Liuping Wang is a Professor in the School of Electrical and Computer Engineering at RMIT University, Australia, since 2007. He serves as Head of Discipline for Electrical Energy and Control Systems since 2005 and teaches Advanced Control Systems (EEET 2100) and Real Time Estimation and Control (EEET 2221). Current academic rank: Professor Location: City Campus, Australia Industry collaborators: ANCA, Australian Power Academy, Advanced Manufacturing CRC His research interests span: Control Theory with applications to UAVs and industrial processes Development of Model Predictive Control systems System Identification using neural networks Robust Control for constrained systems Control of AC motors and power electronics Applications in biomedical research and food process monitoring The 15 most recent publications (2015-2025) demonstrate expertise in: UAV control systems with segmented surfaces Battery condition monitoring for electric vehicles Mult-agent robotics with coordination algorithms Smart grid security and electricity dispatch GPS-denied localization for mobile robots Disturbance observer control with input constraints As a supervisor, he oversees Masters Research and PhD projects but no specific student names are listed. His email is liuping.wang@rmit.edu.au for collaboration or supervision inquiries.
Hannie A. Gijlers is an Associate Professor at the Digital Society Institute, affiliated with the Department of Instructional Technology in the Faculty of Behavioral, Management and Social Sciences at the University of Twente. Her work bridges technology and education, focusing on innovative learning environments and collaborative processes. Academic Rank: Associate Professor Institution: University of Twente Research Institute: Digital Society Institute Department: Instructional Technology Her research interests center on computer-supported collaborative learning (CSCL) , technology-enhanced STEM education , inquiry-based learning , and the role of emotions and feedback in learning. She investigates how digital tools and agent-facilitated environments support students and teachers in collaborative settings, often through cross-cultural comparisons. Her work integrates physiological and gaze-based data to understand implicit learner emotions, pushing the boundaries of learning analytics. The recent publications (2021–2024) reveal a strong focus on teacher guidance models , gamified STEM apps , clinical reasoning in medical education , and climate change literacy . These works span disciplines including educational psychology, computer science, and environmental education, indicating interdisciplinary collaboration. Keywords across these articles include collaborative learning, emotion detection, technology integration, and cross-cultural studies, reflecting a consistent research trajectory in digital pedagogy and learner support. While no specific awards are listed in the provided text, her sustained publication record in high-impact venues and leadership in collaborative research projects suggest recognition within the academic community. Hannie Gijlers actively supervises research, as evidenced by co-authored works with junior researchers and contributions to practitioner research models. Her involvement in datasets and conference presentations indicates ongoing grant-funded or institutionally supported research activities. She has contributed to both theoretical frameworks (e.g., four-phase mentorship model) and applied tools (e.g., Science Chaser app), demonstrating a balance between scholarship and practical innovation. She is part of a vibrant research network at the University of Twente, collaborating with scholars like T.H.S. Eysink, A.W. Lazonder, and N. Janssen. Her team explores agent-facilitated learning, gamification in STEM, and teacher development, often in international collaborations (e.g., Dutch-Finnish studies). These efforts are supported by digital infrastructure and interdisciplinary datasets, positioning her at the forefront of digital society research in education.
Andrea Iannelli is a Tenure-Track Assistant Professor at the Institute for Systems Theory and Automatic Control (IST) , University of Stuttgart, Germany. He also serves as a faculty member of the International Max Planck Research School for Intelligent Systems (IMPRS-IS) and participates in the Cluster of Excellence Data-Integrated Simulation Science (SimTech) . His research focuses on reconciling model-based and data-driven approaches for robust and adaptive control of uncertain dynamical systems. Ph.D. : Control and Dynamical Systems, University of Bristol (UK), 2019 Postdoctoral Researcher : ETH Zürich (Switzerland), 2019–2022 Harnessing the intersection of control theory, optimization, and machine learning , Iannelli’s work addresses data-driven modeling, uncertainty quantification, and robust control with applications in energy systems, intelligent transportation, and industry 4.0 . His recent publications highlight trends in LPV frameworks, online convex optimization, and hybrid control systems , emphasizing safety and efficiency. He contributes to the academic community as an Associate Editor for the International Journal of Robust and Nonlinear Control and as a member of international conference IPCs. His group, Trustworthy Autonomy for Smart Adaptive Systems (TASAS) , mentors PhD students in projects spanning adaptive control, uncertainty quantification, and reinforcement learning .
David Baqaee is a Professor of Economics at the University of California, Los Angeles (UCLA), affiliated with the Department of Economics in the College of Letters and Science. His research focuses on aggregation and heterogeneity in macroeconomics, particularly examining how resource misallocation from market power, nominal rigidities, and increasing returns to scale impacts aggregate productivity. He has contributed to prestigious journals such as Econometrica and the American Economic Review. Education: Ph.D. Economics, Harvard University; B.Sc. Mathematics and Economics, University of Canterbury His research interests span applied economic theory, industrial organization, macroeconomics, and network economics. Recent work explores trade wars, sanctions' long-term effects, energy import dependencies, and the interplay between monetary policy and supply-side dynamics. He has served as an associate editor for Econometrica and the Quarterly Journal of Economics. His publications reflect a focus on policy-relevant macroeconomic questions, including the consequences of geopolitical events, trade restrictions, and pandemic impacts on global supply chains. His methodologies emphasize disaggregated models and input-output networks to capture microeconomic foundations of aggregate phenomena.
Abhik Roychoudhury is a Provost's Chair Professor of Computer Science at the National University of Singapore (NUS), leading the Trustworthy and Secure Software (TSS) research group since 2001. His work focuses on automated program repair, software testing, security, and agentic AI. He is a Senior Advisor at SonarSource following the acquisition of his startup AutoCodeRover. He holds an ACM Fellowship and has received the ICSE Most Influential Paper Award for program repair research. Education: M.S. and Ph.D. in Computer Science from State University of New York at Stony Brook (1997-2000). Research interests include program analysis, software security, and AI-driven software engineering. His team has pioneered techniques like SemFix and Angelix for program repair, and AFLNet for protocol fuzzing. He has served as editor-in-chief of ACM TOSEM and conference chair for ICSE and FSE. Awards include the NUS Outstanding Graduate Mentor Award (inaugural recipient) and IEEE New Directions Award. His work bridges academia and industry, with contributions to projects like the DesCartes initiative for critical urban systems. Key collaborations include Microsoft on API repair and IBM on AI research centers. His recent focus includes agentic AI for software engineering, reflected in AutoCodeRover's acquisition by SonarSource.
Nuno Pinto is a Senior Lecturer in Urban Planning and Urban Design at the University of Manchester's School of Environment, Education and Development. He holds a PhD in Planning from BarcelonaTech (Spain) and a Civil Engineering degree from the University of Coimbra (Portugal). Previously, he held academic positions at the University of Coimbra and served as a Researcher at the Polytechnic Institute of Leiria. His research focuses on quantitative approaches to urban planning, including decision support systems, urban simulation, integrated transport planning, and big data applications. He is particularly known for his work on cellular automata models and agent-based simulations in urban policy analysis. Nuno has secured significant funding, including a £663k EPSRC grant for the 'Resilience Beyond Observed Capabilities Network+' and a £19k Turing-Manchester grant for VR analytics in digital twins. Teaching expertise spans data science applications in planning, GIS, and decision-support methods across multiple master's programs. He advises on PhD topics combining quantitative methods with Iberian/Latin American urban contexts. Nuno is a Fellow of the Higher Education Academy and recipient of the 2011 Breheny Prize for outstanding urban planning research. Notable projects include 'Synthetic Cities' digital twin frameworks, peri-urban climate change analyses (PERI-CENE), and cross-border collaborations like the FAPESP-University of Manchester initiative. Current research explores smart city strategies in Latin America and carbon accounting systems. Supervised over a dozen PhD students, including works on mobility decision systems, metropolitan data analytics, and serious gaming for urban participation. Active in professional networks such as the COST TU1408 Air Transport and Regional Development initiative.
Tim J. Nye is an Associate Professor in the Department of Mechanical Engineering at McMaster University's Faculty of Engineering. He holds a Ph.D. in Mechanical Engineering (1997) from the University of Waterloo, following an M.Sc. (1989) at Ohio State and B.A.Sc. (1987) at Waterloo. His research focuses on applying operations research techniques to manufacturing systems, with specific expertise in optimization algorithms for sheet metal processes, hydroforming reliability, and adaptive control in forging. Education: Ph.D. Mechanical Engineering, University of Waterloo (1997) M.Sc. Mechanical Engineering, Ohio State (1989) B.A.Sc. Mechanical Engineering, University of Waterloo (1987) Research interests span multiple dimensions of advanced manufacturing: developing decision models for production investment, creating novel lot-sizing algorithms incorporating work-in-process costs, exact solutions for 2D nesting problems, and agent-based systems for reliability prediction using warranty data. His work bridges theoretical operations research with practical metal forming applications. Recent publications demonstrate consistent contributions to manufacturing optimization, with particular focus on stamping processes, sheet metal design, and hydroforming reliability. These align with McMaster's research clusters in Advanced Materials & Manufacturing and Infrastructure. Scientific awards include the 2002 CSME Best Student Paper competition win for machine vision research with S. Dworkin. He maintains active collaborations with industry partners, as evidenced by his research on industry-university R&D ventures. Current projects explore intelligent open die forging as a solid freeform fabrication method, demonstrating his commitment to both traditional manufacturing improvement and emerging rapid prototyping technologies.
Dr. Tyler Hollett serves as an Associate Professor of Learning Sciences in the Department of Learning and Performance Systems at The Pennsylvania State University, contributing to the Learning, Design, and Technology program from 315 Keller Building, University Park, PA. His research champions interest-driven learning often devalued by formal institutions and neoliberal markets, investigating contexts like skateboarding, video gaming, and nature hobbies (fishing, birding). Hollett examines how passion-fueled activities generate embodied, affective learning that transcends goal-oriented education, advocating for equitable alternatives to capitalist learning trajectories. Current projects focus on intergenerational play through the FIGMENT Lab, exploring family gaming dynamics, climate engagement via outdoor hobbies, and evolving children's play across settings. Analysis of his recent publications reveals a methodological commitment to qualitative inquiry, with recurring themes of spatial-temporal rhythms, affective atmospheres, and embodied cognition. His work bridges learning sciences, critical pedagogy, and digital media studies, increasingly emphasizing intergenerational and ecological dimensions of informal learning. No scientific awards are listed in his current profile. However, Hollett actively mentors graduate students, inviting collaboration on FIGMENT Lab initiatives. His advising philosophy emphasizes rigorous scholarship within supportive, interest-driven research teams, with the FIGMENT Lab representing his current focus on family-centered learning in gaming, nature, and play contexts.
Dr. Ahmed F. Abdelghany is the Associate Dean for Research and Professor of Operations Management at the David O'Maley College of Business, Embry-Riddle Aeronautical University, since January 2006. He specializes in commercial airlines, airports, big data cloud computing, business analytics, and operations research models. Prior to his academic career, Dr. Abdelghany worked in enterprise optimization at United Airlines, Chicago. Education: Ph.D. in Civil Engineering (Transportation Systems) from the University of Texas at Austin (2001) Dr. Abdelghany’s research focuses on airline network planning, flight scheduling, simulation of complex transportation systems, and NextGen air traffic management. He has authored two influential books: Modeling Applications in the Airline Industry (Routledge 2010) and Airline Network Planning and Scheduling (Wiley 2018). His publications analyze airline operations, competitive dynamics, and crowd management in transportation facilities. He teaches courses like Airline Management (BA 315) and Airline Operations & Mgmnt (BA 609), and participates in industry short courses. Dr. Abdelghany contributes to research projects such as NextGen air traffic implementation, integrated airport initiatives, and benefit-cost analysis of arrival management systems. His work bridges academic theory with real-world airline and transportation challenges.
Yan Huang is an Associate Professor in the Department of Software Engineering and Game Development at Kennesaw State University (KSU). His work bridges Federated Learning (FL) and Cybersecurity Education , with a focus on personalization and privacy in distributed systems. Research spans Machine Learning , Extended Reality (XR) , and Data Privacy . He has served as Editor of WCMC and Program Co-Chair for CyberSciTech 2020-2024. Research Trends: Recent publications emphasize Federated Learning for non-IID data, VR-based Cybersecurity Education , and Privacy-Preserving Algorithms in IoT and social media analytics. Key subfields include personalized learning architectures, graph learning, and game-theoretic privacy frameworks. Scientific Awards: Excellent Paper Award (Tsinghua Science and Technology, 2021) Best Paper Award (Future Generation Computer Systems, 2019) Best Paper Awards at IEEE SmartWorld 2021, COCOA 2019, and WASA 2019 Grants: Led over $600,000 in NSF and NSA-funded projects, including VR cybersecurity education for K-12 and XR engineering curricula. His lab recruits VR/AR Research Assistants via industry partnerships.
Derek T. Robinson is an Associate Professor at the University of Waterloo's Department of Geography and Environmental Management , specializing in land-use science, agent-based modeling, and geospatial analysis. His work integrates GIS, ecological models, and human decision-making to assess impacts of land policies on ecosystem services and human well-being. Research Interests : Land-use/cover change and carbon cycle dynamics Agent-based modeling of socio-ecological systems Exurban land management and fragmentation Ecosystem service quantification Land policy scenario analysis Teaching : Courses in spatial analysis, advanced GIS, and land-use-carbon interactions. His lab utilizes cutting-edge tools like ArcGIS, NetLogo, and UAV systems (e.g., Aeryon SkyRanger) for fieldwork and modeling.
Jeeseop Kim is an Assistant Professor in the Department of Aerospace and Mechanical Engineering at The University of Texas at El Paso (UTEP), College of Engineering, specializing in robotics, autonomy, and control theory. His research focuses on safety-critical planning and control, with emphasis on bipedal/quadrupedal locomotion, hybrid dynamical system control, and whole-body planning and control. Education: B.S. in Mechanical and Aerospace Engineering, Seoul National University (2014) M.S. in Intelligence and Information (Robotics), Seoul National University (2017) Ph.D. in Mechanical Engineering, Virginia Tech (2022) Postdoctoral Scholar, Mechanical and Civil Engineering, Caltech (2022–2025) His research spans safety-critical control systems for legged robots, including obstacle-aware nonlinear model predictive control (MPC), control barrier functions, and distributed coordination algorithms. Recent work explores adaptive delay estimation, tactile sensing for robotic grasping, and hardware-software co-design for humanoid robots. Key article trends highlight advancements in autonomous inspection robotics, hybrid control architectures, and real-time planning for quadrupedal systems. His work integrates control theory with practical applications in industrial and healthcare domains. Awards: ASME DSCD Rudolf Kalman Best Paper Award (2022) IEEE ICRA Outstanding Paper Award (2023) Jeeseop teaches MECH 4332: Mechanical Computational Applications in Vision and Robotics (Fall 2025). He actively recruits Ph.D. students for Spring/Fall 2026 and seeks motivated undergraduates/MS students with skills in robotics kinematics, programming (C/C++, Python, MATLAB), and CAD design. The AIGIS Lab welcomes applicants with interests in robotics, controls, and autonomous systems.
Jessica A. Mong, PhD , is a Professor in the Department of Pharmacology & Physiology at the University of Maryland School of Medicine , where she also serves as Assistant Dean for Graduate & Post-Doctoral Studies and Director of Graduate Education for the Program in Neuroscience. Her research focuses on the neuroendocrine mechanisms underlying sex differences in sleep circuitry and the estrogenic modulation of sleep-wake cycles. Primary Appointment: Pharmacology & Physiology Administrative Title: Assistant Dean for Graduate & Post-Doctoral Studies Laboratory Director: Program in Neuroscience Research Interests: Dr. Mong's work investigates how ovarian steroids influence sleep-wake behavior through sexually differentiated neuroanatomical substrates. Key areas include: Mechanisms of estrogenic modulation in the median preoptic nucleus (MnPN) Developmental programming of sex differences in sleep sensitivity Translational studies using rodent and nonhuman primate models of menopause Functional significance of hormonal influences on sleep quality and recovery Scientific Trends: Her recent publications (2023-2025) emphasize: Role of KCNMA1 channelopathy in sleep regulation Adenosinergic signaling in MnPN Translational menopause models Estrogen's protective effects against noise-induced hearing loss Sex-dependent responses to kynurenine pathway challenges Awards & Appointments: NIH BIRCWH Scholar (Building Interdisciplinary Research Careers in Women's Health) Co-Chair, Society for Women’s Health Research Interdisciplinary Research Network on Sex-Differences in Sleep Health NIH/NHLBI R01 HL129138 grant recipient Education & Training: B.S., Biology, Gettysburg College (1987-1991) Ph.D., Neuropharmacology, University of Maryland Baltimore (1994-2000) NIH Postdoctoral Fellowship in Endocrinology, Rockefeller University (2000-2003)
Nathorn Chaiyakunapruk is a Professor in the Department of Pharmacotherapy at the University of Utah College of Pharmacy . He holds an adjunct appointment in Population Health Sciences and serves on multiple institutional committees including the Global Health Steering Committee and Health Economics Core at CTSI . His academic leadership extends to international roles with the World Health Organization and founding initiatives like the ISPOR Asia Consortium . Education : PhD in Pharmaceutical Outcomes Research, University of Washington PharmD, University of Wisconsin-Madison BS in Pharmaceutical Science, Chulalongkorn University Research Interests span health technology assessment , global health economics , and evidence synthesis . His work applies methodologies like network meta-analysis and umbrella reviews to address health equity, infectious disease modeling, and pharmaceutical policy. Recent studies focus on social determinants of health and vaccine economic value . Article Trends highlight collaborations in AI-assisted systematic reviews , vaccine rollout optimization , and health disparities . His publications frequently address cost-effectiveness and global health burden across infectious and non-communicable diseases. Scientific Awards : Senior Class (P4) Distinguished Teacher (2022) NRCT Outstanding Research Award (2019, 2012) Monash University PVC Research Award (2015) Nagai Research Foundation Awards (2006-2010) ISPOR Task Force Leadership (CHEERS 2022) Teaching & Service : Courses include Systematic Review and Meta-analysis and Global Health Policy . He chairs the Asia Pacific Evidence-based Medicine Network and advises WHO on vaccine economics and Thailand’s National Health Security Office on pharmaceutical policy.
Panagiotis Papapetrou is a Professor of Data Science and Deputy Head of Department at the Department of Computer and Systems Science , Stockholm University (since 2017). He also serves as Head of the Data Science Research Group and holds an Adjunct Professor position at Aalto University (Finland). As a Board Member of the Swedish Association for Artificial Intelligence (SAIS) , he contributes to shaping AI research directions in Sweden. Research Pillars: Algorithmic data mining, interpretable machine learning, time series classification, and health informatics Key Projects: AI for societal fairness, digital twins for smart buildings, EXTREMUM for explainable medical AI, and e-learning personalization Teaching Legacy: Developed courses in Data Mining (HT2013-2022), Machine Learning (VT2022-2024), and Health Informatics (VT2018-2021) His work focuses on interpretable AI for healthcare applications, particularly through counterfactual explanations for time series classification and forecasting. This includes developing methods like Glacier for constrained counterfactuals and Ijuice for k-justified explanations. His research also explores multimodal clustering of sepsis patient records and federated learning approaches for ICU mortality prediction. Recent scientific contributions include: CounterFair (2024): Group fairness analysis via counterfactual burden metrics M-ClustEHR (2024): Multimodal clustering for electronic health records COMET (2024): Constraint-based glucose forecasting explanations Temporal pattern mining (2024-2025): Enhanced forecasting models through decomposition Z-Time (2024): Interpretable multivariate time series classification His editorial leadership includes: Action Editor at Machine Learning Journal (since 2024) Action Editor at Data Mining and Knowledge Discovery (since 2018) Guest Editorial Board for ECML/PKDD Journal Track (2014-2019)
