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Süleyman Sadi SEFEROGLUView profile

Professor

• Educational Technology
• Computer Education
• Instructional Technologies
• +5 more

Dr. Süleyman Sadi SEFEROGLU is a Professor at Hacettepe University's Faculty of Education, Department of Computer Education and Educational Technologies in Ankara, Turkey. With an extensive publication record spanning over two decades, he has established himself as a leading scholar in educational technology and digital transformation in education. His research interests focus on educational technology, computer education, instructional technologies, digital transformation in education, information and communication technologies, digital literacy and citizenship, technology policy, and artificial intelligence applications in education. His work bridges theoretical frameworks with practical applications in educational settings. Professor SEFEROGLU's recent publications (2022-2025) demonstrate a strong focus on contemporary challenges including digital addiction, AI in education, teacher technostress, digital risk behaviors, and the evolving landscape of educational technology. His research shows a clear trajectory toward understanding the psychological, social, and pedagogical implications of digital transformation in education. He has been actively involved in numerous international conferences as both presenter and invited speaker, reflecting his standing in the educational technology community. His work has increasingly addressed the intersection of emerging technologies like artificial intelligence with educational practice. Professor SEFEROGLU has supervised thesis and dissertation work, though specific student names are not detailed in the available information. His professional activities include participation in accreditation processes and educational policy discussions, particularly regarding Turkey's educational technology initiatives.

Josephine Chen-WilsonView profile

Senior Lecturer

• Developmental Psychology
• Educational Psychology
• STEM Education
• +7 more

Dr Josephine Chen-Wilson is a Senior Lecturer in Developmental and Educational Psychology at the University of Northampton, School of Psychology and Behavioural Sciences. She holds an Honorary Research Fellowship at the University of Wolverhampton (2020–2023) and is a national STEM ambassador. Education: Joint Honours Degree in Psychology and Education (University of Warwick); PhD in Psychology (University of Manchester, supported by Graduate School of Science, Engineering and Medicine scholarship) Her research focuses on three strands: self-concept clarity and online self-presentation (POSS), emotion and health behavior (#FoodMoodnYou), and science capital's impact on STEM aspirations in primary school children. Her work spans cross-cultural collaborations in Europe and East Asia, with a focus on pandemic-related behavioral changes and STEM outreach. Key article trends include: Validation of emotional eating scales across language groups Remote interventions for managing food cravings during lockdowns Gender perceptions in science education Teacher self-efficacy in STEM instruction Intergenerational learning environments Scientific awards include Graduate School of Science, Engineering and Medicine scholarship Honorary Research Fellowship, University of Wolverhampton She has supervised 20 doctorate students to completion and co-founded STEM initiatives Girls4Science (University of Wolverhampton) and STEM4Me (University of Northampton).

• Educational Psychology
• Teacher Education
• Assessment and Testing
• +5 more

Elaine Radmer, Ph.D., serves as an Associate Professor in the Teacher Education department within the School of Education at Gonzaga University. Her academic work critically examines test-based education reform, organizational accountability, and societal inequities in schooling systems. Her educational background includes: Ph.D. in Educational Psychology, Washington State University M.A. in International Studies and Teaching English as a Second Language, Wheaton College B.A. and B.S. in Education & Biology, Eastern Washington University A.A., Walla Walla Community College Radmer's research interrogates unexamined assumptions in educational institutions and explores how humans learn in social settings beyond formal schools. She champions collaborative inquiry into assessment practices and investigates culturally responsive pedagogy, particularly through young adult literature's impact on reading comprehension. Her work consistently addresses power dynamics, privilege, and strategies for making schools responsive to diverse learners. Her publication trajectory reveals evolving focus from classroom-level assessment (2012-2017) toward systemic leadership and equity (2018-2024), with recent emphasis on data-informed attendance systems, culturally intelligent leadership, and perseverance in re-engaged students. This progression demonstrates increasing engagement with institutional change while maintaining core commitments to equity and teacher empowerment. No major scientific awards are documented in available sources. Radmer actively mentors student researchers, as evidenced by asterisked co-authors across her publications spanning literacy, mathematics education, and leadership studies. Her collaborative projects with colleagues like Darragh, Garoui, and Conlin reflect sustained engagement with K-12 practitioners, though specific grant funding details aren't provided. Conference presentations at AERA and WERA demonstrate consistent scholarly dissemination. Her work involves cross-disciplinary partnerships with librarians, mathematics educators, and literacy specialists through professional organizations including AERA and WERA, focusing on practical applications of research in school settings.

Joachim BaumeisterView profile

Professor

• Semantic Information Systems
• Knowledge Graphs
• Deep Learning
• +5 more

Joachim Baumeister is a Professor at the Chair of Computer Science VI - Artificial Intelligence and Knowledge Systems within the Institute of Computer Science at the University of Würzburg's Faculty of Mathematics and Computer Science. While his primary employment since September 2010 has been at denkbares GmbH, a company specializing in knowledge-based systems, he continues to regularly give lectures at the university. His research focuses on Semantic Information Systems, Knowledge Graphs, Deep Learning applications, Natural Language Processing, and Knowledge-based Configuration for Industry 4.0. Professor Baumeister's work bridges theoretical AI research with practical industry applications, particularly in knowledge-based configuration systems and semantic technologies. His recent publications (2020-2024) reveal a strong emphasis on product configuration systems, semantic knowledge representation, regulatory document processing, and knowledge-based systems. His research has evolved from foundational work on semantic wikis and knowledge engineering to more recent applications involving deep learning and large language models, demonstrating adaptability to emerging technologies while maintaining focus on practical knowledge representation problems. Professor Baumeister's work demonstrates significant contributions to case-based reasoning, knowledge configuration, and semantic technologies, with applications spanning regulatory compliance, industrial configuration systems, and document processing. His current research areas include: Semantic Information Systems and Knowledge Graphs Deep Learning for Image Recognition and Language Understanding Knowledge-based Configuration for Industry 4.0 Natural Language Processing Intelligent Personal Assistants and Chat Bots Though specific students aren't listed in the provided information, Professor Baumeister actively invites students to contact him regarding projects, bachelor theses, and master theses in his areas of expertise. His work at denkbares GmbH focuses on the design, implementation, and evolution of knowledge-based systems and semantic information systems.

Ryan MarcusView profile

Assistant Professor

• Machine Learning
• Query Optimization
• Index Structures
• +4 more

Ryan Marcus is an Assistant Professor in the Department of Computer and Information Science at the University of Pennsylvania. His research focuses on integrating machine learning into data management systems to create adaptive tools that optimize hardware utilization, invent novel processing strategies, and interpret user intentions. Currently based in Office 407, Amy Gutmann Hall, he actively explores query optimization, index structures, intelligent clouds, programming language runtimes, program synthesis for data processing, and reinforcement learning applications to systems challenges. Key research themes include machine learning for databases , learned query optimization , intelligent cloud systems , and blockchain adaptability . Scientific achievements include the Best Paper Award at SIGMOD '21 for the Bao system and the development of AutoSteer, a cross-database learned query optimizer. Notable PhD advisees co-advised include Peizhi Wu (with Zack Ives), Jeffrey Tao (with Andrew Head), and Zixuan Yi (with Zack Ives). His recent work, presented at venues like VLDB and SIGMOD, emphasizes scalable LLM-augmented data systems (ScaleLLM), robust cardinality estimation, and adaptive Byzantine fault-tolerant consensus (BFTBrain). For full system evaluations, he created testing environments such as BFTGym. Contact: rcmarcus@seas.upenn.edu

Benjamin PierceView profile

Professor

• Programming Languages
• Type Systems
• Language-based Security
• +4 more

Benjamin Pierce is the Henry Salvatori Professor in the Department of Computer and Information Science at the University of Pennsylvania. His research spans programming languages, formal verification, and sustainable computing, with a focus on practical applications in software reliability and security. He leads initiatives like Carbon Connect (NSF Expedition in Sustainable Computing) and serves on climate-focused committees such as Penn's Faculty Senate Select Committee on the Climate Emergency. Research Interests Pierce's work integrates theoretical and applied computer science, emphasizing: Programming Languages : Type systems, language-based security, and compiler verification Formal Methods : Computer-assisted verification, proof automation, and property-based testing Sustainability : Reducing computing's environmental impact through algorithmic efficiency and policy Recent Publications His 2023-2025 publications demonstrate a strong focus on enhancing software testing (e.g., Tyche for property-based testing), advancing formal verification tools (e.g., Coq deautomation), and pioneering sustainable computing frameworks. Climate-related research is a growing theme. Awards and Honors 2024: Distinguished Paper Award (ICSE) 2020: Best Paper Award (POPL) 2015: Most Influential Paper Award (ACM SIGPLAN) 2013: LICS Test of Time Award 2012: ACM Fellow Advising and Grants He advises 8 PhD students on topics ranging from type systems to verified compilation. Notable projects include: NSF-funded Carbon Connect expedition SHF grant for usable property-based testing Development of verification tools (VERSE, Unison) Professional Activities Serves on editorial boards for Journal of Functional Programming and Logical Methods in Computer Science , and organizes major conferences (PLDI, POPL, OOPSLA). Advocates for low-carbon virtual conferences.

Thomas EiterView profile

Professor

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Computational Logic
• +7 more

Thomas Eiter is a Full Professor at the Institute of Logic and Computation, Technical University of Vienna (TU Wien), where he serves as Head of Research Unit. He is a Full Member of the Division of Mathematics and Natural Sciences since 2022 and holds leadership roles within the university. His research focuses on knowledge representation and reasoning, computational logic, algorithms and complexity in AI, declarative problem solving, nonmonotonic logic programming and databases, and reasoning about actions and change. His work bridges theoretical foundations with practical applications in artificial intelligence, particularly in logic programming and knowledge-based systems. He has made significant contributions to Answer Set Programming (ASP), developing frameworks like DLV and HEX programs that enable sophisticated reasoning capabilities. His recent publications demonstrate a strong focus on stream reasoning (LARS framework), knowledge forgetting, modular reasoning systems, and the integration of logic programming with ontologies. His research shows consistent contributions to both theoretical foundations and practical implementations of AI systems over several decades. ACM Fellow (2020) Fellow of the European Association for AI (2006) Distinguished Paper Award of the 17th International Joint Conference on Artificial Intelligence (IJCAI, 2001) Prominent Paper Award of the Artificial Intelligence Journal (2013) Test of Time Award (10 years) of the International Conference on Logic Programming (2013) Eiter has led and participated in numerous research projects, both internationally funded (such as LogiCS@TUWien, Humane AI, AI4EU) and nationally funded (including projects like BILAI, TAIGER, and several FWF-funded initiatives). His research unit has received substantial support from European Commission programs (H2020) and Austrian funding agencies (FWF, FFG, WWTF). He is actively involved in the academic community as a member of the Austrian Academy of Sciences (ÖAW), Academia Europaea, and has served on the Executive Council of AAAI. His research unit maintains strong connections with international collaborators and has developed influential systems like the DLV answer set programming system.

• Physiotherapy
• Neurological Rehabilitation
• Gerontology
• +5 more

Ana Isabel Vieira is an Adjunct Professor at the Alcoitão School of Health, where she serves as Director of the Department of Physiotherapy. She is affiliated with the Business Research Unit (BRU-ISCTE) - Data Analytics Group, integrating academic, clinical, and community-focused roles. Her career spans over three decades in physiotherapy practice and education. Bachelor's in Physiotherapy (1990, Alcoitão School of Health) Postgraduate in Psychomotricity and Therapeutic Relaxation (1994, Faculty of Human Kinetics) Master's in Educational Sciences - Health Education (2006, University of Lisbon) PhD in Health Sciences - Neurological Rehabilitation (2017, Catholic University of Portugal) Her research focuses on neurological rehabilitation , gerontological physiotherapy , and community health initiatives . Notable work includes tactile discrimination studies in elderly populations, social touch assessment tools, and multidisciplinary aging research. She leads projects addressing dementia prevention , community accessibility , and informal caregiver support . Recent publications demonstrate her engagement with frailty assessment , post-stroke rehabilitation , and oral-motor dysfunction in aging populations. Her work has been published in journals like Journal of Oral Rehabilitation and Physiotherapy Theory and Practice. Career Award (2018, Alcoitão Higher School of Health) Performance Bonus (2009, Holy House of Mercy of Lisbon) Honorable Mention for Communication (2009, XXII Taipas Meeting) An active academic mentor, she supervises multiple Master's theses and serves on doctoral juries. Her professional activities include community projects like Cascais Cuida , Tango Argentino in Parkinson's , and SIRS (Solidão e Isolamento em Idosos) . She participates in international research networks including the World Wide Fingers project.

Benjamin C. PierceView profile

Professor

• Programming Languages
• Type Systems
• Language-based Security
• +5 more

Benjamin C. Pierce is the Henry Salvatori Professor of Computer and Information Science in the School of Engineering and Applied Science at the University of Pennsylvania. As a Fellow of the ACM, he has made significant contributions to programming language theory and formal methods. His academic leadership includes previous editorial roles as co-Editor in Chief of the Journal of Functional Programming and Managing Editor for Logical Methods in Computer Science. His research spans multiple interconnected domains in programming language theory, with particular emphasis on type systems and their applications to security and verification. Pierce's work bridges theoretical foundations with practical implementations, most notably through his development of the Unison file synchronization tool and contributions to the Clowdr virtual conference platform. His research interests form a cohesive trajectory from foundational type theory to applied security and verification techniques. Pierce's scholarly output shows consistent focus on property-based testing, type systems, and formal verification methods. His recent publications demonstrate evolving interests in differential privacy verification, synchronization technologies, and the practical challenges of implementing formal methods in real-world systems. The progression of his work reflects both theoretical depth and practical relevance to software development challenges. Fellow of the ACM Author of influential textbooks Types and Programming Languages and Software Foundations Lead designer of the Unison file synchronizer Co-developer of the Clowdr virtual conference platform Former editorial leadership for multiple prominent programming languages journals As an educator and mentor, Pierce has contributed to the Programming Languages Mentoring Workshop (PLMW) and has served on numerous conference program committees. His academic service extends to SIGPLAN leadership roles including SIGPLAN Vice Chair and Steering Committee membership. His textbook Software Foundations has become a standard resource for teaching formal methods and proof assistants.

Madi BabaiaslView profile

Assistant Professor

• Human intention detection
• Human-robot interaction
• Rehabilitation robotics
• +7 more

Madi Babaiasl is a Clare Booth Luce Assistant Professor in the Department of Aerospace and Mechanical Engineering at Saint Louis University's School of Science and Engineering. Her research focuses on developing innovative robotic solutions for assistance, rehabilitation, agriculture, and education applications. Education: Ph.D. in Mechanical Engineering (Robotics) from Washington State University M.S. in Mechatronics Engineering from Tabriz University, Iran B.S. in Electrical Engineering from Tabriz University, Iran Dr. Babaiasl's research spans multiple domains at the intersection of robotics, machine learning, control theory, and artificial intelligence. Her primary focus centers on developing safe and efficient human-robot interaction systems, particularly for assistive and rehabilitation applications. She investigates human intention detection, agricultural automation, and novel approaches to robotics education, integrating knowledge from psychology, physical therapy, agriculture, and education to create comprehensive robotic solutions. Her work addresses real-world problems such as developing devices to suppress hand tremors for Parkinson's patients and creating steerable needles for surgical applications. Analysis of her recent publications (2022-2025) reveals a clear evolution from medical robotics (particularly steerable needles) toward more diverse applications including assistive and agricultural robotics. The newer publications increasingly incorporate advanced AI techniques like transformer models, large language models, and multimodal signal processing for human-robot interaction, with strong emphasis on practical implementation using ROS2, edge computing, and real-time control systems for applications where cloud connectivity may be limited. Scientific Recognition: Featured in RSIP Vision Magazine as a Woman in Science (January 2022) Featured in SWE's 'A Day in The Life of Robotics Engineer' blog (April 2022) Multiple features in university publications for steerable needle research (2018-2019) Wanda Munn Scholarship for outstanding academic achievement (2019) Top 0.2% in national university entrance exams in Iran (2006) Recent lab achievements including Midwest Robotics Workshop 2025 Travel Grant (2025) Dr. Babaiasl actively mentors students through her Mecharithm Lab at SLU, seeking those with robotics foundations, programming skills (particularly Python), and familiarity with ROS. She has successfully blended academic and entrepreneurial pursuits by founding Mecharithm in 2021, which generated $73,000 in its first year. Her mentorship philosophy emphasizes project-based learning, self-directed growth, and developing as an independent researcher. Leading the Mecharithm Lab, Dr. Babaiasl oversees research projects including WheelArm (enhancing independence in assistive robotic systems), multi-modal human intent recognition, and deploying large language models for intuitive human-robot interaction. Her lab comprises graduate and undergraduate students primarily from Mechanical Engineering and Computer Science backgrounds, working on meaningful projects that aim to leave a lasting legacy for society through robotics innovation.

• Neuropsychology
• Frontal Lobe Functions
• Executive Functions
• +7 more

Philippe Allain is a University Professor at the University of Angers, France, where he serves in the Psychology Department within the UFR of Letters, Languages and Human Sciences. He co-directs the Master's course in Neuropsychology and leads the Laboratory of Psychology of the Pays de la Loire (LPPL, EA 4638). Additionally, he serves as a neuropsychologist at the CHU Angers in the Department of Neurology, focusing on neurosciences, aging, and medicine. His research centers on the neuropsychology of the frontal lobes from both cognitive (executive functions and cognitive control) and socio-behavioral (social cognition, behavioral and emotional regulation) perspectives. His work follows three main axes: theoretical models of frontal functioning, development of evaluation tools for frontal dysfunctions, and studies on normal and pathological aging of cognitive functions. His recent publications demonstrate a strong focus on Alzheimer's disease, Huntington's disease, schizophrenia, and aging-related cognitive changes. His 15 most recent publications reveal a consistent research trajectory examining memory processes, executive functions, and social cognition across various neurological conditions. Notably, he has published extensively on Alzheimer's disease (6 articles), Huntington's disease (3 articles), and schizophrenia (1 article), with increasing use of innovative methods like pupillometry and virtual reality for cognitive assessment. His work frequently involves international collaborations and appears primarily in Q1 and Q2 journals. President of the French Language Neuropsychology Society (SNLF) Professor Allain has supervised 17 doctoral theses (9 funded) with diverse topics including social cognition in schizophrenia, virtual reality assessment of social cognition, geriatric living labs, sensory deficit rehabilitation, and Huntington's disease. His research has been supported by various grants, including European Huntington's Disease Network collaborations. He currently supervises 6 doctoral students and leads the LPPL research laboratory. He directs the Laboratory of Psychology of the Pays de la Loire (LPPL, EA 4638) and has been instrumental in developing the ALLEGRO hospital-based geriatric living lab. His work integrates clinical practice with research, particularly through his dual role at the University of Angers and CHU Angers, creating a strong bridge between academic research and clinical neuropsychology practice.

Jie WangView profile

Professor

• Algorithms
• Text Mining
• Computational Complexity
• +7 more

Jie Wang is a Professor of Computer Science at the University of Massachusetts Lowell's R. Miner School of Computer and Information Sciences. He joined UMass Lowell in 2001 as a Full Professor and chaired the department for 9 years from 2007 to 2016. He serves as Director for China Partnership of the US-based Consortium for Mathematics and Its Applications (COMAP) since 2011. Prior to UMass Lowell, he was Assistant Professor and then Associate Professor of Computer Science at the University of North Carolina. Professor Wang's research spans multiple areas including text mining algorithms and systems, data modeling, combinatorial optimizations, network security, wireless sensor networks, and computational complexity theory. His work has evolved from theoretical foundations in computational complexity (1980s-early 2000s) to practical applications in data analysis, intelligent text automation, and AI systems. His recent publications focus on AI-Oracle machines, LLMs, text mining, document engineering, and network security. His research portfolio demonstrates a clear evolution from theoretical computer science to applied research with practical impact. The publications show increasing focus on AI, text mining, and document engineering in recent years, while maintaining foundations in algorithm design and network security. His work bridges theoretical computer science with real-world applications across multiple domains. Honorary Advisor (2013) - NeoUnion Hong Kong Education Science Culture Organization MHE Scholar (2012) - Ministry of Higher Education, China PMYR Award for Major New Initiatives (2010) - University of Massachusetts Lowell Teaching Excellence Award (2002) - University of Massachusetts Lowell Nominee of Board of Governors' Teaching Excellence Award (2000) - University of North Carolina Professor Wang has graduated 18 PhD students and is currently directing 5 PhD students. His research has been funded by the National Science Foundation, IBM, Intel, and other companies totaling approximately $4.8 million. He is active in professional service, including chairing conference program committees, serving as journal editors, and as editor-in-chief of a book series on mathematical and interdisciplinary modeling. His laboratory work focuses on text mining systems, network security applications, and computational models for practical problems.

Amery WuView profile

Associate Professor

• Applied Statistical Modeling
• Psychometrics
• Educational Measurement
• +4 more

Amery Wu serves as Associate Professor and ECPS Graduate Advisor for Admissions and Scholarship at the University of British Columbia's Faculty of Education, specifically within the Department of Educational and Counselling Psychology, and Special Education. Based in Scarfe Library Block 287, Dr. Wu specializes in advanced quantitative methods for educational and psychological measurement. Dr. Wu's research focuses on applied statistical modeling in educational contexts, with particular expertise in test item performance analysis , globalization of testing through internet platforms , and longitudinal assessment methodologies . Their scholarly work bridges psychometrics with practical educational applications, examining how test design impacts diverse learner populations across international contexts. Key methodological contributions include innovations in mixed-effects modeling, differential item functioning analysis, and validation frameworks for complex assessment systems. Recent publications demonstrate a clear trajectory toward integrating response process data with performance outcomes , particularly through Bayesian modeling and advanced visualization techniques for online assessments. The research consistently addresses measurement challenges in high-stakes contexts including immigration language testing (CELPIP), health literacy instruments, and inclusive classroom models. Dr. Wu's work emphasizes the ecological validity of assessments within their sociocultural contexts. Teaching responsibilities include core methodology courses: EPSE 423 (Assessment of Classroom Learning), EPSE 481 (Introduction to Research in Education), EPSE 482 (Statistics for Educational Research), EPSE 483 (Reading Educational Research), and advanced graduate courses EPSE 592 (Experimental Designs) and EPSE 596 (Correlational Analysis). As Graduate Advisor for Admissions and Scholarship, Dr. Wu shapes the quantitative training of future educational researchers.

• Software Engineering
• Data Management and Data Science
• Information Systems
• +2 more

Earl Barr is a Professor of Software Engineering at the Department of Computer Science, University College London. His research focuses on software engineering, data management and data science, and neural software engineering approaches. Research Interests: Dr. Barr's work bridges traditional software engineering with modern machine learning techniques. He explores automated program repair, code summarization, log anomaly detection, and the application of neural models to software development workflows. His studies often address both practical challenges in industry and theoretical aspects of code analysis. Article Trends: His recent publications emphasize the integration of large language models (LLMs) into software engineering tasks, including fact selection for program repair, semantic prompt augmentation, and grid-based code representation. Other recurring themes include empirical studies of development practices, fuzzing techniques for program analysis, and the use of surprisal theory in issue tracking systems. Scientific Awards: ACM Sigsoft Distinguished Paper Award (2013) Best Paper Award - IEEE Conference on E-Commerce Technology (2005) I3P Fellowship (2009-10) Professional Activities: Dr. Barr has served as a visiting assistant professor at the University of California Davis (2013) and as a reviewer for top software engineering conferences and journals including ICSE, ISSTA, FSE, SAS, TOSEM, TSE, and the DARPA MURI Program. He also contributed to commercialization efforts through a patented approach leveraging statistical analysis from large software corpora for engineering tools.

Paul S. RosenbloomView profile

Professor

• Cognitive Architecture
• Artificial General Intelligence
• Hybrid Symbol Systems
• +4 more

Paul S. Rosenbloom is a Professor in the Department of Computer Science at the University of Southern California , with affiliations at the Institute for Creative Technologies . His work focuses on cognitive architectures , particularly the development of the Sigma architecture and contributions to the Common Model of Cognition . He has pioneered the integration of symbolic, probabilistic, and neural systems in AI research. Research Interests: Dr. Rosenbloom's research spans hybrid symbol systems , neural-symbolic integration , and the evolution of computational models of cognition . His recent work rethinks the Physical Symbol Systems Hypothesis through hybrid systems that bridge symbolic AI and neural networks, addressing challenges in universality , compositional reasoning , and cognitive modeling . Scientific Awards: 2011 Kurzweil Award for Best AGI Idea 2012 Kurzweil Award for Best AGI Paper 2023 Springer Prize for Best Paper Publications and Contributions: He has authored over 150 publications and co-authored foundational works on the Common Model of Cognition with Laird, Lebiere, and Stocco. His research has been supported by grants from the U.S. Army RDECOM and USC's Institute for Creative Technologies. He has mentored numerous collaborators and co-authors, including researchers like V. Ustun , A. Demski , and H. Joshi , in projects spanning virtual humans , reinforcement learning , and distributed vector representations .