Find Academic Supervisors

• Structural Equation Modeling
• Bayesian Statistics
• Psychometrics
• +3 more

Sonja D. Winter is an Assistant Professor in the Statistics, Measurement, and Evaluation in Education program at the University of Missouri’s College of Education and Human Development. She holds a Ph.D. in Quantitative Methods, Measurement, and Statistics from the University of California-Merced and completed a postdoctoral fellowship at the Missouri Prevention Science Institute. Her research focuses on advancing Bayesian statistical methods, particularly structural equation modeling (SEM), with an emphasis on prior sensitivity analysis, longitudinal data analysis, and addressing challenges in educational research such as small samples and missing data. Key areas of expertise include Bayesian methods, psychometrics, and the application of advanced quantitative techniques to educational and developmental psychology data. She leads the Winter Lab, which explores Bayesian SEM, measurement invariance, and the integration of prior knowledge through frameworks like prior predictive checks. Her work emphasizes methodological rigor, including evaluating model fit indices and addressing overfitting/underfitting issues. She collaborates on projects involving LGBTQ+ community inequities, school discipline equity, and teacher stress measurement. Active in both research and education, Winter teaches graduate courses on measurement and Bayesian methods while advocating for transparent and reproducible statistical practices.

Wes BonifayView profile

Associate Professor

• Psychometrics
• Item Response Theory
• Measurement
• +2 more

Wes Bonifay is an Associate Professor in the Educational, School & Counseling Psychology department at the University of Missouri's College of Education & Human Development. His research focuses on psychometrics, measurement theory, and statistical modeling in educational contexts. Research areas include: Item Response Theory methodologies Bayesian statistical approaches Psychometric model evaluation Measurement precision in assessments Meta-analytic techniques for educational research His recent publications examine innovative approaches to psychometric modeling, including Bayesian applications, parsimonious model development, and methodological critiques. Research spans educational measurement, clinical assessment, and methodological innovation in psychological research.

Manfred ReichertView profile

Professor

• Business Process Management (BPM)
• Service-Oriented Architectures
• E-health
• +7 more

Prof. Manfred Reichert is a full professor at the University of Ulm, serving as Director of the Institute of Databases and Information Systems and Dean of Studies at the Faculty of Engineering and Computer Science. He holds dual expertise in Computer Science and Mathematics, with academic leadership roles including chairing examination boards and strategic research initiatives. His interdisciplinary affiliations include co-opted membership in the Faculty of Mathematics and Economic Sciences. Reichert's research focuses on Business Process Management (BPM), IoT-driven processes, service-oriented architectures, and e-health applications. Notable contributions include co-developing the ADEPT process management system and pioneering object-centric process modeling. He has led over 20 international research projects (EU FP7, DFG, Industry) and authored >200 peer-reviewed papers, earning an h-index of 60+ and prestigious awards like the Merckle Forschungspreis. Education: PhD in Computer Science & Mathematics Diploma Leadership: Former associate professor at University of Twente, former director of CTIT research center Service: Conference chair for BPM, CoopIS, EDOC; steering committee member for GI SIG Databases Recent work explores IoT integration in BPM, generative AI for process models, and neuroscience-informed usability studies. His research bridges technical innovation with human-centric design, addressing challenges in process lifecycle management, federated learning, and mobile health interventions. Awards: IFIP TC2 Manfred Paul Award, doIT Software Award Key Projects: BPMN extensions for IoT, data-driven healthcare solutions

• Environmental Law
• Environmental Justice
• Administrative Law
• +5 more

Rebecca Bratspies is a Professor at the City University of New York (CUNY) School of Law and founding Director of the Center for Urban Environmental Reform (CUER). An internationally recognized expert on environmental justice, administrative law, and the human right to a healthy environment, she has authored numerous law review articles, op-eds, and books, including Environmental Justice: Law, Policy & Regulation . Her work bridges legal theory with grassroots advocacy, focusing on urban sustainability, biotechnology regulation, and equity in disaster recovery. Education: B.A. in Biology from Wesleyan University; J.D. cum laude from the University of Pennsylvania. Affiliations: Center for Progressive Reform, Global Network for the Study of Human Rights and the Environment, International Journal of Law in Context editorial board. Research spans environmental justice, climate policy, and the intersection of law with biotechnology. She advocates for decolonizing legal pedagogy and addressing systemic racism in administrative law. Her projects include community-driven initiatives like the We All Count census engagement comic book. Publications highlight global environmental governance, single-use plastic regulation, transboundary harm, and the role of precautionary principles in sustainability. Her work increasingly addresses climate justice, urban policy, and equity in energy transitions. Scientific Awards: Luce Scholar Contact: bratspies@law.cuny.edu

• Mental Health Services
• Substance Abuse Treatment
• Health Services Research
• +7 more

Mary Jo Larson serves as Senior Research Scientist II at the Institute for Behavioral Health, Brandeis University, specializing in health services research focused on mental health, substance abuse, and military healthcare systems. Her work examines access, quality, and cost of care for vulnerable populations including military service members, veterans, and those experiencing homelessness or incarceration. Her educational background includes a Ph.D. from Brandeis University and a Master of Public Administration from Harvard University's John F. Kennedy School of Government. Dr. Larson's research centers on mental health services delivery, substance abuse treatment systems, and integrated care models. She has particular expertise in military and veterans' health, studying post-deployment health outcomes, opioid prescribing patterns, and complementary health approaches. Her work frequently addresses disenfranchised populations through longitudinal studies and clinical trials, including a major investigation of military members returning from deployment and a pilot trial on academic detailing for opioid prescribers. Analysis of her recent publications reveals consistent focus on military health systems, opioid crisis interventions, and mental health policy. Key trends include examination of nonpharmacologic pain treatments, impacts of healthcare reform on mental health access, and innovative harm reduction strategies for substance use disorders, with strong emphasis on real-world clinical implementation. Her scientific contributions have been recognized through: Leadership Fellow, Bush Foundation (1983-1984) Predoctoral Trainee in Mental Health Economics, National Institute of Mental Health (1985-1987) Lucius N. Littauer Fellow, Harvard University (1985) Best in Theme abstract award, AcademyHealth (2010) Dr. Larson secures research funding for primary data collection and secondary analyses examining addiction care systems, integrated services for co-occurring disorders, and military health outcomes. She teaches global mental health policy and has directed feasibility studies of web-based training for mental health clinicians, demonstrating commitment to both research translation and workforce development. She currently leads a longitudinal study of military deployment impacts and designs clinical interventions like her academic detailing program for opioid prescribers, working closely with military healthcare systems and community organizations serving vulnerable populations.

Zhoulai FuView profile

Associate Professor

• Programming Language Theory and Implementation
• Program Analysis
• Testing and Verification
• +5 more

Zhoulai Fu is a tenured Associate Professor at the State University of New York (SUNY), Korea, specializing in programming languages and software security. He also holds joint appointments as a Research Associate Professor at Stony Brook University and is affiliated with the Electrical and Computer Engineering Department at Virginia Tech. His educational background includes: Ph.D., 2009-2013, INRIA – Université de Rennes 1, France M.Eng., 2008-2009, Télécom ParisTech, France M.S, B.S, and French engineer degrees (Ingénieur), 2005-2008, École Polytechnique, France Professor Fu's research focuses on the intersection of Programming Languages, Software Security, and Large Language Models, with special emphasis on improving software reliability through formal methods, numerical error analysis, and scalable verification techniques . His work spans abstract interpretation, automated testing, and verification tools development. He has made significant contributions to floating-point analysis and program verification, with publications at top-tier conferences including PLDI, POPL, OOPSLA, ICSE, and CAV. His publication record shows a consistent trajectory in programming language theory with increasing practical applications. Early work focused on foundational aspects of abstract interpretation and floating-point analysis, while recent papers address security concerns through programming language techniques and incorporate modern approaches like incorrectness logic. Key themes across his publications include formal verification of low-level code, numerical error analysis, and developing scalable analysis tools for real-world software systems. His notable achievements include: Principal Investigator for DARPA E-BOSS Program funding Sole Principal Investigator for National Research Foundation of Korea funding Program Committee membership for POPL 2026, FSE 2024, and PLDI 2023 Professor Fu actively mentors students and has taught courses including Foundations of Computer Science, Programming Abstractions, and Research in Computer Science. His research is supported by significant grants from DARPA and NRF, enabling him to lead the Data & Intelligent Computing Lab at SUNY Korea. He is currently seeking postdocs, PhD, and graduate students to join his research team. He leads the Data & Intelligent Computing Lab, which focuses on advancing programming language techniques for software reliability and security. The lab collaborates with institutions including Virginia Tech, Stony Brook University, and international partners across Europe, working on projects that bridge theoretical computer science with practical software engineering challenges.

Joanna DelicarisView profile

Researcher

• Formal Verification
• Stochastic Systems
• Hybrid Systems
• +2 more

Joanna Delicaris is a Researcher (PhD Student) at the University of Münster, focusing on reachability analysis and optimal reachability probabilities in stochastic hybrid automata with continuous nondeterminism. She is also investigating hybrid Petri nets and their extensions, particularly their relationship with hybrid automata in the context of stochastic and nondeterministic behavior. Developing the RealySt tool for computing reachability probabilities in stochastic hybrid systems Collaborating with Prof. Dr. Anne Remke and colleagues on interdisciplinary projects Her research bridges formal verification, stochastic modeling, and hybrid system analysis. She has contributed to multiple publications on topics such as rectangular automata with random clocks and state-space construction techniques. Joanna co-teaches courses including: Modeling and Analysis of Dynamical Systems Discrete Structures Efficient Model Checking of Stochastic Hybrid Systems

Jaeung SimView profile

Assistant Professor

• Information Systems
• Digital Marketing
• Online Platforms
• +4 more

Jaeung Sim is an Assistant Professor at the University of Connecticut's School of Business, Department of Operations and Information Management. His research focuses on understanding consumer interactions with information technology, digital platforms, and energy systems, with emphasis on sustainable operations and policy implications. He holds a Ph.D. in Management Engineering from KAIST and a B.S. in Industrial & Management Engineering (Summa Cum Laude) from POSTECH. Prior to academia, he served in the Republic of Korea Army as a sergeant and published data analytics work on music streaming trends. Research interests include: Online platform governance and consumer behavior Digital marketing strategies Energy economics and policy analysis Econometric field experiments Data-driven decision-making in operations Recent work explores topics like AI ethics in knowledge sharing, autocomplete impact on search behavior, smart metering effectiveness, and racial disparities in energy burdens. His music analytics research examines pandemic effects on streaming consumption and live-streaming economies. Teaching includes courses on data mining/business intelligence (OPIM 5671) and Python-based data science (OPIM 5512). Active in UConn's Stamford campus, he contributes to initiatives like decentralized AI education programs.

Wang FengjiaoView profile

Assistant Professor

• Machine Learning
• Data Mining
• Social Network Analysis
• +3 more

Wang Fengjiao is an Assistant Professor and Lecturer at the Kahlert School of Computing, University of Utah. Her research focuses on machine learning, data mining, and social network analysis, with notable contributions to semi-supervised learning, generative models, and social media analysis. She holds a position in one of the founding institutions of the internet (ARPANET), leveraging computational advancements for interdisciplinary challenges. Her work spans theoretical innovations and applied systems, including algorithms for tabular data, image generation via Fréchet distance minimization, and probabilistic text recommendation models. Recent trends in her publications emphasize scalable learning frameworks, spatial-temporal event modeling, and privacy-preserving techniques in multi-platform social networks. Wang's research has addressed challenges such as user geolocation inference, collaborative co-clustering in heterogeneous data, and steering information diffusion under attention constraints. Her contributions to content-aware POI recommendations and distance-based social discovery further highlight her expertise in integrating machine learning with real-world social systems. No scientific awards or grants are explicitly mentioned in the provided materials. Contact information is available at fengjiao@cs.utah.edu, and her office is located in MEB 3102.

Tala KasimView profile

Senior Lecturer

• Digital Construction
• BIM (Building Information Modeling)
• Health and Safety Compliance
• +5 more

Dr. Tala Kasim is a Senior Lecturer in Civil Engineering at Aston University's College of Engineering and Physical Sciences. She holds roles including Deputy Head of Department for Operations and Programme Director for the MSc Civil Infrastructure Engineering. Her research focuses on digital construction, BIM applications, automated compliance systems, and sustainable design. She has conducted Innovate UK-funded projects with Arcadis Ltd and collaborates with Heriot-Watt University on supply chain integration. Kasim teaches modules like BIM for Construction and Digital Engineering, and supervises PhD students. She is an External Examiner at Coventry University and has professional certifications including CEng, MICE, and FHEA. Education: PhD (BIM-based Compliance, Cardiff University), MSc (Energy Performance, University of South Wales), BSc (Aston University) Research Projects: BIM-based health and safety compliance systems, digital lab management platforms, pavement design automation Her work emphasizes improving construction productivity through digital tools and advancing safety management via automated regulatory checks. Over 12 research outputs span topics from AI in construction to sustainable building frameworks. Awards: None explicitly noted Grants: Innovate UK funding for BIM compliance project, collaborative grants with industry partners

• Operating Systems
• Fault Tolerance
• Cyber-Physical Systems
• +5 more

Marcus Völp is an Associate Professor and head of the CritiX research group at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT). His research focuses on ultra-reliable operating systems, fault and intrusion tolerant systems for cyber-physical environments, and hierarchical hybridization techniques to construct resilient computing platforms. His work bridges theoretical foundations with practical implementations, particularly in developing dependable systems-on-chip that can withstand faults and intrusions. Research spans formal verification methods, radiation-hardened hardware, blockchain security, and autonomous vehicle safety systems. Recent publications demonstrate advancement in parameterized system verification, radiation effects on routers, and N-version machine learning for autonomous systems. His group maintains strong focus on practical resilience mechanisms for real-time and critical systems across computing layers.

Perry AlexanderView profile

Professor

• Formal Methods
• System-Level Design
• Cybersecurity
• +5 more

Warren P. Alexander is the AT&T Distinguished Professor at The University of Kansas, specializing in formal methods applied to system-level design. His research focuses on ensuring reliable, secure, and trustworthy computer systems through mathematical methodologies, tool development, and curriculum integration. He emphasizes pragmatic engineering approaches to formal techniques, including protocol design and verification. Key research interests include remote attestation protocols, cybersecurity assurance, and trusted computing architectures. His work bridges theory and practice, with contributions to frameworks like Rosetta and Copland for system design and verification. Dr. Alexander’s publications span formal verification, system-level design, and cybersecurity, reflecting a commitment to advancing both academic and industrial applications of rigorous system design principles.

René WesterholtView profile

Assistant Professor

• Spatial Analysis
• GIScience
• Urban Analytics
• +7 more

René Westerholt is an Assistant Professor (Juniorprofessor) in Spatial Modelling at the Department of Spatial Planning at Technische Universität Dortmund, Germany. He also leads the Spatial Modelling Lab (RAM) and is affiliated with the GIScience research group at Heidelberg University. His academic background includes a PhD in Geography from Heidelberg University and an M.Sc. in Geoinformatics from Osnabrück University. His research focuses on spatial analysis methodologies, particularly integrating social dimensions into quantitative analysis. Key areas include geosocial media data analysis, spatial autocorrelation, and urban analytics. He has interdisciplinary experience in software development for nature conservation and agricultural projects, and is active in professional societies like the Royal Geographical Society and DGPF. Teaching responsibilities include leading the M.Sc. Urban Analytics and Visualisation programme at the University of Warwick and courses such as IM913 Spatial Methods and IM927 Digital Cities. His work bridges theoretical GIScience with practical applications in urban planning and environmental studies.

Charles GrelloisView profile

Lecturer

• Program Verification
• Formal Semantics
• Probabilistic Programming
• +2 more

Charles Grellois is a Lecturer in Verification at the University of Sheffield's Department of Computer Science. His research focuses on formal verification methods for functional and probabilistic programs using semantic and type-theoretic approaches. Research interests include program verification, linear logic, higher-order model checking, and termination analysis of probabilistic programs. Collaborates with medical researchers on mathematical modeling for cancer treatment prediction. Publications appear in computer science logic conferences including CSL and MFPS. Current work develops proof systems for bringing-it-about logics and intuitionistic deontic logic.

Vishnu PendyalaView profile

Professor

• Machine Learning
• Artificial Intelligence Ethics
• Big Data Analytics
• +3 more

Professor Vishnu Pendyala is a tenured faculty member at San José State University (SJSU), serving as a Senator in the Academic Senate and Chair of the IEEE Computer Society, Santa Clara Valley Chapter. His academic roles include teaching graduate courses in Machine Learning (DATA 245), Big Data Technologies (DATA 228), and Data Warehousing (DATA 226). He holds dual expertise in Computer Engineering and Data Analytics, straddling the College of Engineering and the Data Science programs. His research focuses on AI ethics, misinformation detection, and sustainable AI , with over 100 publications and keynote addresses at IEEE, ACM, and Springer conferences. Notable contributions include frameworks for combating misinformation, quantifying AI's environmental impact, and promoting equitable AI development. Pendyala is a IEEE Distinguished Contributor and ACM Distinguished Speaker , emphasizing interdisciplinary collaboration in his work. Recent trends in his articles reflect growing attention to AI's societal implications, such as ethical governance, environmental sustainability, and policy reforms. He actively engages with media (Newsweek, The Hill) and policymakers to translate technical insights into public discourse. Pendyala’s service roles include leadership in academic senate committees and global IEEE chapters, advocating for equitable educational and research practices. Education: PhD, MS, BS in Computer Engineering and MBA in Finance. His work bridges technical innovation with societal responsibility, addressing challenges such as AI-driven democracy, ecological footprint mitigation, and global data governance.