Rosental Alves is a Professor at the University of Texas at Austin's School of Journalism and Media, holding the Knight Chair in International Journalism. A former managing editor of Brazil's Jornal do Brasil , he founded the Knight Center for Journalism in the Americas. He earned a BA from Rio de Janeiro Federal University and was a Nieman Fellow at Harvard. His research explores international reporting, Latin American press freedom, digital journalism innovation, and media democratization. He created UT Austin's first online journalism course and advises global media organizations. Recent publications focus on journalist safety in Brazil, media innovation in Latin America, and digital transitions in news. Awards include the Nieman Fellowship and Knight Chair endowment. He leads training initiatives through the Knight Center, impacting thousands of journalists globally. No specific students or labs are detailed.
Michael Benedikt is a Professor of Computer Science at the University of Oxford and a Governing Body Fellow of University College. He holds the role of Director of the Advanced MSc in Computer Science program. His research focuses on databases, Web data management, logical methods in computer science, and theoretical computer science. Benedikt's work intersects with artificial intelligence, machine learning, and algorithms, with contributions to query languages, data integration, and formal methods. Education: Ph.D. in Mathematics, University of Wisconsin, 1993 Prior roles: Distinguished Member of Technical Staff at Bell Laboratories (1994–2006), visiting researcher at Yahoo! Labs Research Interests: Databases and information exchange Web and Web 2.0 data management Logical methods in computer science Formal verification and query optimization Applications in AI and machine learning Key Projects: FOX : Query-driven data acquisition from web-based sources PDQ : Proof-driven query answering over web-based data TRANCE : Transforming nested collections efficiently Awards: Best Paper Award at ICALP 2017 (Track B) EPSRC Established Career Fellowship (2015–2020) Advising & Grants: Directed the MSc in Advanced Computer Science program Supervised PhD students including Chia-Hsuan Lu and past advisees such as Luying Chen and Ben Spencer Received funding for projects like the ERC DIADEM initiative Labs & Teams: Active in the Department of Computer Science’s research groups, including the Algorithms At Large and Databases teams.
Michelle LaFrance is an Associate Professor in the English Department at George Mason University, specializing in Writing and Rhetoric. Her research focuses on feminist methodologies, institutional ethnography, community writing, and writing program administration. She holds a Ph.D. from the University of Washington (2009) and has published extensively on topics like academic labor, e-portfolios, and writing center pedagogy. Her recent work examines discourses of volunteerism and belonging in urban communities. Dr. LaFrance teaches courses on critical pedagogy, feminist research, and public writing. Her major awards include the 2021 College Composition and Communication Research Impact Award for her book Institutional Ethnography: A Theory of Practice for Writing Studies Researchers , which also received an Honorable Mention from the International Writing Across the Curriculum Association. She has supervised numerous graduate students in areas such as queer worldmaking, linguistic justice, and composition pedagogy. Education: Ph.D., University of Washington, 2009 Key Affiliations: Director of Graduate Studies, Writing Program Administrator LaFrance's research emphasizes materialist frameworks and participatory methods. She explores the intersections of writing studies with issues of labor, space, and community engagement. Recent projects include analyzing writing instructors' negotiations of language standards and reimagining equity practices in two-year colleges.
Marco Lazzari is a Full Professor at the University of Bergamo in the Department of Human and Social Sciences. His research focuses on educational technology integration, digital storytelling applications in teaching, and inclusive education methodologies. Previously he served as Department Head (2018-2024) and coordinates doctoral studies in Human Sciences and Welfare Innovation. Education Background: Ph.D. in Computer Science M.S. in Information Sciences B.S. in Information Sciences Research Interests: Digital storytelling for inclusive pedagogy Educational robotics applications Technology-mediated distance learning Teacher training in digital literacy Social media's educational impact His recent publications demonstrate strong focus on educational technology in post-pandemic contexts, inclusive robotics programs, and digital storytelling frameworks. Research trends include addressing educational disparities through technology, evaluating pandemic learning impacts, and developing sustainable digital pedagogies across educational levels. Scientific Awards: No major awards listed in provided materials As Director of the Educational Technologies Center (2005-2018), he established technology-enhanced learning initiatives. Currently supervises doctoral students investigating educational technology efficacy, digital inclusion, and robot-assisted learning. Research collaborations span computer science, pedagogy, and special education disciplines. Laboratory Focus: Educational robotics implementation Digital storytelling frameworks Teacher technology training programs Accessibility in educational technology
Robert Jacob is a Professor of Computer Science at Tufts University's School of Engineering, where he leads research in human-computer interaction with particular focus on implicit brain-computer interfaces. His work bridges computer science, cognitive science, and interface design to create adaptive systems that respond to users' cognitive states without explicit input. His educational background includes a Ph.D. from Johns Hopkins University. Professional milestones include: ACM CHI Academy membership (2007) ACM Fellow designation (2016) Leadership roles as ACM SIGCHI Vice President and conference chair for CHI, UIST, and TEI Professor Jacob's research centers on implicit interaction techniques, particularly using fNIRS brain sensing to create adaptive interfaces. His work has evolved from foundational studies in reality-based interaction and tangible programming to current neuroadaptive systems that measure cognitive workload in real-time. This research spans domains including music learning, museum education, and general user interface adaptation. His publications reveal consistent focus on brain-computer interfaces since 2012, with increasing sophistication in physiological measurement and machine learning techniques. Recent work integrates multiple physiological signals beyond brain data to create comprehensive user state models. Major recognitions include: CHI 2016 Best Paper Award for music learning research CHI 2014 and 2012 Best Paper Honorable Mentions Keynote addresses at major conferences including Neuroadaptive Technology Conference (2017) Extensive media coverage in New Scientist, IEEE Computer, and Boston Globe Professor Jacob has mentored 17 PhD students who now hold faculty positions at institutions including Worcester Polytechnic Institute, Northwestern University, and Carleton University. His HCI Lab, located in the Joyce Cummings Center, receives funding from NSF and other sources supporting neuroadaptive interface research. Current projects focus on broadening implicit interaction to include multiple physiological measurements while maintaining user privacy and system transparency.
W. Eric Wong is a Professor of Computer Science at The University of Texas at Dallas (UTD), affiliated with the Erik Jonsson School of Engineering and Computer Science. He holds a Ph.D. in Computer Science from Purdue University (1993), following earlier degrees from Purdue and Eastern Michigan University. His research focuses on reducing software production costs while enhancing reliability, safety, and quality through program-based and architecture/design-based testing methodologies. Key areas include automated test generation, fault localization, debugging, and software safety analysis. Professional Background: Tenured Professor at UTD since 2002 Prior roles include Senior Scientist at Telcordia Technologies (1995–2002) and Consultant at Texas Instruments (2004–2005) Active in industry partnerships, such as projects with Motorola, Avaya Labs, and Raytheon Research Interests: Software Testing & Debugging Dependable Software Development Security Requirements Engineering Fault Localization Techniques Model-Based Testing Software Reliability Modeling Awards & Recognition: 2007 IEEE COMPSAC Best Paper Award 1997 NASA Quality Assurance Special Achievement Award Recipient of a $404,772 NSF grant for software safety and reliability research (2021) Professional Activities: Editorial roles for journals like Journal of Systems and Software and International Journal of Software Engineering Program Chair for ISSRE 2012, COMPSAC 2010, and multiple ACM SAC conferences Member of IEEE Reliability Society Administrative Committee (2008–2013) IBM System z Curriculum Advisory Panel member Labs & Teams: Leads the Software Engineering Group at UTD, collaborating on projects like eXVanatge (dependable software solutions) and Fault-Prone Module Identification in telecommunications systems. Engages in cross-disciplinary efforts with industry and international institutions.
Jenni Alisaari is a Professor of Education specializing in Linguistically and Culturally Diverse Education at the School of Applied Educational Science and Teacher Education, University of Eastern Finland. Her work focuses on linguistically responsible pedagogy, multilingualism in education, and culturally responsive teaching practices. Teaches Master’s Degree Programme in Early Language Education for Intercultural Communication Former roles include University Lecturer of Finnish at University of Stockholm, Special Researcher in Sociology at INVEST Research Centre, and Teacher Trainer at University of Turku and Åbo Akademi Research interests intersect language, culture, and identity in educational contexts. She studies: Linguistically Responsible Pedagogy Multilingual Learners Support for Newly Arrived Students Using Music in Language Instruction Language as a Cultural Identity Resource Curriculum Reform Implementation Her publications since 2015 reveal a focus on: Intercultural Communication in Classrooms Migrant Student Belonging Language Policy in Nordic Countries Cognitive Benefits of Musical Language Instruction Teacher Training for Linguistic Diversity Educational Equity Frameworks
Kevin W. Hamlen is the Louis A. Beecherl, Jr. Distinguished Professor in the Department of Computer Science at the University of Texas at Dallas. He serves as Executive Director of UT Dallas' Cyber Security Research and Education Institute. His research focuses on language-based security , binary software hardening , cyberdeception , and formal program verification . He has received multiple grants from agencies like AFOSR, NSF, DARPA, and industry partners including Lockheed Martin and Intel. PhD and MS from Cornell University BS from Carnegie Mellon University His research explores automated approaches to software security through techniques like binary disassembly , control-flow integrity , and honey-patching . He has pioneered methods for malware defense and cloud/web/mobile security . Recent work examines adaptive cyberdeception and GPU-based security frameworks . His publications span binary code manipulation , malware mitigation , and blockchain security . Key awards include the NSF IUCRC Technology Breakthrough Award and two CSAW Best Paper 2nd Prizes . He advises numerous PhD students, many of whom now work at Google, IBM, and Microsoft. His book Autonomous Cyber Deception (Springer, 2019) with Ehab Al-Shaer and Cliff Wang provides comprehensive coverage of adaptive cyberdeception strategies.
Denghui Zhang is an Assistant Professor in the School of Business at Stevens Institute of Technology. His research focuses on data science, large language models (LLMs), and business analytics, with particular emphasis on applications in financial systems, knowledge graphs, and spatio-temporal prediction. He is a member of the Stevens Institute for Artificial Intelligence and has held academic roles including reviewer positions for prestigious journals like Nature Communications and conferences such as AAAI and SIGKDD. Dr. Zhang holds a PhD in Information Systems from Rutgers University (2023) and an MS in Computer Science from the University of Chinese Academy of Sciences (2018). His educational background bridges computer science and business analytics, enabling his cross-disciplinary research. His research explores cutting-edge topics like federated learning optimization for LLMs, theory-of-mind reasoning mechanisms, and ethical AI governance. Notable contributions include turbulence forecasting models, traffic prediction frameworks, and venture capital investment strategies leveraging reinforcement learning. Dr. Zhang has received prestigious recognitions including the ICIS 2023 Best Student Paper Award and AAAI-23 Student Scholar distinction. His work frequently addresses practical challenges in AI ethics, financial decision-making systems, and scalable machine learning architectures. He actively contributes to academic communities through program committee roles for top conferences and has pioneered novel methodologies in multi-agent financial systems and graph neural network design.
Jun Yan is an Associate Professor and Concordia University Research Chair in Artificial Intelligence in Cyber Security and Resilience at the Concordia Institute for Information Systems Engineering (Concordia University). His research focuses on cybersecurity, smart grid systems, and AI-driven solutions for energy and communication networks. He supervises graduate students in programs such as Information Systems Security (MASc), Computer Science (MCompSc), and Information and Systems Engineering (PhD). Research Highlights : Cybersecurity of distributed energy systems, AI penetration testing frameworks, and resilient transactive energy markets. Awards : Holds a prestigious university research chair in AI-driven cybersecurity. His work integrates machine learning with domain-specific challenges in smart grids, IoT security, and multi-agent systems. Notable contributions include frameworks for detecting adversarial attacks on power systems, optimizing renewable energy integration, and developing AI tools for penetration testing. His articles reflect a strong emphasis on interdisciplinary solutions blending cybersecurity, energy systems, and advanced computing. Yan’s research also addresses policy and infrastructure challenges in sustainable energy systems, including waste management policy analysis and optimal configuration of hybrid renewable systems. He has pioneered open-source co-simulation platforms like PEMT-CoSim and Quantum-Sim for secure energy trading and quantum communication in grids. He actively engages in grant-funded projects and advises on both academic and applied aspects of cybersecurity and intelligent systems.
Michael Goh serves as Professor and Campbell Leadership Chair in Education and Human Development at the University of Minnesota's College of Education and Human Development, where he coordinates Graduate Programs in Higher Education. Previously (2017-2022), he held the systemwide position of Vice President for Equity and Diversity across the university's five campuses. His educational foundation includes: PhD in Counseling and Student Personnel Psychology from the University of Minnesota MS in Counseling and Counselor Education from Indiana University BA in Psychology and Sociology (double major) from Indiana University Goh's research centers on cultural intelligence (CQ) and intercultural competence development within higher education contexts, examining cross-cultural counseling practices, leadership for inclusive excellence, and culturally intelligent frameworks for mental health services. His interdisciplinary approach bridges psychology, sociology, and educational leadership to address diversity, equity, and inclusion challenges in global academic environments, with particular focus on international student development and culturally responsive administration. His 2020-2025 publications reveal consistent exploration of intercultural competence in higher education internationalization, with strong emphasis on Asian case studies (Japan, Singapore) and practical applications for DEI leadership. Recurring themes include global citizenship education frameworks, equity-driven institutional transformation, and cross-cultural therapeutic expertise development, demonstrating both theoretical depth and practical implementation strategies across diverse educational settings. Notable recognitions include: Fellow of the American Psychological Association (2024) Commissioner for Midwestern Higher Education Compact (2021-2025) Senior Fellow at Minnesota Institute for Trauma Informed Education (2021-present) Pacific Circle Consortium Honors Recognition for cross-border scholarly work (2018) Exemplary Diversity Leadership Award from American Counseling Association (2010) Multiple distinguished teaching and mentorship awards from University of Minnesota His grant leadership includes NSF-funded Louis Stokes North Star STEM Alliance targeting underrepresented students in STEM fields, and NIH Partners in Research Grant developing culturally responsive children's mental health practices. Current projects focus on linguistic access to mental health services and multinational studies of expert counselors across Asia. Goh previously directed the University of Minnesota's Institute for Diversity, Equity, and Advocacy (IDEA), fostering interdisciplinary equity research, and maintains connections with the Workforce Development and Research Lab through his focus on culturally intelligent leadership development.
Rei Sanchez-Arias is a Teaching Professor and Director of the Master of Applied Data Science (MADS) program at UNC Chapel Hill's School of Data Science and Society. His expertise includes data mining, machine learning algorithm development, and data science pedagogy. He previously held positions at Florida Polytechnic University and St. Thomas University. Research interests span educational tools, health informatics, and optimization methods. Recent work involves AI for endoscopic surgery evaluation, meta-analysis of MLOps tools, and curriculum design for data science programs. Awards include the Excellence in Teaching Award from Florida Polytechnic. Student mentorship focuses on data wrangling and analytics projects.
Charles Ling is a Professor of Computer Science at Western University, holding the title of Science Distinguished Research Professor. He also serves as Director of the Data Mining and Business Intelligence Lab and Associate Scientist at the Lawson Health Research Institute. His academic background includes a B.Eng. (CS and EE) from Shanghai Jiao Tong University and MSc/PhD from the University of Pennsylvania (UPenn). Research interests span machine learning, deep learning, AI, and healthcare informatics, with notable contributions to the GlucoGuide diabetes management system. He has authored over 220 peer-reviewed papers and a book titled Crafting Your Research Future , focusing on academic career development. Awarded Fellow of the Canadian Academy of Engineering (CAE) and recipient of the First Prize for Best Clinical Research Presentation (2011). Active in grants (NSERC, FedDev, Mitacs) and organizational roles in top conferences (KDD, ICDM). Supervises 5 PhD and 4 MSc students, with notable advisees including Harry Zhang and Victor Sheng. Leverages AI in education to enhance children's cognitive abilities through video-based programs like Power Thinking , approved by Curriculum Services Canada. His work integrates machine learning with healthcare, finance, and software engineering.
Abi Gilmore is a Professor of Arts Management, Politics, and Cultural Practices at the University of Manchester's School of Arts, Languages and Cultures (ICP). She holds a part-time secondment as UKRI Policy Fellow at the Department for Culture, Media & Sport. Her work focuses on cultural policy, creative industries, and the role of public spaces like parks in local governance. Gilmore has led interdisciplinary projects such as the AHRC Connected Communities initiative and the UKRI-funded study on pandemic impacts on cultural sectors. She contributes to policy networks including Policy@Manchester and the Manchester Urban Institute, and advises organizations like Creative Addo. Her academic leadership includes founding the MA Arts Management program and co-developing the PhD by Professional Practice in Arts and Cultural Management. Educated at the University of Leicester (BSc Sociology, 1995; DSc Cultural Policy, 2000), Gilmore has held roles in both academia and cultural sector governance, including directing the Northwest Culture Observatory. Her research emphasizes participatory methods, policy evaluation, and the foundational role of cultural infrastructure. She serves on boards for arts organizations such as Brighter Sound and Macclesfield Barnaby Festival, and has extensive international collaborations with institutions in Melbourne and Toronto. Key research outputs include monographs on public parks as cultural policy sites (2024) and edited volumes analyzing pandemic impacts (2022). Her work intersects with UN SDGs related to education, sustainable cities, and responsible consumption. Recent projects explore cultural recovery post-pandemic, devolved governance models, and the political economy of creative ecosystems.
Giulia Toti is an Assistant Professor of Teaching in the Department of Computer Science at the University of British Columbia (UBC), part of the Faculty of Science. Her work focuses on computer science education, equity in curriculum design, and fostering inclusive learning environments. She teaches courses such as Applied Machine Learning (CPSC 330), Fairness, Accountability, Transparency, and Ethics (FATE) in Data Science (DSCI 430), and Computers and Society (CPSC 430). Her research explores diversity initiatives in CS education, mastery learning frameworks, and equitable grading practices. Notable contributions include studies on pandemic-era remote teaching impacts and the development of Agora, a tool for enhancing large-classroom engagement. Toti has received UBC Faculty Teaching Awards for her pedagogical innovations. Her interdisciplinary work spans machine learning applications in industry and healthcare, including semantic search systems for clinical data (SemEHR) and predictive analytics for energy production. She is affiliated with the ACE Lab and actively contributes to curriculum reforms addressing DEI (Diversity, Equity, Inclusion) challenges in STEM education. Grants/Awards: Faculty Teaching Awards Labs/Teams: ACE Lab (Advancing Computing Education) Advising: No explicit advisee listings found, but contributes to pedagogical research impacting teaching practices.
