms for scheduling, and digital assessment frameworks that integrate learning analytics. Her work bridges spreadsheet modeling's pedagogical value with modern challenges like ChatGPT's influence on student learning. Her teaching portfolio includes courses such as IS102 (Computer as an Analysis Tool), IS304 (Process Modeling), and FNCE645 (Financial Modeling). These courses emphasize practical skills in translating business requirements into technology solutions through spreadsheet-based analytical frameworks.

Rui AbreuView profile

Professor

• Software Engineering
• Software Testing
• Debugging
• +6 more

Rui Abreu is a Professor at the Faculty of Engineering of the University of Porto (FEUP), Portugal, with extensive expertise in software quality, testing, and debugging. Previously, he served as Associate Professor at IST-ULisbon and Assistant Professor at the University of Porto. His research bridges academia and industry through roles including Visiting Researcher at Google NYC (2019-2020) and co-founding DashDash, a $9M Series A-funded startup for spreadsheet-based web app development. His educational background includes a Ph.D. in Computer Science - Software Engineering from Delft University of Technology and an M.Sc. in Computer and Systems Engineering from the University of Minho. His research focuses on automating software testing and debugging , with growing emphasis on quantum software testing, vulnerability detection, and AI-assisted development tools. Recent work explores large language models for loop invariant generation, interpretable vulnerability reports, and quantum mutation testing. His publication trends reveal a strong shift toward security-critical systems and emerging computing paradigms , with 30% of recent papers addressing quantum software challenges and 45% focusing on vulnerability detection/repair. The work consistently combines static/dynamic analysis with machine learning, targeting practical tool development for real-world engineering problems. 6 Best Paper Awards Distinguished Paper Award at ESEC/FSE 2019 Abreu actively mentors through conference committees (serving on 12+ program committees in 2024-2025) and industry engagement. His DashDash venture demonstrates successful technology transfer, while Google collaboration advanced C/C++ security tooling. Current work includes quantum software metrics and security commit standardization. He leads research teams focused on software quality automation, with recent projects including GZoltarAction (GitHub fault localization bot) and Maestro (vulnerability repair benchmarking platform). Future directions emphasize scalable security analysis for quantum systems and human-AI collaboration in debugging workflows.

Charles KelliherView profile

Associate Professor

• Tax Compliance
• Tax Planning
• Social Norms
• +2 more

Charles Kelliher is an Associate Professor at the Kenneth G. Dixon School of Accounting within the College of Business at the University of Central Florida. His research primarily explores tax compliance, tax planning strategies, and the impact of social norms on taxpayer behavior. He employs empirical and behavioral approaches to investigate fiscal decision-making. Kelliher's work spans interdisciplinary domains, integrating accounting with behavioral economics and public policy. His recent articles focus on modern tax administration challenges, including pre-populated tax returns and behavioral interventions to enhance compliance. Long-term research trajectories include financial modeling applications, with historical work on spreadsheet optimization for capital budgeting and investment simulations. Methodological contributions include psychometric scale development for tax compliance studies.