Jennifer Mankoff is the Richard E. Ladner Professor at the Paul G. Allen School of Computer Science & Engineering, University of Washington. She previously held faculty positions at UC Berkeley’s EECS department and Carnegie Mellon’s HCI Institute. Her research focuses on accessibility, empowering disabled individuals through technologies like generative AI, 3D printing, and computational knitting. Education : PhD in Computer Science from Georgia Tech (advised by Gregory Abowd and Scott Hudson), BA from Oberlin College. Her work addresses technical challenges in accessibility across domains such as higher education, health, and DIY solutions. She leads the Make4All Group and the Center for Research and Education on Accessible Technology and Experiences (CREATE). Awards include the SIGCHI Social Impact Award, IBM Faculty Fellowship, and ASSETS 10-Year Impact Award. Scientific Awards : SIGCHI Social Impact Award Alfred P. Sloan Fellowship IBM Faculty Fellowship ASSETS 10-Year Impact Award CHI Academy Member Mankoff has mentored over 50 undergraduate and graduate students, including current faculty members like Julie Kientz and Gary Hsieh. She advocates for inclusive curriculum development, teaches courses on data-centric computing and HCI, and provides mentorship on navigating academia with disabilities. Contact : jmankoff@cs.uw.edu | jmankoff@acm.org | 206-685-3035
James Gordon is an Associate Teaching Professor at Arizona State University's School of Computing and Augmented Intelligence. He holds an M.S. (2006) and B.S. (2003) in Computing and Software Systems from the University of Washington. His teaching focuses on core computer science disciplines, including Operating Systems (CSE 330), Principles of Programming Languages (CSE 340), and introductory programming concepts like Data Structures and Algorithms (CSE 310). He has consistently taught these courses across multiple semesters since at least 2022, also coordinating practicum courses (CSE/SER 580) emphasizing hands-on learning. James has no listed scientific awards or publications, reflecting a strong emphasis on pedagogy and curriculum development. His academic contributions are centered on undergraduate and graduate teaching in foundational computing topics. Labs/teams: Involvement in practicum courses suggests engagement with applied computing projects, though specific lab affiliations are not explicitly mentioned.
Holger Wittges is the Managing Director of the SAP University Competence Center (UCC) at the Technische Universität München (TUM) . His work focuses on Digital Transformation , Next Generation ERP , and Hybrid Cloud infrastructure. He is affiliated with the KrcmarLab and collaborates with IBM via the OpenPOWER@TUM initiative. Educational Background: 2004: Dr. rer. oec. (Promotion), Universität Hohenheim 1996: Diplom Wirtschaftsinformatiker, Universität Bamberg Research Interests include Digital Transformation, Cloud Computing, Enterprise Resource Planning (ERP), XaaS (Everything as a Service), and Service-Oriented Architecture (SOA). His work bridges academic innovation with industry needs through SAP UCC TUM, which provides 40+ educational service bundles like SAP HANA and S/4HANA for teaching and research. Recent Publications highlight advancements in machine learning for ERP support ticket systems, energy efficiency in SAP S/4HANA, and educational frameworks for cloud-based enterprise software. Articles emphasize collaboration with institutions across Europe and contributions to digital ecosystems like the SAP University Alliances. Key Projects include the OpenPOWER@TUM initiative with IBM, focusing on accessible AI/ML infrastructure for academia, and the SAP UCC TUM, which drives Education as a Service (EaaS) strategies for digital business ecosystems.
Viktoriya Olari is a researcher at the Didactics of Computer Science department, Freie Universität Berlin. Her work focuses on artificial intelligence literacy, data literacy, and digital education frameworks for K-12 and teacher training programs. She contributes to projects like ENKIS, DigiProMIN, and TrainDL, emphasizing interdisciplinary approaches to computer science education. Key Projects: ENKIS, AMI, Digi4All, siMINT, AI@IT2School Her recent publications address pedagogical methods for AI/data literacy integration, teacher professional development, and physical computing in education. She holds weekly consultation hours for students and maintains research partnerships across Germany. Research Themes: AI education in schools, data-driven pedagogy, digital transformation of teacher training
Ke Yang serves as Assistant Professor in the Department of Computer Science at the University of Texas at San Antonio (UTSA), College of Sciences. He founded and leads the Cohort for AI REsponsibility (CAREAI) initiative, while also holding core faculty positions in UTSA's School of Data Science and MATRIX (AI Consortium for Human Well-being). Education: Ph.D. from New York University (supervised by Prof. Julia Stoyanovich) Research Focus: Dr. Yang's work centers on AI trustworthiness and responsibility , with specialized expertise in algorithmic fairness, data ethics, and human-centered data science. His research addresses critical challenges including Large Language Model hallucinations, explainable AI frameworks, and algorithmic accountability mechanisms. He actively develops open-source tools like Ranking Facts and FairDAGs to implement these principles in practical systems. Publication Trends: Recent work (2020-2025) demonstrates evolving focus from foundational fairness in ranking systems toward generative AI safety and medical applications. His publications show strong theoretical grounding combined with real-world implementation, particularly in privacy policy analysis and medical question-answering systems using causal inference techniques. Scientific Recognition: Pearl Brownstein Doctoral Research Award (NYU Tandon School of Engineering) CDS Postdoctoral Fellowship (University of Massachusetts) Professional Development: Dr. Yang has secured significant research funding including the CDS Postdoctoral Fellowship at UMass. His graduate work at NYU and Drexel University was fully supported by research assistantships, demonstrating consistent funding acquisition throughout his career. He actively contributes to academic community building through conference tutorials and educational initiatives. Research Ecosystem: He directs CAREAI at UTSA while collaborating across institutional boundaries through MATRIX and the School of Data Science. Previously, he contributed to the Data systems Research for Exploration, Analytics, and Modeling (DREAM) lab and Center for Data Science at UMass Amherst, maintaining continuity in his responsible AI research trajectory.
Ebru Cankaya is a Senior Lecturer II in the Department of Computer Science at the University of Texas at Dallas (UTD), part of the Erik Jonsson School of Engineering and Computer Science. She holds a Ph.D. in Computer Science from Ege University (Turkey) and has extensive academic experience across multiple institutions, including adjunct roles at Southern Methodist University and visiting professorships at Izmir University of Economics and Earlham College. Her research focuses on cybersecurity, risk modeling in databases, lossless text compression, and cloud computing. She has received numerous teaching awards, including the 2019 Outstanding Faculty of the Year award at UTD. Educational Background: Ph.D. in Computer Science, Ege University (2004) M.S. in Computer Science and IT & Management, Ege University (2004/2009) MBA in Economics and Administrative Sciences, Ege University (2000) B.Sc. in Computer Engineering, Ege University (1994) Research Interests: Computer and Network Security: Including access control models (e.g., Bell-LaPadula, Chinese Wall) and cryptographic techniques. Risk Modeling in Databases: Focusing on privacy-preserving data storage and obfuscation strategies. Text Compression: Innovations in encoding methods like Star Encoding and hybrid techniques. Cloud Computing: Security and dependability in distributed systems. Awards and Recognition: 2022: Teaching Award, Jonsson School 2019: Outstanding Faculty of the Year 2013: Faculty of the Month (NACURH) Multiple nominations for University and System-Wide Teaching Awards TUBITAK/EBILTEM Research Awards (2003–2004) Her professional activities include organizing doctoral symposiums (e.g., COMPSAC 2012/2013), participating in faculty development programs (e.g., Working Connections IT Institute), and mentoring undergraduate researchers. She has held academic roles across Turkey and the U.S. since 1997, including research assistantships at Ege University and a decade-long tenure at Ege University as a lecturer and assistant professor.
Prof. Dr. Yavuz Yakut serves as full-time Professor and Head of the Department of Physiotherapy and Rehabilitation at Hasan Kalyoncu University's Faculty of Health Sciences since 2016. Previously, he held academic positions at Hacettepe University from 1985 to 2016, progressing from Research Assistant to Professor, while concurrently serving on national committees including the Ministry of Health and Ministry of Finance Budget Implementation Commissions (1997-2003) and YÖK Physiotherapy Sub-Commission (2013-2016). His educational foundation includes a Bachelor's (1984), Master's (1987), and PhD (1990) in Physiotherapy and Rehabilitation, all completed at Hacettepe University. Yakut's research demonstrates exceptional breadth across rehabilitation science, with concentrated expertise in biomechanics and scoliosis rehabilitation . His work significantly advances neurological rehabilitation for conditions like multiple sclerosis and cerebral palsy, while pioneering applications in burn rehabilitation and orthotics/prosthetics . Recent publications reveal strategic integration of biopsychosocial models and telerehabilitation , particularly addressing pandemic-related challenges and chronic disease management across diverse populations. Analysis of his 2023-2025 publications shows consistent interdisciplinary innovation: validating cross-cultural assessment tools (e.g., Turkish translations of scoliosis and ADL questionnaires), developing novel exercise protocols (dance therapy, cognitive exercise therapy), and investigating rehabilitation responses in complex cases including HIV, rheumatic diseases, and post-earthquake trauma. His methodology frequently combines biomechanical analysis with patient-centered outcomes, demonstrating particular rigor in controlled trials for spinal deformities and burn recovery. His leadership extends beyond direct research through committee roles shaping national rehabilitation policy and educational standards, including his current departmental leadership and recent systematic review on physiotherapy distance education during pandemic disruptions.
Leid Zejnilovic is an Assistant Professor at Nova School of Business and Economics (Nova SBE), where he co-founded the Data Science Knowledge Center and serves as Academic Director, and co-founded the Open and User Innovation Knowledge Center as Scientific Deputy Director. He also co-founded the Patient Innovation platform, enabling patients and caregivers to share self-made healthcare solutions. With a double PhD from Carnegie Mellon University and Católica-Lisbon School of Business and Economics, his career spans over 20 years of international consulting, academic entrepreneurship, and teaching at institutions like Imperial College Business School and Ludwig Boltzmann Institute. PhD in Strategy, Entrepreneurship and Technological Change (Carnegie Mellon University / Catholic University of Portugal, 2014) Master in Engineering and Public Policy (Carnegie Mellon University, 2012) Master in Information Technology (Dzemal Bijedic University, 2007) Bachelor in Telecommunications (University of Sarajevo, 2002) His research focuses on Technology and Innovation Management, Human-Computer Interaction, and data-driven solutions across healthcare, tourism, and education. He has published extensively in journals like California Management Review , PLoS ONE , and Marine Policy , with recent work analyzing big data in tourism, machine learning for oral health, and pandemic impacts on fisheries. As an Associate Editor for Data & Policy Journal , his contributions bridge academic research and real-world applications. Co-founding the Data Science for Social Good Foundation and leading over 100 talks in industry and academia, Zejnilovic's career emphasizes translating innovation into social and economic impact through platforms, policy, and education.
Kshitij Sabnis is a Lecturer in Aerospace Engineering at the School of Engineering and Materials Science, Queen Mary University of London. He serves as Admissions Lead and Outreach & Recruitment Lead for Aerospace Engineering, and Deputy Director of Industrial Engagement (Graduate Attributes). He is affiliated with the Centre for Intelligent Transport and conducts experimental research in high-speed aerodynamics. Education: PhD in Experimental Aerodynamics, University of Cambridge Master’s in Physics Dr Sabnis's research focuses on experimental aerodynamics across various speed regimes, particularly shock/boundary-layer interactions, vortex dynamics, and supersonic flows. His work involves wind tunnel experiments on simplified models to understand complex fluid mechanics in applications ranging from racecar wings to supersonic aircraft intakes. He employs advanced diagnostics and develops novel experimental setups to enhance physical insight into flow phenomena. His recent publications (2019–2025) reflect a strong emphasis on high-speed flow behavior, including shock-induced separation, vortex interactions, and nacelle aerodynamics. Key themes include flow control, wind tunnel design, and validation of turbulence models. His work bridges fundamental fluid dynamics with practical aerospace engineering challenges. Scientific Awards: FHEA (Fellow of the Higher Education Academy) Dr Sabnis actively supervises PhD students and leads externally funded research projects. He has secured grants from EPSRC and the Royal Society, supporting work on schlieren imaging enhancement and small-scale wind turbines for rural energy. He teaches advanced aerodynamics modules and contributes to curriculum and industrial engagement. He leads a research group focused on experimental high-speed aerodynamics and is involved in developing new diagnostic techniques and test rigs. His team investigates vortex interactions and aerodynamic performance under extreme flow conditions.
Bruna Damiana Heinsfeld serves as Assistant Professor of Learning Technologies within the Department of Curriculum & Instruction at the University of Minnesota's College of Education and Human Development. Her research critically examines the intersections of technology, society, and education through the lens of Critical Studies of Education and Technology (CSET), with emphasis on power dynamics and social justice implications. Her academic credentials include: Ph.D. in Interdisciplinary Learning and Teaching (Learning Design and Technologies concentration) from UTSA M.A. in Education (Digital Languages, Media and Education concentration) from PUC-Rio, Brazil Multiple Postgraduate Certificates from Brazilian institutions: Media Discourse Analysis, Ontology and Epistemology, Philosophy/Sociology/Social Sciences, and Distance Learning Management B.A. in English Language and Literature from UERJ, Brazil Dr. Heinsfeld's research program centers on critical discourse analysis of educational technology narratives across corporate, policy, and educational contexts. She investigates how technological discourses are constructed and operationalized, particularly regarding digital equity, participatory exclusion, and the sociopolitical dimensions of technology adoption. Her methodological approach combines Critical Discourse Analysis (CDA) with critical pedagogy to unpack ideological, cultural, and economic factors shaping educational technology implementations. She examines epistemological foundations of technological beliefs and challenges neoliberal narratives in EdTech through rigorous deconstruction of policy documents and marketing materials. Analysis of her recent publications (2019-2023) reveals consistent focus on corporate influence in educational technology, with particular attention to Google and Microsoft's marketing narratives, pandemic-era remote learning disparities, and Latinx student experiences. Her work demonstrates how technological solutions often reinforce existing inequalities through participatory exclusion mechanisms, while her policy analyses expose contradictions between equity rhetoric and actual implementation. Recurring methodological threads include discourse analysis of educational landscape reports and critical examination of public policy frameworks. No scientific awards were documented in the provided materials. As an advisor, Dr. Heinsfeld cultivates a supportive environment grounded in social justice principles, emphasizing critical consciousness development and student autonomy. Her advising philosophy centers on accessible feedback, interdisciplinary exploration, and preparation for meaningful societal engagement. She teaches foundational courses including CI 4311W Technology and Ethics in Society (examining algorithmic bias, privacy concerns, and AI ethics) and CI 8147 Critical Discourse Analysis in Educational Research (focusing on language-power dynamics in educational contexts). While specific research laboratories aren't detailed, her collaborative work spans international contexts with Brazilian institutions and U.S. colleagues, particularly evident in joint publications with researchers like V. Marone and M. Pischetola. Her research trajectory indicates ongoing critical engagement with emerging technologies like AI in education policy, as evidenced by upcoming 2025 conference presentations.
Kimberly B. Rogers is an Associate Professor of Sociology at Dartmouth College , where she has been employed since 2015. She is affiliated with the Quantitative Social Science Program and the Neukom Institute for Computational Science . Her research focuses on how inequalities are produced, maintained, and resisted through behavior and emotion dynamics in social interactions , with particular attention to status and power hierarchies , occupational inequality , and mental health outcomes . She teaches courses such as Introductory Sociology , Research Methods , and Status and Power in Social Interaction , integrating computational tools into her pedagogy. PhD in Sociology, Duke University (2013) MA in Sociology, Duke University (2008) MA in Psychology, Wake Forest University (2005) BA in Psychology, Randolph-Macon Woman's College (2003) Rogers' research spans three key areas: cultural consensus in identity sentiments , behavioral/emotional responses to inequality , and computational modeling of social processes . Her work reveals how micro-social mechanisms perpetuate or disrupt status hierarchies across contexts like occupational roles , racialized interactions , and digital collaboration . Recent publications examine technological co-diffusion , pandemic-induced identity shifts , and gendered occupational perceptions . Her scholarly output follows trends in computational social science and cross-cultural emotion analysis . She employs Bayesian affect control theory to model dynamic identity processes and uncertainty in interactions , while her 2025 work on violence against women demonstrates applications of general strain theory to contemporary social issues. Senior Faculty Grant (2023-24) , Dartmouth College Wilson Fellowship (2021-22) , Dartmouth College Outstanding Article Award (2017) , American Sociological Association Seed Funding Grant (2016-17) , Dartmouth Provost Doctoral Dissertation Grant (2010-11) , National Science Foundation Rogers has received multiple grants for collaborative projects like THEMIS.COG , examining identity and sentiment modeling in groups . She mentors students through engaged scholarship and social impact practicums , though specific advisees aren't listed. Her 2019-2020 involvement with Campus Compact and 2016 DCSI teaching grant highlight her commitment to community-engaged pedagogy .
LIM Yi Hao is an Adjunct Lecturer at the School of Computing and Information Systems (SCIS), Singapore Management University (SMU), where he contributes expertise in cyber threat intelligence. He is also Google’s Intelligence Strategy Lead for Asia Pacific, based in Singapore, leading strategic engagements, partnerships, and thought leadership initiatives across the region. His research and professional interests focus on Cyber Threat Intelligence , Information Security , and Digital Risk Management . He actively shapes regional narratives through speaking engagements, conferences, and webinars, bridging industry strategy with academic insight. While no recent publications are listed, his work centers on strategic cybersecurity intelligence and its application in enterprise and policy contexts, reflecting a strong interdisciplinary approach combining technology, strategy, and regional dynamics. No scientific awards listed. LIM Yi Hao advises and collaborates within both academic and corporate frameworks, leveraging his dual role to align real-world cybersecurity challenges with educational development. Though no formal advisees are mentioned, his leadership at Google involves mentoring and strategic guidance across teams. There is no public information on grants or funded research projects. He is affiliated with the School of Computing and Information Systems at SMU and operates at the intersection of academia and industry, contributing to curriculum relevance through practical intelligence frameworks.
Emma Mercier is an Associate Professor and Associate Head & Director of Graduate Programs in the Department of Curriculum & Instruction at the University of Illinois, Urbana-Champaign's College of Education. She also holds a secondary appointment in the Department of Educational Psychology, demonstrating her interdisciplinary approach to educational research. Dr. Mercier's research focuses on the relationship between social interaction and learning, with particular emphasis on collaboration and computer-supported collaborative learning (CSCL) in classroom settings. Her work examines how technology influences group interactions and learning, especially through the use of multi-touch tables in classrooms. She investigates between-group and whole-class interactions, device ecologies, teacher tools, and classroom contexts that shape learning opportunities in technology-enhanced environments. Her research spans K-12 and higher education settings, with significant contributions to engineering education and the design of collaborative learning spaces. Analysis of Dr. Mercier's recent publications reveals a strong focus on orchestration tools that support instructors in facilitating collaborative learning, the role of technology (particularly augmented and virtual reality) in collaborative problem solving, and the design of effective collaborative tasks in engineering education. Her work bridges educational theory with practical classroom applications, often employing design-based implementation research methodologies. A notable trend is her increasing focus on machine learning applications to analyze and support collaborative interactions in real-time classroom settings. Dr. Mercier has been actively involved in mentoring graduate students and teaching courses related to educational research methods, child development and technology, and advanced study of education. Her work has involved significant collaboration with researchers across institutions and disciplines, particularly in the fields of educational technology, learning sciences, and engineering education. Her research has been supported through various projects, including the CSTEPS (Collaborative Support Tools for Engineering Problem Solving) initiative, which has developed and evaluated tools to support collaborative learning in engineering classrooms. This work has involved partnerships with teaching assistants, course assistants, and faculty to implement and refine collaborative learning approaches in undergraduate engineering courses.
Dr. Ed E. Moret is an Associate Professor of Computational Medicinal Chemistry at Utrecht University, where he serves as Managing Director of the Utrecht Institute for Pharmaceutical Sciences. He is a member of the Departmental Executive Board and Chair of the Board of Examiners of the School of Pharmacy. His academic career spans over three decades with significant contributions to pharmaceutical sciences. Utrecht University, Utrecht Institute for Pharmaceutical Sciences School of Pharmacy, Department of Chemical Biology and Drug Discovery Managing Director since January 2010 Dr. Moret's educational background includes completing Gymnasium-b at Gymnasium Camphusianum in Gorinchem in 1979, followed by pharmacy studies at Utrecht University until 1988. He earned his PhD in 1993 with research on calculations and simulations of DNA-alkylating cytostatics under supervision of Prof. L.H.M. Janssen and Prof. J.P.A.E. Tollenaere. He also conducted postdoctoral research at the Scripps Research Institute with Prof. A.J. Olson. His primary research interests focus on molecular recognition, particularly in auto-immune diseases, with expertise spanning computational medicinal chemistry, computer-aided drug discovery, cheminformatics, and bioinformatics. Dr. Moret's work bridges the gap between theoretical calculations and experimental validation in drug design. His research portfolio demonstrates a consistent trajectory from fundamental molecular interactions to applied drug discovery, with particular emphasis on enzyme inhibitors, carbohydrate-protein interactions, and molecular recognition processes. Analysis of his publication record reveals a strong focus on structure-based drug design, with significant contributions to the development of inhibitors for enzymes like β-glucocerebrosidase, NNMT, and neuraminidase. His work spans multiple therapeutic areas including lysosomal storage disorders, cancer metabolism, and infectious diseases. The interdisciplinary nature of his research is evident in the integration of computational approaches with experimental validation across biochemistry, pharmacology, and medicinal chemistry. Teacher of the Year (awarded three times by Pharmacy students) Member of editorial boards for Medicines and Conceptuur journals Secretary of Board of FIGON (2016) Secretary of Raad voor de Farmaceutische Wetenschappen (2024) Member of Board of Stichting Farmaceutische Erfgoed (2024) Dr. Moret has been actively involved in educational innovation, developing and coordinating the master's programme Drug Innovation, the profile Drug Regulatory Sciences, and the Honours programme Pharmaceutical Sciences. He has taught courses for pharmacy, chemistry, UCU and medical sciences students, as well as PhD courses in bioinformatics and computer-aided drug discovery. His educational contributions include developing an inquiry-based elective course on drug discovery, for which he published educational research. He holds BKO and SKO teaching qualifications and participated in the Centre of Excellence in University Teaching program. As Managing Director of the Utrecht Institute for Pharmaceutical Sciences, Dr. Moret leads research initiatives across chemical biology, drug discovery, and pharmaceutical sciences. His leadership extends to multiple advisory and editorial roles within the pharmaceutical research community, reflecting his significant contributions to both academic and professional spheres of pharmaceutical sciences.
Victor R. Lee serves as an Associate Professor at Stanford University's Graduate School of Education, with his office located at CERAS Building (520 Galvez Mall, Suite 531) in Stanford, California. He is actively affiliated with the Center for Studies in Education and Technology (CSET), where he conducts interdisciplinary research at the intersection of technology and learning. Dr. Lee holds a Ph.D. in Learning Sciences from Northwestern University and earned dual Bachelor's degrees in Cognitive Science and Mathematics from the University of California, San Diego. His academic trajectory bridges technical disciplines with educational research, establishing a foundation for his work in data-intensive learning environments. His research program centers on two interconnected domains: data literacy development in K-12 contexts and STEM education innovation across diverse learning spaces. He investigates how individuals make meaning from data during inquiry-based learning, with particular emphasis on self-collected student data and the epistemological challenges of data sense-making. Concurrently, his STEM education work spans traditional classrooms, makerspaces, computer labs, and school libraries, examining engaged learning practices and conceptual change in mathematics and science. Current projects focus on identifying the specialized knowledge teachers require to effectively scaffold student interactions with complex real-world datasets. Recent publications (2023-2024) reveal a strategic pivot toward artificial intelligence education, examining both teacher preparation and student understanding of AI systems. His work demonstrates consistent methodological rigor through design-based research, classroom implementations, and analysis of student reasoning patterns, particularly regarding how learners conceptualize algorithmic processes in platforms like YouTube. As a core faculty member within CSET, Dr. Lee collaborates with multidisciplinary teams to develop and evaluate educational interventions that bridge theoretical learning sciences with practical classroom applications, with recent emphasis on AI literacy tools and data-enabled pedagogical approaches.
