Find Academic Supervisors

• Privacy and Cybersecurity
• Service and Business Model Innovation
• IoT Ecosystems
• +1 more

Prof. Dr. Patrick Cichy is an affiliated professor at the Institute for Technology and Innovation Management (TIM) of RWTH Aachen University and also associated with Bern University of Applied Sciences. His research agenda lies at the intersection of information systems, innovation management, and data science, with a core focus on privacy & cybersecurity, service and business-model innovation, IoT ecosystems, and text mining/visual analytics. Research Interests: Privacy & Cybersecurity: Investigating how individuals and organizations balance privacy concerns with data sharing incentives, especially in emerging technology contexts. Service & Business Model Innovation: Examining how firms create and capture value from digitally enabled services and personal data. IoT Ecosystems: Studying the dynamics of value creation, legitimacy, and privacy within interconnected Internet-of-Things environments. Text Mining & Visual Analytics: Leveraging advanced computational techniques to map and analyze large-scale discourse and innovation patterns. Across his latest publications (2014–2024), a clear thematic trajectory emerges: an evolving exploration of privacy calculus and data-sharing behavior, methodological advances in text mining for innovation studies, and longitudinal analyses of privacy discourse spanning three decades. These works collectively contribute to both theoretical development and practical guidance for policymakers and managers navigating digital transformation. Contact: Email: cichy@time.rwth-aachen.de Office hours: By appointment

Marylyn D RitchieView profile

Professor

• Computational Genomics
• Bioinformatics
• Pharmacogenomics
• +8 more

Marylyn D Ritchie, PhD, is the Edward Rose, M.D. and Elizabeth Kirk Rose, M.D. Professor at the Perelman School of Medicine, University of Pennsylvania. She concurrently serves as Director of the Institute for Biomedical Informatics, Vice President for Research Informatics for the University of Pennsylvania Health System, Director of the Division of Informatics in the Department of Biostatistics, Epidemiology, and Informatics, and Vice Dean of Artificial Intelligence and Computing. Education: BS in Biology, University of Pittsburgh at Johnstown, 1999 MS in Applied Statistics, Vanderbilt University, 2002 PhD in Statistical Genetics, Vanderbilt University, 2004 Research Interests Dr Ritchie’s work integrates computational genomics , bioinformatics , pharmacogenomics , and systems genomics to advance precision medicine. She develops statistical and machine-learning approaches to dissect epistasis , genetic epidemiology , and evolutionary computation in large-scale biobanks, with a special focus on cardiovascular disease and Alzheimer’s disease . Her group is also pioneering translational informatics methods that incorporate social determinants of health and fairness metrics into AI-driven clinical decision support. Publication Trends In 2025 alone, Dr Ritchie co-authored more than fifteen high-impact studies spanning vision-language models for 3D CT , multi-omics Alzheimer’s risk prediction , fairness in neuroimaging AI , ancestry-specific pharmacogenomics , and cloud-based polygenic risk score platforms . The collective work highlights a shift from single-omics discovery to integrative, equitable, and clinically actionable models across diverse ancestries. Awards & Honors While specific named awards were not detailed in the text, Dr Ritchie’s endowed professorship and multi-institutional leadership roles signify sustained recognition. Grants & Advising Dr Ritchie leads large NIH, foundation, and industry-funded initiatives that support interdisciplinary teams of postdocs, graduate students, and data scientists. Her lab actively mentors trainees from UPenn’s Cell and Molecular Biology and Genomics and Computational Biology graduate groups. Laboratories & Teams She directs the Ritchie Lab (ritchielab.org), which develops open-source visualization tools such as PhenoGram , PheWAS-View , and Synthesis-View for genome-wide and phenome-wide data exploration. The lab operates within the Institute for Biomedical Informatics and collaborates closely with the Penn Medicine BioBank and multiple clinical departments to translate big-data discoveries into precision medicine workflows.

Greg UrbanView profile

Professor

• Linguistic Anthropology
• Cultural Anthropology
• Cultural Motion
• +10 more

Greg Urban is the Arthur Hobson Quinn Professor of Anthropology at the University of Pennsylvania , with a career spanning over four decades. His work bridges Linguistic Anthropology , Cultural Motion , and Business Anthropology , focusing on how culture circulates through societies, corporations, and global contexts. He has held leadership roles as Chairman of Anthropology at UPenn (2001-2007, 2014-2018) and directed research initiatives like the Culture and Nuclear War Project . Education : Ph.D. in Anthropology (1978), MA (1973), BA (1971) from the University of Chicago. Key Books : Metaculture: How Culture Moves through the World (2001), The Culture Puzzle (2021), and Nation-States and Indians in Latin America (1991). Urban’s research interests include: Cultural Motion : The dynamics of cultural replication and transmission across societies Discourse Analysis : Rituals, power structures, and semiotic flows in communication Corporate Anthropology : Ethnographic studies of business organizations and citizenship Amerindian Cultures : Sociolinguistics and cultural practices in Brazil and South America His articles (1978-2025) reveal trends in: Corporate semiotics and affective cultural forms Constitutional discourse and citizenship Amazonian mythologies and ethnographic theory Metaculture as a framework for globalization Ritual practices and linguistic relativity Comparative studies of nation-state-indigenous interactions Scientific Awards : Lindback & Ira H. Abrams Awards for Teaching Guggenheim Fellowship Center for Advanced Study Fellowship American Ethnological Society Book Prize Multiple University Research Awards Urban’s advising and grants focus on: Interdisciplinary projects blending anthropology with business and political science Long-term ethnographic fieldwork in Brazil STS (Science and Technology Studies) collaborations Studies of corporate citizenship and constitutional processes

Valerio PascucciView profile

Professor

• Big Data Management
• Scientific Visualization
• Computational Topology
• +7 more

Valerio Pascucci is a Professor at the University of Utah's School of Computing and a DOE Laboratory Fellow at Pacific Northwest National Laboratory. He directs the Center for Extreme Data Management Analysis and Visualization (CEDMAV) and previously led projects at Lawrence Livermore National Laboratory and University of Texas at Austin. PhD in Computer Science (Purdue University, 2000) MSc in Electrical Engineering (University 'La Sapienza', Rome, 1993) As a pioneer in Big Data Management , Scientific Visualization , and Computational Topology , his work connects topological methods with progressive algorithms to enable interactive exploration of petascale datasets. His research spans climate modeling , neuroscience , materials science , and precision agriculture , focusing on multi-resolution techniques and geometric compression . Recent publications show specialization in web-based visualization and AI-driven analytics for climate data, with emphasis on equity in data access and FAIR data principles . His ViSUS project enables real-time data streaming from supercomputers to desktops, while NAPA explores GPU-based architectures for streaming algorithms. Scientific Awards : Best Paper Award, IEEE Pacific Visualization 2011 Best Application Paper Award, IEEE VIS 2006 DOE Laboratory Fellow He advises numerous graduate students and leads collaborations across national laboratories , universities , and industry . Funded by NSF Grant #2127548 , he develops technologies for exascale computing and geospatial intelligence .

Christopher LukasikView profile

Associate Professor

• American literature before 1900
• Art History
• Early American Studies
• +9 more

Christopher Lukasik is an Associate Professor in the Department of English at Purdue University, with affiliations in American Studies and the School of Interdisciplinary Studies (SIS). His research focuses on the intersection of American literature, visual culture, and illustration studies in the 18th and 19th centuries, with a particular interest in intermediality and cultural history. Ph.D., English, Johns Hopkins University, 2002 His scholarly work examines how visual practices shaped social and political identities, as seen in his monograph Discerning Characters: The Culture of Appearance in Early America (2011). Current research includes The Image in the Text: Intermediality, Illustration, and Nineteenth-Century American Literature , exploring literary annuals' role in developing mass visual culture. His publications span topics like biometric surveillance in early America, abolitionist visual media, and the pedagogy of drawing books. Articles highlight intermedial relationships between text and image, racial visuality, and the cultural capital of illustration. Scientific honors include: Rockwell Center Society of Fellows (2017-2019) Fulbright Specialist Grant (2018) NEH Summer Stipend (2016) Lillian Gary Taylor Fellowship (2013-14) Fulbright Scholar Grant (2009-10) NEH Long-Term Research Grant (2004-05) Lukasik actively participates in academic conferences, including upcoming presentations at SHARP 2025 and SEA 2025. He has also led Fulbright liaison training sessions and symposiums on illustration research.

Minh Hoai NguyenView profile

Assistant Professor

• Computer Vision
• Machine Learning
• Human Activity Recognition
• +5 more

Minh Hoai Nguyen is an Assistant Professor in the Department of Computer Science at Stony Brook University. He received his PhD in Robotics from Carnegie Mellon University and a Bachelor of Engineering from the University of New South Wales. Prior to Stony Brook, he was a post-doctoral research fellow at Oxford University and a Kurti Junior Research Fellow at Brasenose College. Education: PhD in Robotics, Carnegie Mellon University Bachelor of Engineering, University of New South Wales His research focuses on computer vision , machine learning , and time series analysis , particularly in developing algorithms for human action recognition , gesture detection , and expression analysis in video data. Applications include video surveillance , human-computer interaction , and medical diagnosis of behavioral disorders . His work integrates computer vision for video processing, time series analysis for modeling human behavior, and machine learning for training complex algorithms. Notable awards include: CVPR 2012 best student paper award Winner of PASCAL VOC 2012 Challenge for Human Action Recognition He teaches courses such as Video Analysis (CSE 594) and Introduction to Robotics (CSE 525) .

• Artificial Intelligence
• Machine Learning
• Knowledge Graphs
• +5 more

Dr. Madhushi Bandara is a Lecturer at the School of Computer Science, University of Technology Sydney (UTS), specializing in knowledge representation, complex system modeling, and data analytics. She leads the data management research stream at the UTS DigiSAS lab and is a core member of the Biomedical Data Science Laboratory within the UTS Australian Artificial Intelligence Institute. Her industry collaborations include Telstra, Cancer Australia, and Capsifi, focusing on AI integration in healthcare and finance. She coordinates the Business Information Systems major in UTS's Master of Information Technology program and convenes the Future Generation Enterprise Architecture Community of Practice. Education PhD in AI Systems Engineering, University of New South Wales (2020) BSc (Hons) in Engineering, University of Moratuwa, Sri Lanka (2015) Research Interests Madhushi's work bridges machine learning, knowledge graphs, and enterprise architecture to address challenges in data governance for SMEs, ESG metric management, and healthcare pathway analysis. Her research emphasizes translating cutting-edge AI into industry solutions through contextual domain knowledge integration. Scientific Awards UNSW-UTS Trustworthy Digital Society Scholarship Teaching & Leadership She teaches enterprise information systems, digital strategy, and AI for enterprises in UTS's online postgraduate programs. Her service roles include co-chairing tracks at the Australasian Conference on Information Systems and reviewing for Expert Systems with Applications.

• Information Access
• Information Retrieval
• Natural Language Processing
• +3 more

Tetsuya Sakai is a Professor at the School of Fundamental Science and Engineering within Waseda University's Faculty of Science and Engineering. His work focuses on information access, retrieval, and natural language processing, with a particular emphasis on evaluation frameworks for search systems. Affiliations: Waseda University (Faculty of Science and Engineering, School of Fundamental Science and Engineering) Academic Rank: Professor Research Interests : Dr. Sakai's research spans four key areas: (1) Information Access —designing systems for direct and immediate information delivery, (2) Search Evaluation —developing metrics like Height-Biased Gain and hierarchical intent-based diversity measures, (3) Fairness in IR —pioneering frameworks for group fairness in conversational search, and (4) Statistical Reform —advocating Bayesian methods and robust experimental design. His work also addresses privacy inconsistencies in mobile apps and cognitive biases in LLMs. Scientific Awards : Notable recognitions include induction into the SIGIR Academy (2023) , ACM Distinguished Member (2018) , ACM Senior Member (2016) , and multiple DEIM/FIT/CSS Best Paper Awards . He has received teaching honors like the Waseda Presidential Teaching Award (2016) and WASEDA e-Teaching Award (2018) . Article Trends : Recent publications highlight: Advancements in LLM-assisted relevance assessments and hallucination diagnostics for tool-augmented models Conversational search fairness through multi-level evaluation frameworks and group diversity metrics Innovations in 3D medical reconstruction from clinical data and multimodal uncertainty modeling Statistical rigor via randomization tests , credible intervals , and topic set design Privacy analysis in mobile app descriptions and cognitive bias studies in search interaction

• Corpus Linguistics
• Educational Technology
• Natural Language Processing
• +5 more

Laurence Anthony is a Professor at Waseda University's School of Creative Science and Engineering, specifically affiliated with the Center for English Language Education in Science and Engineering (CELESE). He has held this position since 2009, having previously served as an Associate Professor at the same institution from 2004-2009. His academic journey began with a BSc from The University of Manchester (1991), followed by an MA (1997) and PhD (2002) from The University of Birmingham. Anthony's research centers on corpus linguistics, educational technology, and natural language processing applications in foreign language teaching. He is renowned for developing AntConc, a widely used freeware corpus analysis toolkit, along with numerous other educational software tools including AntWordProfiler, FireAnt, and ProtAnt. His work bridges linguistic theory with practical classroom applications, particularly in data-driven learning approaches for English as a Foreign Language contexts. His publication record is extensive with over 50 papers, 12,115 Google Scholar citations, and an h-index of 45. His recent work increasingly explores the intersection of corpus linguistics and artificial intelligence, examining how language models can enhance language teaching and analysis. Anthony's research has evolved from foundational corpus tool development to sophisticated applications in vocabulary profiling, writing analysis, and AI-assisted language learning. Among his notable recognitions are the Waseda University 6th e-Teaching Award (2018), the National Prize of the Japan Association of English Corpus Studies (2012), and the L'Oreal Art and Science of Color Gold Prize (2005). He serves on multiple editorial boards including for Studies in Corpus Linguistics, Journal of Asia TEFL, and Corpus Linguistics Research Journal. Anthony actively contributes to the academic community through numerous presentations at international conferences, recent ones including talks on AI integration with corpus methods at Corpus Linguistics 2025 and the LSP-Num Conference. His professional activities demonstrate ongoing engagement with both theoretical developments and practical applications in language education technology.

Peter HastieView profile

Professor

• Physical Education
• Sport Pedagogy
• Teacher Education
• +3 more

Peter Hastie is a Wayne T. Smith Distinguished Professor in the School of Kinesiology at Auburn University. With over 224 peer-reviewed publications, he is recognized as the top physical education scientist in the United States and ranks fourth globally. His work focuses on innovative pedagogical approaches, particularly the Sport Education Model, and has been adopted internationally across diverse educational contexts. Expertise: Sport Education Model, physical education curriculum design, teacher development, and motor skill progression in children. Global Impact: Implemented educational frameworks in Saudi Arabia, Russia, Spain, Ireland, Portugal, and China, contributing to widespread curriculum adaptations and teacher training programs. Hastie’s research emphasizes student engagement, inclusive education, and interdisciplinary integration (e.g., combining mathematics with PE). He co-created Auburn’s ActiveU and ActiveMe online physical education resources, now adopted by institutions nationwide and in multiple languages. Awards & Recognition: 2024 Creative Research and Scholarship Award from Auburn University. Inducted into the National Academy of Kinesiology, reflecting his status as a leading scholar and practitioner. Hastie has delivered keynote speeches on six continents, advanced the understanding of skill development in children with disabilities, and contributed to policy discussions on health-related fitness education. His work bridges research and practice, influencing both academic discourse and real-world teaching methodologies.

Zsigmond LuczaView profile

Assistant Professor

• Contemporary Painting
• Transmedia Art
• Visual Communication
• +3 more

Zsigmond Lucza (born 1978 in Budapest) is a Hungarian contemporary artist and university assistant professor at the Hungarian University of Fine Arts, Department of Visual Art since 2022. He holds a DLA (Doctor of Liberal Arts) degree from the University of Pécs Faculty of Arts (2011-2014) and has extensive international experience including studies at the University of Lapland in Finland (2012-2013). Lucza's educational background includes dual Master's degrees from the Hungarian University of Fine Arts (2002-2007) in both Painting and Visual Art Teacher programs, along with foundational training at the Buda Drawing School (2000-2002). His academic career includes teaching positions at Jelky András Applied Arts Vocational High School (2014-2018), Modell Fashion School (2008-2012), and Kolumbusz Humanities High School (2005-2007). Lucza's artistic practice spans contemporary painting, transmedia art, and mixed media works, with significant focus on digital integration in traditional art forms. His research interests center on transmedia tendencies in contemporary Hungarian painting, visual communication, and the evolving relationship between digital and physical art spaces. His work often explores identity, perception, and the integration of technology in artistic expression, creating pieces that bridge traditional painting techniques with contemporary digital aesthetics. His artistic output shows a consistent evolution from figurative works toward more experimental transmedia approaches, with recent projects focusing on environmental reflection, digital portraiture, and collaborative installations. Lucza's work demonstrates a sophisticated understanding of both traditional painting techniques and contemporary digital media, creating a distinctive visual language that addresses current artistic concerns while maintaining strong technical foundations. Lucza has received multiple awards including an Erasmus scholarship for study at the University of Lapland, a scholarship from the Budapest Gallery and Kunststiftung Baden-Württemberg, and first prizes in national competitions. His professional affiliations include membership in the Hungarian Artists' Association (MAOE) since 2007, the MAMŰ Society since 2015, and non-academic membership in the Hungarian Academy of Arts (MMA) since 2022. As an educator, Lucza has conducted numerous workshops internationally including the Experimental Drawing Course at the Latvian Academy of Arts and Transmedia Workshops at the University of Pécs. His curatorial work includes the 'Medium Summoners' exhibition at MAMŰ Gallery in Budapest (2017). Lucza maintains an active exhibition schedule with solo shows across Hungary, Finland, and Slovenia, alongside participation in numerous international artist colonies and collaborative projects.

Lou SafraView profile

Assistant Professor

• Political Psychology
• Cognitive Science
• Social and Political Behavior
• +3 more

Lou Safra is Assistant Professor in political psychology at the Center for Political Research (CEVIPOF) of Sciences Po , Paris, and co-directs the Evaluation of Democracy Research Group at the Laboratory for Interdisciplinary Evaluation of Public Policies (LIEPP) . She is also associate researcher at the Institut d’Études Cognitives (École Normale Supérieure, Paris), bridging political science with cognitive neuroscience. Education: PhD in Cognitive Science, École Normale Supérieure, Paris (2017) Research Interests: Lou Safra investigates the cognitive mechanisms underlying social and political behaviour , focusing on leader choice and cooperation . She adopts an ecological and evolutionary perspective to understand inter-individual differences across space and time. Her methodological toolkit includes behavioural experiments , social surveys , computational modelling , and cultural artefact analysis such as paintings and books. Publication Trends: Her recent work (2020–2024) explores how early-life adversity shapes trust and authoritarian preferences , how cultural evolution influences concepts like love in literature, and how public opinion on defence issues evolves during the Ukraine war . Studies appear in high-impact journals spanning political science , psychology , behavioural economics , and cultural evolution . Scientific Awards & Funding: No specific awards or fellowships are listed in the provided text. Advising & Grants: No named students or specific grant details are provided in the text. Labs & Teams: She is affiliated with CEVIPOF–Sciences Po , LIEPP , and the Laboratoire de Neurosciences Cognitives & Laboratoire de Neurosciences Cognitives et Computationnelles at ENS, indicating active collaboration across political science, cognitive neuroscience, and computational modelling teams.

Daniel HershcovichView profile

Assistant Professor

• Natural Language Processing
• Cross-Cultural NLP
• Computational Linguistics
• +7 more

Daniel Hershcovich is a Tenure-Track Assistant Professor at the Natural Language Processing section of the Department of Computer Science, University of Copenhagen. His research focuses on cross-cultural adaptation of language models, integrating human values into AI systems, and evaluating AI's real-world impact in domains like law, literature, and food culture. Research Themes Cultural value alignment in LLMs Multimodal models for accessibility Cross-cultural recipe and food knowledge Historical Scandinavian text analysis Ethical AI and bias mitigation Scientific Recognition SAC Highlight Award (ACL 2025) Outstanding Paper Award (ACL 2017) Advising & Grants : Mentions collaborations on multiple EMNLP/ACL/CoNLL papers. Leads Independent Research Fund Denmark project ALIKE (2025-2027) and contributes to Innovation Fund Denmark's XHAILe (2025-2028). Co-organized SemEval 2019 and CoNLL 2019/2020 shared tasks. Labs & Teams : Leads the CoAStaL research group. Collaborates with teams at IBM Research Haifa, University of Manchester, and Wuhan University of Science and Technology.

Xiaobo LiView profile

Professor

• Neuroscience
• Medical Imaging
• Machine Learning Applications in Neurology
• +3 more

Xiaobo Li is a Professor in the Department of Bio-Medical Engineering at New Jersey Institute of Technology. Holding a Ph.D. in Computer Aided Geometric Design from the University of Birmingham and a B.S. in Automation from Nanjing University of Aeronautics, their research bridges computational methods with neuroimaging and psychiatric disorder analysis. Ph.D., University of Birmingham (Computer Aided Geometric Design, 2004) B.S., Nanjing University of Aeronautics (Automation, 1999) Dr. Li’s work focuses on applying machine learning and graph theory to understand brain network abnormalities in conditions like ADHD , schizophrenia , and traumatic brain injury . Their studies analyze structural-functional connectivity , reward processing , and gut-brain axis interactions using fMRI , fNIRS , and diffusion tensor imaging . Recent publications highlight their development of tools like the GAT-FD MATLAB toolbox for brain network analysis and their exploration of multimodal MRI in schizophrenia diagnosis. They also investigate the neurobiological effects of photobiomodulation and vision therapy interventions.

• Artificial Intelligence
• Reinforcement Learning
• Evolutionary Computation
• +1 more

Tim Rocktaschel is a Professor of Artificial Intelligence in the Department of Computer Science at University College London (UCL), where he has been working since 2018. He was promoted to Professor in October 2023, having previously served as an Associate Professor (2021-2023) and Lecturer (2018-2021) at the same institution. His educational background includes a Doctorat from University College London (2017) and a Diplom Informatiker from Humboldt-Universitat Berlin (2012). Rocktaschel's research focuses on the cutting edge of artificial intelligence, with particular emphasis on reinforcement learning, evolutionary computation, and open-ended learning systems. His work explores how AI systems can learn more efficiently through better exploration strategies, environment design, and the integration of language models with reinforcement learning frameworks. His recent publications reveal a strong trend toward developing more efficient and generalizable AI systems. The research spans unsupervised environment design, prompt engineering for self-improving systems, exploration strategies in reinforcement learning, and the application of language models to enhance policy learning. His work often bridges theoretical AI concepts with practical implementations, as evidenced by tools like GriddlyJS for reinforcement learning development. Rocktaschel maintains an active presence in the AI research community with numerous publications in top venues including NeurIPS, ICML, and the Journal of Artificial Intelligence Research. His work on zero-shot generalization, pragmatic understanding in language models, and open-ended learning environments has garnered significant attention in the field. He is actively involved in developing tools and datasets for the AI community, such as the large-scale NetHack dataset, which provides a complex environment for testing reinforcement learning algorithms. His research continues to push the boundaries of what's possible in artificial intelligence, particularly in creating systems that can learn and adapt in complex, open-ended environments.