Find Academic Supervisors

Pardis PishdadView profile

Associate Professor

• Sustainable Built Environments
• Integrated Project Delivery (IPD)
• Digital Twin Technology
• +9 more

Pardis Pishdad is an Associate Professor and Graduate Program Director in the School of Building Construction at Georgia Institute of Technology’s College of Design. She directs the Smart Built Environment Eco-System (Smart Bees) Laboratory, focusing on integrating cyber-physical systems, digital twins, and innovative project delivery methods (e.g., IPD, Flash Tracking) for sustainable built environments. Her research bridges technology adoption, trust-building in construction contracts, and supply chain optimization. Education: PhD, Environmental Design and Planning (Virginia Tech) Master’s Degrees: Civil Engineering (Virginia Tech), Design Studies in Project Management (Harvard), Architecture (University of Tehran) Bachelor’s in Architectural Engineering (Azad University of Shiraz) Research Interests: Her work emphasizes sustainable construction practices using IoT, BIM, and blockchain. Key areas include lifecycle cost analysis, lean construction, and smart building technologies. She explores trust dynamics and collaboration in construction projects through game theory and process optimization. Recognition: 2018 ENR Top 20 Under 40 Professionals 2016 CII National Outstanding Researcher Award 2020-2022 Georgia Tech Provost Teaching Learning Fellow Advisory Roles: Academic Advisor for CII’s Supply Chain Management Community, Vice Chair of BuildingSMART’s BIM Forum 5D Taskforce. Formerly advised the Construction Management Association of America’s Board (2016–2018). Industry Collaboration: Partnerships with Turner Construction, GDOT, and VDOT. Research on Flash Tracking and blockchain has been integrated into industry practices. Labs & Teams: The Smart Bees Lab pioneers cyber-physical systems for smart buildings, exploring AI-driven solutions and sustainable construction frameworks.

• Inverse Problems
• Nonlinear Acoustics
• Medical Imaging
• +5 more

Yang Zhang is a Visiting Assistant Professor in the Department of Mathematics at the University of California, Irvine (UCI), working under Prof. Katya Krupchyk. His research focuses on inverse problems in imaging sciences, nonlinear hyperbolic equations, and medical imaging applications. He previously held a postdoctoral position at the University of Washington, Seattle, under Prof. Gunther Uhlmann. His work integrates microlocal analysis and partial differential equations to address challenges in wave propagation, nonlinear acoustics, and elasticity. Education & Career: PhD from Purdue University (advisor: Prof. Plamen Stefanov) Postdoc: University of Washington, Seattle (2020–2024) Research Interests: Dr. Zhang's work spans inverse problems for nonlinear hyperbolic equations, acoustic imaging, and integral transforms in medical contexts. He develops novel methodologies using multi-fold linearization, wave interactions, and advanced calculus techniques. His studies on Rayleigh and Stoneley waves in elasticity further demonstrate his expertise in microlocal analysis. Key Contributions: His research bridges theoretical mathematics and applied imaging, with notable publications on inverse scattering, damping effects in wave equations, and Compton camera imaging. He is an active member of the Inverse Problems International Association (IPIA). Grants & Collaborations: Collaborations with prominent figures like Prof. Gunther Uhlmann and Prof. Katya Krupchyk highlight his network in inverse problems. His work often involves both analytical and computational approaches, with applications in medical diagnostics and geophysics.

Gary MarksView profile

Professor

• Comparative Politics
• Multilevel Governance
• European Integration
• +4 more

Gary Marks is a Distinguished Professor of Political Science at the University of North Carolina at Chapel Hill (UNC-Chapel Hill) and a Part-Time Professor at the European University Institute (EUI) in Florence. His primary affiliation is with the Department of Political Science at UNC-Chapel Hill, where he holds the Burton Craige Professorship. He also serves as a Research Professor at the Robert Schuman Centre for Advanced Studies at the EUI. Marks received his Ph.D. in Political Science from Stanford University and has held visiting professorships and fellowships at institutions such as VU Amsterdam, the Free University of Berlin, and the Hoover Institution. His research focuses on comparative politics, multilevel governance, European integration, and international organization. Notable contributions include his postfunctionalist theory of governance, detailed in works like Multi-Level Governance and European Integration (2001) and A Theory of International Organization (2019). He has been awarded prestigious honors, including the Humboldt Research Prize (2010), the Daniel Elazar Federalism Scholar Award (2017), and the Martha Derthick Award (2023) for his influential scholarship. Marks co-founded the UNC Center for European Studies (1994) and the EU Center of Excellence (1998). He currently co-leads an ERC Advanced Grant (TRANSNATIONAL) investigating political polarization in Western societies. His recent research explores education-based political cleavages, transnational governance, and the implications of crises like the pandemic on solidarity and policy responses. Awards: Humboldt Research Prize, Martha Derthick Award, Daniel Elazar Award, Honorary Doctorate from Maastricht University (2024) Grants: €2.5M ERC Advanced Grant (2010–2015), Current ERC Grant on Political Polarization (2021–2026) Labs/Teams: Transnational Lab at EUI, Chapel Hill Expert Survey (CHES) project Marks’ work bridges academic and policy circles, with datasets like the CHES providing foundational insights into global governance and political dynamics.

Jay PujaraView profile

Academic

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +5 more

Jay Pujara is a Research Associate Professor in the Department of Computer Science at the University of Southern California (USC), affiliated with the Viterbi School of Engineering and the Information Sciences Institute (ISI). He directs the Center on Knowledge Graphs and leads research in artificial intelligence, specializing in knowledge graph construction, scalable machine learning, and probabilistic models. Education : PhD in Computer Science (University of Maryland, 2016), MS and BS in Computer Science from Carnegie Mellon University (2005 and 2004), with minors in Robotics, Mathematical Sciences, and Logic & Computation. Research Interests : His work focuses on probabilistic models for dynamic data, knowledge graph construction, entity resolution, and applications in NLP and social network analysis. He emphasizes scalable algorithms and real-world impact in domains like finance, climate science, and healthcare. Awards : Includes the SWSA Ten-Year Award (2023), Best Paper Awards at IUI 2019 and ISWC 2013, and grants totaling over $9M from DARPA, NSF, and industry partners. Grants & Mentorship : Principal Investigator on projects like "Artificial Domain-Understanding and Collaborative Agency" (DARPA) and "Explainable and Robust AI Agents" (NSF). Mentored over 50 students in PhD, MS, and undergraduate programs, focusing on knowledge graphs, NLP, and machine learning. Labs & Teams : Leads ISI’s Knowledge Graph and Neurosymbolic AI teams, coordinating the Open Knowledge Network (OKN) and tools like KGTK. Active in academic service, including roles on PhD admissions committees and ISI’s Space Management Committee.

Navid IzadyView profile

Senior Lecturer

• Operations Research
• Healthcare Management
• Stochastic Modelling
• +3 more

Dr. Navid Izady is a Reader in Operations & Supply Chain at Bayes Business School, part of City St George's, University of London. His academic career includes a PhD from Lancaster University Management School (2010), and prior roles at the University of Southampton. He specializes in stochastic modelling for healthcare and manufacturing operations, collaborating with hospitals and healthcare organizations on sponsored research and consultancy projects. Dr. Izady holds qualifications in Industrial Engineering from Sharif University of Technology (BSc and MSc) and a PhD in Management Science. He teaches operations management, stochastic modelling, healthcare modelling, and decision analysis across BSc, MSc, and MBA programs. His research focuses on optimizing healthcare logistics, patient flow management, and resource allocation in hospitals. He has developed frameworks for managing pandemic and non-pandemic demand, reconfiguring inpatient services, and optimizing staffing and patient admission/discharge processes. His work bridges theoretical stochastic models with practical healthcare challenges, emphasizing operational efficiency and resilience. Notable contributions include studies on inpatient bed pressure reduction, sample pooling techniques for pandemic testing, and queueing theory applications in emergency departments and specialty clinics. His publications highlight innovations in healthcare operations management and simulation methods. Dr. Izady's expertise includes operations research, simulation, statistics, and stochastic processes. He supports industry partnerships and has supervised numerous research students, contributing to both academic and applied knowledge in healthcare and manufacturing systems.

Don B. RussellView profile

Professor

• Electric Power Engineering
• Power System Protection
• Control and Automation
• +5 more

Don B. Russell is a distinguished Professor of Electrical & Computer Engineering at Texas A&M University, holding the Harry E. Bovay, Jr. Chair and Regents Professor title. He is a member of the National Academy of Engineering and a Fellow of multiple professional organizations. His research focuses on power system automation, protection, and real-time diagnostics, with a strong emphasis on waveform analytics for fault detection and wildfire mitigation. Russell leads the internationally recognized Power System Automation Laboratory, supported by sponsors like the National Science Foundation and Texas A&M's Energy Resources Program. Educational Background: Ph.D., Electrical Engineering, University of Oklahoma (1975) M.E., Electrical Engineering, Texas A&M University (1971) B.S., Electrical Engineering, Texas A&M University (1970) Research Interests: Power system protection and control Incipient failure detection via waveform analysis Forensic engineering and wildfire prevention Engineering ethics and professionalism Smart grid technologies and automation Awards and Honors: IEEE Millennium Medal (2000) R&D 100 Award (Digital Feeder Monitor) Outstanding Engineering Achievement Award (NSPE) 6 Distinguished Achievement Award (Texas A&M) Grants and Sponsors: The lab collaborates with TXU Energy, NSF, ONR, and industry partners to advance power system reliability and safety. His work has led to commercialized technologies like high-impedance fault detection relays. Labs and Teams: The Power System Automation Lab specializes in real-time data capture and fault analysis, with global recognition for reducing wildfire risks and improving distribution network resilience.

Eric MasanetView profile

Professor

• Energy System Analysis
• Climate Change Mitigation
• Sustainable Manufacturing
• +4 more

Eric Masanet is a Professor and Mellichamp Chair in Sustainability Science for Emerging Technologies at the University of California, Santa Barbara (UCSB), holding a courtesy appointment in the Department of Mechanical Engineering. He leads the Bren School's Industrial Sustainability Analysis Laboratory, focusing on decarbonizing industrial and IT sectors while advancing equity and sustainability. His research spans energy system analysis, climate mitigation, and sustainable manufacturing. Education: Ph.D. in Mechanical Engineering from UC Berkeley, with M.S. and B.S. degrees from Northwestern University and the University of Wisconsin-Madison, respectively. Research interests include data center sustainability, industrial decarbonization, and the intersection of technology and climate policy. He has contributed to the IPCC's Sixth Assessment Report, advised the U.S. White House, and serves on the DOE's Industrial Technology Innovation Advisory Committee. Notable achievements include authoring the U.S. Data Center Energy Usage Report and leading the Resources, Conservation, and Recycling journal as former Editor-in-Chief. His work bridges academia with policy, influencing international energy and climate strategies. Advising and grants: Supervises PhD students (e.g., Jaxon Stuhr) and postdocs (Antoine Merlo, Jason Ye) in decarbonization research. Collaborates with Lawrence Berkeley National Laboratory and international organizations like the IEA. Labs/Teams: Directs the Industrial Sustainability Analysis Laboratory, advancing models for low-carbon industrial and IT systems.

• Risk Assessment
• Hydrogen Technologies
• Process Safety
• +4 more

Nicola Paltrinieri is a Professor of Risk Assessment at the Department of Mechanical and Industrial Engineering, NTNU (Norway), and an Adjunct Professor at the University of Bologna (Italy). His expertise spans risk assessment, hydrogen technologies, process safety, and data-driven safety management. He holds Chartered Engineer and Chartered Scientist certifications and has served on editorial boards for journals like Safety Science and Journal of Risk Research . Education: PhD in Environmental, Safety and Chemical Engineering (University of Bologna, 2012) Master’s in Chemical and Process Engineering (University of Bologna, 2008) Research Interests: Focuses on hydrogen infrastructure safety, Natech accident analysis, risk-based inspection strategies, and AI integration in safety systems. His work emphasizes sustainable energy transitions and mitigating risks in emerging technologies like hydrogen. Key Projects (2022-2026): H2Glass : Decarbonizing glass and aluminum sectors via hydrogen HyInHeat : Hydrogen technologies for industrial heating HYDROGENi : Norwegian research center for hydrogen/ammonia Awards: Onsager Fellowship (2016–2021) Frank Lees Medal (2012) for safety-related publications Grants & Leadership: Head of NTNU Energy Team Hydrogen, coordinator for EU-funded projects like SUSHy , and active in international risk committees (e.g., EFCE, ESRA). His work bridges academia and industry, with over 8 PhD examinations supervised. Labs/Teams: Leads the NTNU Energy Team Hydrogen and collaborates on initiatives like SH2IFT-2 for safe hydrogen fuel handling. His research group focuses on AI-driven risk analysis and hydrogen infrastructure resilience.

• Natural Language Processing
• Machine Learning
• Deep Learning
• +7 more

Tuğba Dalyan is an Associate Professor in the Department of Computer Engineering at Istanbul Bilgi University, Faculty of Engineering and Natural Sciences. She holds a Ph.D. in Computer Engineering from Yıldız Technical University (2014), an MSc from Kocaeli University (2007), and dual BSc degrees in Mathematics and Computer Science and Business Administration (Minor) from Istanbul Bilgi University (2003). She has been a faculty member since 2016 and previously served as a Teaching Staff member and Research Assistant at the same institution. Her research focuses on Natural Language Processing , Machine Learning , Deep Learning , Text Mining , Data Science , and Big Data Analytics . Her work spans computational linguistics, sentiment analysis, author profiling, machine translation, and smart systems. She has led and contributed to numerous research projects, particularly in AI-driven urban solutions and health technologies. The most recent publications show a strong trend in Turkish NLP, zero-shot classification, multimodal AI (image captioning), emotional robotics, and decision support systems using fuzzy logic. Her work combines theoretical rigor with practical applications in smart cities, education, and healthcare. Best Paper Award , CICLing 2012 TÜBİTAK 2209-A student project awards (2022–2024) Horizon2020 Eşik Üstü Ödülü , MIMOSCSA 2024 TÜBİTAK 2242 competition: 2nd and 3rd place (2016, 2018) She has advised numerous student research projects, many of which have received national recognition. She has directed multiple TÜBİTAK and institutional research grants, including projects on smart homes, blockchain crowdfunding, mental health, and AI for social polarization. Her leadership roles include Head of Department, Vice Dean, and Director of Graduate Programs. Tuğba Dalyan leads research in AI and NLP with a strong emphasis on Turkish language technologies. She is involved in interdisciplinary teams working on emotional robots, smart city platforms, and citizen science ecosystems. Her lab activities focus on neural networks, text analysis, and intelligent systems development.

Daniel A. SassView profile

Associate Professor

• Psychometrics
• Structural Equation Modeling
• Factor Analysis
• +3 more

Dr. Daniel A. Sass is an Associate Dean for Graduate Studies and Associate Professor in the Department of Management Science and Statistics at the University of Texas at San Antonio’s Carlos Alvarez College of Business. He directs the Statistical Consulting Center and focuses on methodological research, including psychometrics, structural equation modeling, and factor analysis. His applied work spans education, public health, and organizational behavior. Education: Ph.D. in Management Science and Statistics, University of Wisconsin-Milwaukee B.A., University of Wisconsin-Milwaukee Research Interests : Dr. Sass specializes in advanced statistical methodologies with applications in education and social sciences. His work emphasizes psychometric validation, measurement invariance, and applied collaborative projects. Key areas include teacher retention, classroom management, and cross-cultural scale adaptation. His research bridges theoretical statistical frameworks with real-world challenges in education and public policy. Publications Trends : Recent work explores pandemic impacts on productivity, educator stress in charter schools, and diabetes management programs. Earlier studies focus on statistical methods like factor analysis and structural equation modeling validation. His articles consistently address practical implications for policy and practice. Advising/Grants : While no advisees are listed, his collaborative projects involve interdisciplinary teams across education, public health, and organizational studies. His Statistical Consulting Center supports UTSA researchers in applying rigorous statistical methods to their work. Labs/Teams : Director of the Statistical Consulting Center, providing methodological support for academic and applied research projects.

• Artificial Intelligence
• Healthcare Informatics
• Data Science
• +5 more

Luís B. Elvas is an Assistant Professor at ISCTE-University Institute of Lisbon's Department of Social and Business Sciences (SINTRA) and a Research Assistant at ISTAR-Iscte Research Center. He holds qualifications including a Technical Specialization in TensorFlow for AI (Coursera, 2021) and certifications in IoT/Blockchain from ISCTE and cybersecurity from Palo Alto Networks. His research spans artificial intelligence, healthcare informatics, smart cities, and blockchain, with applied work in medical imaging, data sharing, and urban analytics. Research interests include: Healthcare AI : Developing deep learning models for cardiac diagnostics, medical imaging analysis, and blockchain-based health data systems Smart Cities : Implementing IoT solutions for urban mobility optimization, disaster management, and sustainable transportation Data Science : Creating predictive analytics frameworks for clinical decision support and urban planning His publications demonstrate a strong focus on AI-driven healthcare solutions (67% of recent works) and smart city technologies (33%), with emerging interests in blockchain and NLP. Research consistently targets real-world applications in clinical settings and urban environments. Awards: Award for best internship, Order of Engineers (2022) Distinction for best internship, Order of Engineers (2021) He leads/contributes to multiple EU research consortia including AMR-EDUCare (antimicrobial resistance education), NEEM (e-health in Nepal), and Blockchain.PT. Coordinates the IEEE Computational Intelligence Society Student Branch Chapter at ISCTE and developed the ManagiDiTH master's program in digital health transformation.

Michael PhilbenView profile

Associate Professor

• Carbon Cycle
• Climate Change Biogeochemistry
• Peatland Ecosystems
• +4 more

Dr. Michael Philben is an Associate Professor of Chemistry and Geological and Environmental Science at Hope College, where he joined in 2019 after postdoctoral positions at Memorial University (Canada) and Oak Ridge National Laboratory. His research focuses on climate-carbon cycle feedbacks in vulnerable ecosystems, particularly peatlands and Arctic tundra. His educational background includes a Ph.D. in Marine Science from the University of South Carolina (2014) and a B.A. in Earth and Planetary Science from Northwestern University (2010). At Hope College, he teaches Environmental Science courses and contributes to the Day1: Watershed program. Philben's research centers on carbon and nitrogen cycling in ecosystems containing vast organic carbon stocks. He leads an NSF CAREER-funded project investigating Michigan peat bogs as natural laboratories for climate change impacts, using a north-south transect from Portage to Newberry as a 'space-for-time' experiment. His work examines methane emissions, nitrogen availability, and net carbon balance under warming conditions, with particular attention to Sphagnum-dominated peatlands at the southern edge of their climate range. His 15 most recent publications (2020-2024) reveal a strong focus on peatland biogeochemistry, with increasing emphasis on methane dynamics, nitrogen cycling, and the role of specific biochemical compounds like sphagnan. The research combines field measurements across climate gradients with laboratory experiments, often involving Hope College students in all project phases. NSF CAREER Award for peatland climate research Philben actively mentors undergraduate researchers through the Philben Research Group, which investigates how warming impacts carbon cycling in peatlands. His projects involve interdisciplinary work spanning analytical chemistry, geology, and ecology. The group maintains a network of seven Michigan peat bog field sites and collaborates on international research, including Arctic studies in Alaska and Canada. His laboratory focuses on using analytical chemistry tools to predict climate-carbon cycle feedbacks, with particular attention to southern Michigan peatlands as sentinels for larger northern peatland complexes. The research group employs techniques including greenhouse gas flux measurements, radiometric dating of peat cores, and analysis of organic matter composition.

Matthew StephensonView profile

Lecturer

• Artificial Intelligence
• Machine Learning
• Data Science
• +5 more

Matthew Stephenson is a Lecturer at Flinders University's College of Science and Engineering, specializing in Artificial Intelligence applications for games. He leads the Data for Decisions initiative within the Factory of the Future Transdisciplinary Hub, focusing on AI-powered scenario generation for smart digital twins. Additionally, he is a member of IRL CROSSING, an international lab studying human-autonomous agent teaming dynamics. PhD in Computer Science (Australian National University, 2019) B.Sc.(Hons) in Computer Science (University of Canterbury, 2015) His research applies AI, Machine Learning, and Data Science to game domains, including intelligent agent development for physics-based environments, procedural content generation, and game analytics. He also investigates deceptive behaviors in multi-agent systems and leverages games as testbeds for real-world AI solutions. Recent publications focus on large language models for game benchmarking, physical reasoning challenges, and evolutionary game generation. Scientific awards include an honourable mention at Foundations of Digital Games (FDG'18). He supervises students in procedural generation, game AI, and physics-based task creation, with teaching roles in computational intelligence and neural networks courses.

Abhishek Singh BhatiView profile

Professor

• Tourism Management
• Sustainable Tourism
• Responsible Tourism
• +6 more

Professor Abhishek Singh Bhati is the Pro Vice-Chancellor and CEO at the Newcastle Australia Institute of Higher Education. He is a distinguished academic and administrator with a focus on tourism management and scholarship of learning and teaching. His research explores technology-driven tourism transformations, low-carbon tourism, and the alignment of tourism with United Nations Sustainable Development Goals (SDGs). Bhati’s work also emphasizes tourist behavior, resilience planning, and vandalism management in tourism settings. PhD (Tourism Management), James Cook University, Australia MBA (Marketing Management), Maastricht School of Management, Netherlands Bachelor of Arts (Economics), Bombay University, India Diploma in Adult and Continuous Education, Institute of Adult Learning, Singapore Graduate Certificate in Education (Tertiary Teaching), James Cook University, Singapore His research spans technology’s role in tourism, sustainable development, and educational innovation. Recent publications address energy-economic synergies, AI in tourism, and post-pandemic travel behavior. Bhati has secured grants from organizations like the World Wide Fund for Nature (WWF) and the Australian Government’s Office of Learning and Teaching (OLT). Scientific Honors: Fellow of the Higher Education Academy (FHEA)

• Textile Engineering
• Textile Design
• Yarn Technology
• +5 more

Asst. Prof. Zehra Evrim Kanat serves as an Assistant Professor in the Textile and Fashion Design Department at Canakkale Onsekiz Mart University's Faculty of Fine Arts since 2020, following research assistant roles at Tekirdağ Namik Kemal University (2014-2020) and Ege University (2009-2014). Her expertise bridges academic research and industry applications in textile engineering. Her educational foundation includes: Doctorate in Textile Engineering from Ege University (2008-2013) Postgraduate in Textile Engineering from Ege University (2005-2007) Undergraduate in Textile Engineering from Ege University (1997-2002) Dr. Kanat's research centers on textile engineering and design, with specialized focus on thermal and moisture management properties of fabrics. She investigates yarn technology, cloth construction, and smart textile applications to enhance comfort in sportswear and technical garments. Her methodological approach integrates artificial neural networks and statistical modeling for predictive analysis of fabric behavior under varying humidity conditions, contributing significantly to thermophysiological comfort research. Publication trends reveal consistent advancement in thermal resistance modeling of knitted and woven fabrics, with recent expansion into smart textiles for sports applications and biomimetic design principles. Her work demonstrates strong interdisciplinary connections between textile science, materials engineering, and functional apparel design. Her research leadership includes: EU-supported project on Textile Insights and Future Aspects (2023-2024) Study on Hatay Silk's fiber properties versus Chinese-Japanese hybrid silk (2022-2023) TUBITAK-funded expert system for woven fabric defect diagnosis (2017-2018) Multiple projects on moisture management properties of technical textiles Dr. Kanat actively contributes to academic discourse through peer review for leading textile journals and participates in interdisciplinary art exhibitions that explore cultural and historical textile narratives.