ChanMin Kim is a Professor in the Learning and Performance Systems department at Penn State College of Education. With over 80 publications and 2553 citations, their work focuses on integrating artificial intelligence , robotics , and educational technology into science and computer science education. Research interests: Science writing, AI-human partnerships, robotics in education, equity-focused technology design Key methodologies: Natural Language Processing, learning analytics, scaffolding strategies Recent work explores large language models in education, debugging processes in pre-service teacher training, and automated assessment systems for science explanations. While the provided data doesn't show specific scientific awards or student advisees, their publications in venues like British Journal of Educational Technology and Journal of Science Education and Technology demonstrate significant contributions to learning sciences. Kim collaborates extensively with researchers in AI, educational technology, and equity-focused domains.
Prof. Dr. Bernd Skiera is a leading Marketing Professor at Goethe University Frankfurt since 1999 and a member of the managing board of the efl - The Data Science Institute. His work bridges information systems and marketing, with a focus on data-driven decision making and digital transformation.
Aniello Murano is a Professor of Computer Science at the Department of Electrical Engineering and Information Technologies , University of Naples Federico II. He serves as Scientific Director of the ASTREA (Automated Strategic Reasoning) Laboratory and leads cutting-edge research in Artificial Intelligence, Strategic Reasoning, Multi-Agent Systems , and Formal Verification . Research Interests : Strategic reasoning under perfect/imperfect information, specification/verification/synthesis of reactive systems, temporal/modal logics, automata theory, parity games, game theory, mechanism design, and formal languages. Notable Projects : PNRR Research Unit Coordinator (2023-2025) on Resilient AI, PRIN 2020 Unit Coordinator (RIPER: Resilient AI-Based Self-Programming and Strategic Reasoning), H2020-MSCA SEAL (Principal Coordinator). Awards & Honors : JPMorgan Faculty Research Award (2022), Royal Society Award (2016), Best Paper PRIMA (2015), INDAM Project Leader (2023), Italian Scientific Habilitation (2017-2018). Students & Postdocs : Supervised 6 PhD students (e.g., Silvia Stranieri, Vadim Malvone) and mentored postdocs such as Munyque Mittelmann and Bastien Maubert. Laboratory : Leads ASTREA Lab, focusing on automated strategic reasoning and resilient AI systems.
Prof. Dr. Wolfgang Nejdl is a Professor at the Institute for Data Science within the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover. He serves as Executive Director of the L3S Research Centre and Leibniz Forschungszentrum Inclusive Citizenship. Web Science Information Retrieval Artificial Intelligence Deep Learning His recent research focuses on AI applications in medicine , multimodal data fusion , and ethical AI systems . Projects include CAIMed (AI in Causal Medicine) and DAISEC (AI & Cybersecurity). His publications span conferences like AAMAS, WWW, and SIGIR. Notable awards include membership in the National Academy of Science and Engineering (acatech) . Former students hold positions at institutions like Stanford, TU Dresden, and ETH Zürich. Current projects involve climate resilience AI , federated learning for healthcare , and quantum-inspired data science .
Talia Ringer is an Assistant Professor in the Department of Computer Science at the University of Illinois, where she is a member of the PL/FM/SE (Programming Languages/Formal Methods/Software Engineering) research group. She leads the Illinois Theorem Provers (ITP) lab, which focuses on advancing proof engineering technologies to make formal verification accessible to programmers of all skill levels across all domains. Research Interests Dr. Ringer's research spans multiple aspects of proof engineering with a strong focus on integrating techniques from dependent type theory, program transformations, and neural proof synthesis to solve real-world verification challenges. Her work addresses how to build systems that allow programmers to prove the absence of costly or dangerous bugs in software. She is particularly interested in proof repair, machine learning for proofs, and developing new methodologies that can drive the creation of large, secure, and robust verified software and hardware systems. Research Trends Dr. Ringer's recent publications demonstrate a strong shift toward integrating machine learning with formal verification, particularly in proof repair and synthesis. Her work explores how large language models can assist with theorem proving, how reinforcement learning can automate verification processes, and how to make proof engineering more practical for real humans. Many publications involve collaborations with students and researchers from multiple institutions, reflecting her commitment to interdisciplinary research. Awards and Recognition Distinguished Paper Award at ESEC/FSE 2023 for "Baldur: Whole-Proof Generation and Repair with Large Language Models" ACM SIGPLAN Distinguished Service Award in 2023 Mentoring and Service Dr. Ringer is a dedicated mentor who has advised numerous undergraduate and graduate students. She is the founder and president of the Computing Connections Fellowship, which provides transitional funding for computer science PhD students needing to escape unhealthy environments. She is also the founder and previous chair of the SIGPLAN Long-Term Mentoring Committee (SIGPLAN-M), which connects more than 200 mentors and 300 mentees across more than 44 countries. Her service work was formally recognized with the 2023 ACM SIGPLAN Distinguished Service Award. Laboratory and Collaborations Dr. Ringer leads the Illinois Theorem Provers (ITP) lab with current members including postdocs, PhD students, masters students, and undergraduates. She collaborates extensively with researchers at the University of Washington, UMass Amherst, Google Research, Galois, and other institutions on various proof engineering projects.
Alexander Pan is a third-year Computer Science PhD student at the University of California, Berkeley, advised by Jacob Steinhardt . His research focuses on developing safe machine learning systems, particularly sequential decision-making agents. He holds a dual bachelor's degree in Mathematics and Computer Science from Caltech, where he worked with Anima Anandkumar and Yuanyuan Shi . His recent work explores AI safety through topics like unlearning , LLM transparency , and reward hacking , with publications at premier conferences including ICML and ICLR. He has received recognition such as the FLI PhD fellowship and hackathon awards for projects like SimSquare and homES ReInvented . Scientific Awards: FLI PhD fellowship Best Social Network Hack - Stanford Hackathon 2021 Best Use of ESRI Technology - Caltech Hackathon 2020 ICML 2023 Oral Presentation
Paul Boersma is a Professor of Phonetic Sciences at the University of Amsterdam within the Faculty of Humanities. His research explores how phonetic, phonological, and morphological phenomena emerge through computational modeling using artificial neural networks and Optimality Theory, with a focus on multi-level constraint interactions and distributional learning. University of Amsterdam Faculty of Humanities Phonetic Sciences Key research areas include: Computational Modeling : Simulations of phonological category emergence from phonetic data Optimality Theory : Gradual Learning Algorithm applications BiPhon Framework : Parallel bidirectional phonology/phonetics models Statistical Learning : Cross-situational and distributional learning mechanisms Recent publications emphasize: 2025: Inclusive speech recognition systems using Whisper model 2025: F0 ratio analysis for creaky voice diagnostics 2024: Prosodic clitics in child speech and checked tones in Shanghai Chinese 2023: Distributional learning in developmental language disorder contexts 2022: Substance-free phonological features and ghost segment phenomena He has also contributed extensively to the Praat software for phonetic analysis, with continuous updates since 1993.
Dongwook Yoon is an Associate Professor at the Department of Computer Science , University of British Columbia , and serves as Director of the SOCIUS Lab . He actively contributes to research in Human-Computer Interaction, Human-AI Interaction, and Virtual/Augmented Reality as a member of the Designing for People (DFP) and CAIDA research clusters. Education : PhD in Computer Science from Cornell University (2017), MS (2009) and BS (2007) in Computer Science from Seoul National University Research Focus : Designing socio-technical systems that bridge the gap between technology and human social processes, with innovations in AR/VR, multimodal interaction, and inclusive design Article Trends show his work spans: Temporal and bichronous learning environments AI self-clones and ethical implications Income inequality in virtual platforms Enhanced multimodal collaboration in VR Eyes-reduced interfaces for situational impairments Speculative participatory design for gig economy challenges Scientific Awards include: Google Academic Research Award (2024) Best Paper Award at CHI 2024 High Impact Award in Educational Technology (2024) CHCCS/SCDHM Graphics Interface Early Career Award (2023) Multiple Honorable Mentions at CHI, DIS, and CSCW Students & Collaborators range from active PhD candidates (Anika Sayara, Yuri Kim) to notable alumni (Thitaree Tanprasert, Ashish Chopra) across his SOCIUS Lab projects. His research receives funding from NSERC , KIST , Adobe , Microsoft , and Google grants.
Cecilia R. Aragon is a Professor in the Department of Human Centered Design & Engineering at the University of Washington, where she also serves as an Adjunct Professor in Computer Science & Engineering, Electrical and Computer Engineering, and the Information School. She is additionally a Senior Data Science Fellow at the eScience Institute. Aragon directs the Human-Centered Data Science Lab and has made significant contributions at the intersection of human-computer interaction and data science. Her research interests focus on human-centered data science, human-centered artificial intelligence, human-centered machine learning, human-computer interaction (HCI), computer-supported cooperative work (CSCW), visual analytics, aviation and astronautics sociotechnical systems, and emotion in informal text communication. Aragon's work bridges technical and social aspects of data science, particularly examining how humans interact with and gain insight from large datasets through both quantitative and qualitative methods. Aragon's recent publications demonstrate a strong focus on understanding online communities, sentiment analysis, distributed mentoring systems, and the ethical implications of AI. Her work spans multiple disciplines including social computing, data visualization, and astrophysics data analysis, showing her interdisciplinary approach to human-centered data science. Presidential Early Career Award for Scientists and Engineers (PECASE) 2008 Fulbright Fellowship 2017-18 HCDE Faculty Innovator in Research Award, University of Washington, 2015 Distinguished Alumni Award, Computer Science, University of California, Berkeley, 2013 Top 25 Women of the Year, Hispanic Business Magazine, 2009 Aragon has secured over $28 million in research funding from organizations including the National Science Foundation, National Institute of Standards and Technology, Department of Energy, Gordon and Betty Moore Foundation, Alfred P. Sloan Foundation, Washington Research Foundation, and industry partners like Microsoft and Intel. Her educational background includes a Ph.D. in Computer Science from UC Berkeley (2004), an M.S. in Computer Science from UC Berkeley, and a B.S. with Honors in Mathematics from Caltech. She leads the Human-Centered Data Science Lab and is affiliated with the eScience Institute, the Nearby Supernova Factory, and various research groups focused on data-intensive scientific collaborations. Her work on collaborative visual analytics systems like Sunfall has had significant impact in both academic and applied settings.
Jonas Kuhn is a professor at the Institute for Natural Language Processing (IMS) at University of Stuttgart. He is working at the interface between language and computers, combining linguistics and computer science. Kuhn's research interests span a wide range of computational linguistics topics including: Language models and spatial reasoning Analysis of large language models (LLMs) through linguistic theories Political text analysis and discourse networks Computational approaches to literature and cultural studies Retrieval-augmented language modeling Semantic change detection Dependency parsing and syntactic analysis His recent publications (2023-2025) focus on the intersection of neural language processing with fields as diverse as spatial reasoning, literary analysis, and political discourse. This reflects his interdisciplinary approach that bridges fundamental language research with practical technology development. As a faculty member at one of Germany's largest computational linguistics centers, Kuhn contributes to both fundamental research and technological development in language processing systems.
Yan Chen is a Professor of Computer Science at Northwestern University's Robert R. McCormick School of Engineering and Applied Science. He leads the Northwestern Lab for Internet and Security Technology (LIST) and the Center for Ultra-scale Computing and Information Security. His research focuses on cybersecurity, network measurement, and distributed systems security. Chen holds a Ph.D. from UC Berkeley (2003), M.S. from SUNY Stony Brook, and B.E. from Zhejiang University. Research interests include securing networking systems, intrusion detection, cloud-native platforms, and mobile security. Notable awards include the DOE Early CAREER Award (2005), Air Force Young Investigator Award (2007), and ACM ASPLOS'18 Most Influential Paper Award. His work has been cited over 17,000 times with an h-index of 62 (2024). Key contributions include the LIST lab's advancements in APT detection, provenance tracking in microservices, and security frameworks like FlowCog. He advises numerous Ph.D. students and has graduated over 20 researchers now in academia and industry.
Agnes Horvat is an Associate Professor of Communication (with a courtesy appointment in Computer Science) at Northwestern University. She directs the Technology and Social Behavior (TSB) joint doctoral program between the McCormick School of Engineering and the School of Communication, and leads the Lab on Innovation, Networks, and Knowledge (LINK). Her research focuses on human-centered computing, network science, and AI's impact on information production/sharing in digital platforms. She has received NSF CAREER, CRII, and collaborative awards as PI. Her work examines algorithmic bias in online spaces, AI-assisted creativity (e.g., LLMs in biomedical writing and music), and collective intelligence dynamics. Media coverage includes Nature , Washington Post , and Le Monde . Her advisees have won prestigious fellowships like the Northwestern Presidential Fellowship and best paper awards at top conferences. Research interests include: (1) algorithmic bias in social media and crowdfunding, (2) AI-driven creativity expansion, (3) network structures of scientific attention, and (4) opinion dynamics in online discussions. Current projects explore LLMs' role in scientific writing and music composition, while past work analyzed gender disparities in scholarly self-promotion and retraction paper attention patterns. Grants: NSF CAREER Award (202?), NSF CRII (202?), Collaborative Grant (202?) Labs/Teams: LINK Lab (focusing on innovation networks), TSB Program (interdisciplinary engineering/communication PhD)
Ming Lin is a Distinguished University Professor at the University of Maryland, College Park, holding joint appointments in Computer Science (Department of Computer Science), the Institute for Advanced Computer Studies (UMIACS), Electrical and Computer Engineering (ECE), and the Maryland Robotics Center. She holds the Dr. Barry Mersky and Capital One E-Nnovate Endowed Professorships. Her research focuses on physically-based modeling, virtual environments, haptics, robotics, and AI applications in healthcare and urban computing. Education: Ph.D., M.S., and B.S. in Electrical Engineering & Computer Sciences from UC Berkeley. She previously spent 20 years at UNC Chapel Hill before joining UMD in 2018. Research interests include collision detection algorithms (e.g., Lin-Canny algorithm), real-time physics simulation, virtual/augmented reality systems, and medical imaging applications. Her work has led to over 2 million downloads of her group's software tools and licenses with 60+ companies. Notable contributions include the Oculus Rift-related VR technologies and Amazon's virtual try-on system. Awards: IEEE Fellow (2012), ACM Fellow (2011), NAI Fellow (2022), and Washington Academy of Sciences Distinguished Career Award (2020). Active in professional service, she serves on the CRA Board and chairs the Committee on Widening Participation in Computing Research. Advising: Supervises 12+ PhD/Master's students. Her lab (GAMMA Group) focuses on AI-driven robotics, autonomous systems, and physically-based simulations. Key projects include traffic simulation frameworks, medical VR applications, and 3D garment modeling.
Sabine Süsstrunk is a Full Professor and Director of the Images and Visual Representation Laboratory (IVRL) at EPFL's School of Computer and Communication Sciences. She holds a BS in Scientific Photography from ETH Zürich, MS from Rochester Institute of Technology, and PhD from University of East Anglia. Her career includes positions at Hewlett-Packard Labs and Corbis Corporation. Her research explores computational imaging, computational photography, color processing, computer vision, and image quality. Key interests include near-infrared applications, multispectral imaging, and computational aesthetics. Her work bridges hardware and software solutions for imaging challenges. Publications demonstrate consistent focus on advancing generative models (diffusion models, neural cellular automata), 3D reconstruction (NeRF variants), and media integrity (DeepFake detection). Recent trends show increased emphasis on 3D vision, robustness in generative AI, and video analysis. Awards & Honors: IS&T/SPIE Electronic Imaging Scientist of the Year (2013) Raymond C. Bowman Teaching Award (2018) EPFL AGEPoly IC Polysphere Award (2020) 8 Best Paper/Demo Awards Fellowships: IEEE, IS&T, ELLIS, AIIA She leads the IVRL lab and advises PhD candidates while serving as President of the Swiss Science Council. Research is supported through competitive grants and industry collaborations.
Verónica Loureiro-Rodríguez is an Associate Professor in the Department of Linguistics at the University of Manitoba's Faculty of Arts. Her research focuses on sociolinguistics, language identity, and code-switching, with special attention to global hip hop and multilingual communities. She holds a PhD from the University of California, Davis, an MA from the University of Colorado at Boulder, and a BA from the Universidade de Santiago de Compostela. Dr. Loureiro-Rodríguez's work examines language attitudes across diverse contexts, including French-English dynamics in Manitoba, Spanish-Valencian bilingual processing, and code-switching in music. She has also explored language use in robotics and cultural hybridity among Puerto Rican and Mexican communities. Her teaching excellence was recognized with the 2021 Faculty of Arts Teaching Excellence Award. Education: PhD (UC Davis), MA (CU Boulder), BA (USC) Awards: 2021 Teaching Excellence Award (Established Faculty) Research Focus: Language policy, digital sociolinguistics, and cultural identity She currently supervises graduate students in Master's and PhD programs, focusing on sociolinguistic methodologies like the matched-guise technique. Her research often intersects with music studies, robotics, and diaspora linguistics.
