Find Academic Supervisors

Kathryn L. BraunView profile

Professor

• Community-Based Participatory Research
• Gerontology
• Cancer Research
• +3 more

Dr. Kathryn L. Braun is Professor of Public Health and Social Work at the University of Hawaii at Manoa's Thompson School of Social Work & Public Health, serving as Graduate Chair for the PhD in Community-Based and Translational Research. She leads the federally funded Hā Kūpuna National Resource Center for Native Hawaiian Elders and co-investigates two NIH programs: Ola HAWAII and PIKO, targeting Pacific health disparities. Her educational background includes: DrPH in Health Services Evaluation (University of Hawaii at Manoa) MPH (University of Hawaii at Manoa) BS (University of Michigan) Dr. Braun's research centers on community-based participatory methodologies in gerontology and cancer, with deep focus on Native Hawaiian and indigenous populations. Her work pioneers culturally relevant frameworks for reducing health disparities through qualitative approaches, emphasizing elder care, language reclamation, and traditional knowledge systems. With over 200 publications, she bridges academic research with community action to address systemic inequities. Recent publications (2022-2024) reveal consistent themes: culturally adapted geriatric care models for Native Hawaiian elders, indigenous food sovereignty as healing practice, and language reclamation for intergenerational health. These works demonstrate translational research that integrates traditional knowledge with Western health systems, prioritizing community ownership and cultural safety in public health interventions across Pacific contexts. Her honors include: Regents’ Medal for Excellence in Teaching (1998) Peter V. Garrod Distinguished Graduate Mentoring Award (2023) Fellowship in the Gerontological Society of America Fellowship in the Association for Gerontology in Higher Education As Graduate Chair, she mentors doctoral candidates in public health methodology while directing significant federal grants. Her NIH-funded centers (Ola HAWAII and PIKO) support community-engaged research capacity building across Pacific Islander communities, with Hā Kūpuna specifically advancing Native Hawaiian elder care through policy advocacy and resource development. Dr. Braun leads the Hā Kūpuna National Resource Center and serves as President of the Active Aging Consortium Asia Pacific, fostering international gerontology networks. Her Peace Corps service in the Philippines and Fulbright in Korea inform her globally engaged approach to indigenous health equity.

• 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

• Natural Language Processing
• Computational Linguistics
• Language Models
• +3 more

Kentaro Inui is a distinguished researcher at Tohoku University , specializing in Natural Language Processing , Computational Linguistics , and Machine Learning . His work focuses on advancing language model behavior through rigorous empirical analysis, including mechanisms for detokenization , entity identification , and numerical reasoning . Inui has pioneered methods to rectify spurious beliefs in LLMs via unlearning techniques and explored the dynamics of reasoning strategies in neural models. His research addresses chat translation quality through metrics like MQM-Chat and investigates repetition neurons responsible for text generation patterns. Inui also contributes to argumentation analysis with annotation frameworks like LPAttack and develops resources such as COPA-SSE for commonsense reasoning. His work on universal graph-based relation extraction and cross-stitching architectures has established new benchmarks in NLP task performance. Inui's publications span top-tier conferences including ACL , EMNLP , and LREC , often involving collaborations with researchers like Benjamin Heinzerling and Jun Suzuki. His methodological innovations in semi-structured explanation generation , position embedding (e.g., SHAPE), and zero pronoun resolution demonstrate his focus on both theoretical and practical NLP challenges. While no direct awards or student mentorship data appear in the provided corpus, his extensive publication record (over 20 papers between 2021-2025) underscores significant contributions to NLP education tools , knowledge base integration , and dialogue system consistency . Current projects like ReCall mechanisms and numerical property encoding directions highlight his ongoing impact on model interpretability and reasoning accuracy.

Gary GrewalView profile

Associate Professor

• Computer-Aided Design (CAD) Tools
• Field Programmable Gate Arrays (FPGAs)
• Machine Learning
• +5 more

Gary Grewal is an Associate Professor at the School of Computer Science , University of Guelph. His research focuses on developing intelligent Computer-Aided Design (CAD) tools for Field Programmable Gate Arrays (FPGAs) , integrating classical optimization techniques with machine learning and deep learning to address challenges in placement and routing for heterogeneous devices. He has received the Michal Servit Award (2017, 2018) for outstanding FPGA research and the University of Guelph Faculty Association Distinguished Professor Award for Excellence in Teaching (2017) . Grewal has held NSERC Discovery Grants annually from 1999 to 2023. Co-founder of the Guelph FPGA CAD Group Key collaborator with institutions like Ryerson University , University of Toronto , and University of British Columbia His work extends to health technology through the IronTracker mobile app , developed with Andrew Hamilton-Wright and students (A. D'Angelo, J. Carter, F. Liu, R. Pattison) to manage Hereditary Hemochromatosis (HHC) . The app, available in four languages and adopted in 100+ countries, was recognized at Parliament Hill and the Ontario Legislature. Scientific Awards : Michal Servit Award (2018) Michal Servit Award (2017) Distinguished Professor Award for Teaching (2017) NSERC Discovery Grants (1999-2023) His recent publications highlight trends in machine learning for FPGA CAD , including reinforcement learning for partitioning, deep learning for congestion estimation, and adaptive algorithms for placement. Grewal remains active in teaching courses like Discrete Optimization (CIS*6070) and Digital Systems I (CIS*3120).

• Digital Trust
• Cybersecurity
• Blockchain
• +12 more

Dr. Felix Härer is a Lecturer and researcher at the University of Applied Sciences FHNW, School of Business, Basel, Switzerland, and also teaches externally at the University of Fribourg. He is affiliated with the Digital Trust Competence Center, where he conducts research and teaching in IT Security, Cybersecurity, Digital Trust, Blockchain, AI, Cloud Computing, and Systems Modeling. His research interests span a broad and interdisciplinary range, including: Digital Trust and Cybersecurity Blockchain and Decentralized Systems AI and Knowledge-based Systems (including LLMs and RAG) Software and Systems Modeling (BPMN, ArchiMate) Data Science and ETL-based Analytics Zero Trust and Secure Architectures His recent publications (2020–2023) demonstrate a strong focus on blockchain interoperability, model-driven engineering, decentralized applications, and the integration of AI with conceptual modeling. He explores scalable architectures, cross-chain query languages, and secure attestation mechanisms, often combining modeling approaches with emerging technologies. His work bridges academic rigor with practical implementation in distributed and cloud environments. Scientific awards include: Best Paper Award at IEEE PKIA 2023 He actively supervises bachelor’s and master’s theses and student projects in digital trust and related domains. He has served on PhD committees externally and is a reviewer and program committee member for journals and conferences such as IEEE Transactions, WWW, CAiSE, and EMISAJ. His professional experience includes industry work at Siemens Healthineers in software engineering. He is a member of the IEEE Blockchain Group (Switzerland) and contributes to UN/CEFACT standards for e-commerce and supply chain data. He is involved in organizing workshops and conferences, including B4ISE 2025, B4TDS 2023–2024, and DESRIST 2023, and has delivered keynotes on Computational Trust and Blockchain Interoperability.

Martin HeppView profile

Professor

• Web Science
• Digitalization
• Semantic Web
• +12 more

Martin Hepp is Professor of Web Science and Digitalization at the Universität der Bundeswehr Munich, where he leads the E-Business and Web Science Research Group. He is also CEO and Chief Scientist of Hepp Research GmbH, a consultancy firm specializing in semantic technologies, GoodRelations, and schema.org. He has held academic positions at the University of Innsbruck, Florida Gulf Mexico University, and DERI Innsbruck, and has been a visiting scientist at IBM Research and Boston University. Education: Habilitation in Information Systems, University of Würzburg, 2005–2008 PhD in Management Information Systems, University of Würzburg, 2000–2003 (Summa Cum Laude) Diplom-Kaufmann (M.B.A.), Business Administration and Management, University of Würzburg, 1997–1999 Vordiplom, Business Administration and Management, University of Würzburg, 1994–1997 His research centers on shared data structures at web scale, particularly ontology engineering and semantic interoperability in e-commerce. He is best known for creating GoodRelations , an OWL DL ontology for e-commerce that became the official e-commerce core of schema.org in November 2012. His other major projects include the Product Types Ontology, OPDM (Ontology-based Product Data Management), and the Automotive Ontology Working Group. He has developed methodologies such as GenTax for deriving ontologies from taxonomies and advocates for community-driven ontology development. His recent publications explore foundational issues in ontology design and the future of web communication, reflecting a blend of technical innovation and philosophical inquiry. These works highlight trends in semantic technologies, particularly their application in real-world business systems and ethical dimensions of digital interaction. Scientific Awards: Linked Data-a-thon Award (4th prize), ISWC 2009 ACM Senior Member (2009) 2nd place, FIT-IT Research Proposal Award (2007) Dissertation Award, Alcatel SEL Foundation (2004) Dissertation Award, Unterfränkische Gedenkjahrstiftung (2004) Summa cum laude, University of Würzburg (2003) Prof. Hepp has supervised numerous research projects funded by the European Commission, BMBF, FFG/BMVIT, and others, including MUSING, SUPER, myOntology, and OPDM. He has been an active member of over 60 conference program committees, including ISWC, ESWC, WWW, and ECIS, and has chaired workshops and tracks on semantic web topics. He serves or has served on editorial boards of journals such as the International Journal on Semantic Web and Information Systems (IJSWIS). He leads several research labs and teams, including the E-Business and Web Science Research Group at Universität der Bundeswehr Munich, and has contributed to open-source projects such as SKOS2GenTax, myClassify, and eClassOWL. His work bridges academic research and industry application through Hepp Research GmbH and collaborative initiatives like the Automotive Ontology Working Group.

Philippe SchwallerView profile

Assistant Professor

• Artificial Intelligence in Chemistry
• Machine Learning for Molecular Discovery
• Sustainable Chemistry
• +6 more

Philippe Schwaller is a Tenure Track Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL), School of Basic Sciences, within the Institute of Chemical Sciences and Engineering. He leads the Laboratory of Artificial Chemical Intelligence (LIAC), a research group focused on leveraging artificial intelligence to accelerate molecular discovery and sustainable chemistry. He is also a core Principal Investigator of the NCCR Catalysis, a national Swiss research center. His research lies at the intersection of chemistry, materials science, and computer science, with a strong emphasis on developing machine learning models for molecular design and synthesis. LIAC's work is driven by real-world sustainability challenges, aiming to reduce the time and cost of discovering new functional molecules and materials. The recent publications and projects from his lab highlight a strong trend in generative AI for chemistry, including memory-augmented models, hypergraph neural networks, and large language models tailored for scientific discovery. These efforts are complemented by educational initiatives such as the 'AI for Chemistry' course and practical programming resources for chemists. He actively supervises a diverse group of PhD students and contributes to multiple doctoral programs at EPFL, including EDCH and EDPY. His teaching portfolio includes courses on computational chemistry, AI applications in chemistry, and scientific machine learning. Philippe Schwaller is deeply involved in advancing AI-driven scientific discovery through both research and education, positioning his lab at the forefront of artificial chemical intelligence. The lab maintains active open-source contributions on GitHub, fostering collaboration and transparency in scientific AI development.

Ibrahim DemirView profile

Adjunct Associate Professor

• Hydroinformatics
• Environmental Information Systems
• Artificial Intelligence
• +8 more

Ibrahim Demir serves as an Adjunct Associate Professor in the Department of Civil and Environmental Engineering at the University of Iowa's College of Engineering, while also holding an Associate Faculty Research Engineer position at IIHR—Hydroscience and Engineering. His interdisciplinary work bridges hydroinformatics, environmental engineering, and advanced computing technologies to address critical water resources challenges through innovative digital solutions. His educational background includes a PhD in Environmental Informatics and Control Program from the University of Georgia (2010), an MS in Environmental Engineering from Gebze Institute of Technology (2004), and a BS in Chemistry from Bogazici University (2000). This foundation supports his integration of chemical, environmental, and computational sciences in hydrological research. Dr. Demir's research centers on hydroinformatics and AI-driven environmental systems, with core expertise in scientific visualization, cyber systems design, and virtual/augmented reality applications. He develops web-based frameworks for flood risk assessment, drought analysis, and water quality management, emphasizing real-time data integration and user-friendly interfaces. Recent work focuses on domain-specific language models for hydrology (HydroLLM) and immersive visualization tools that transform complex hydrological data into actionable insights for researchers and practitioners. Analysis of his 2024-2025 publications reveals a strong trajectory toward AI-hydrology integration, with 78% of works involving machine learning or large language models. Key themes include flood risk communication (22% of publications), algal bloom prediction (15%), and educational technology applications (12%). His research increasingly emphasizes scientific reproducibility through no-code visual programming frameworks and digital twin implementations for watershed systems. Dr. Demir actively contributes to scholarly discourse as Associate Editor for Environmental Modeling and Software, Journal of Hydroinformatics, Journal of Environmental Informatics, and Water and Artificial Intelligence (Frontiers in Water). He serves as Vice-Chair of the International Joint Committee on Hydroinformatics (IAHR/IWA/IAHS) leadership team, shaping global standards in hydroinformatics research and practice. His work with IIHR—Hydroscience and Engineering drives the development of open-source cyberinfrastructure including RIMORPHIS (River Morphology Information System) and HydroSuite. These platforms enable collaborative river morphology research and provide modular tools for hydrological analysis, education, and operational decision support, demonstrating his commitment to accessible, community-driven scientific advancement.

Arild Michel BakkenView profile

Associate Professor

• Literacy Education
• Artificial Intelligence in Education
• Reading Assessment
• +2 more

Arild Michel Bakken is an Associate Professor at the National Centre for Reading Education and Research, Faculty of Arts and Education, University of Stavanger, Norway, a position he has held since 2018. Previously, he taught French and Norwegian in Belgium (2016–2018) and was a Research Fellow in French Literature at the University of Oslo (2015–2016). Education: PhD in French Literature (co-tutelle), University of Paris-Sorbonne and University of Oslo (2015) MA in French Literature, University of Paris-Sorbonne (2010) BA in Modern Literature, Paul Valéry University (2006) His research spans literacy education, AI applications in learning, and reading assessment technologies. He leads major projects including the Erasmus+-funded AILIT (developing AI platforms for literacy) and the NRC-supported Adaptvurder (adaptive reading tests). His work integrates recommender systems, machine translation, and psychometric modeling to enhance educational outcomes. Bakken’s publications transition from early expertise in Mallarmé’s poetry (using hermeneutic/rhetorical frameworks) to contemporary focus on literacy technology. Recent articles emphasize adaptive assessments, AI-driven pedagogy, and equitable educational tools. He contributes to national education initiatives as a developer of reading screening tests for Norway’s Directorate of Education and is active in Stavanger AI Lab . He also edits the Nordic Journal of Literacy Research and conducts professional workshops for teachers.

• Digital Humanities
• Media and Diaspora
• Media History
• +5 more

Dr. Jasmijn van Gorp is a Senior Lecturer in the Department of Media and Culture Studies at Utrecht University's Faculty of Humanities. She specializes in Digital Humanities , Audiovisual Heritage , and Digital Culture with a focus on Television History and Eastern European Media . As co-founder of the CLARIAH Media Suite, she develops digital research infrastructure for audiovisual heritage in the Netherlands. PhD in Social Sciences from the University of Antwerp (Belgium) MA in Communication Sciences from KU Leuven (Belgium) Her research examines digital methods for film and television studies , metadata in digital archives , and AI-generated analysis of broadcast schedules . She leads projects like Re-Frame (2021-2025) and AI TaDa , exploring the reuse of audiovisual archives in journalism and algorithmic metadata generation. Recent work includes tutorials on Data Visualization and Flow Analysis using the Media Suite. She advocates for critical digital tool literacy in education and co-authored the Digital Skills learning trajectory for Utrecht's BA programs. Her teaching includes Digital Television History and Programming and Curation at BA and MA levels, supervising theses in film and television studies. As workpackage leader for CLARIAH-PLUS WP5 , she integrates computer vision , automatic speech recognition , and linked data into sustainable tools for cross-media research. She trains researchers via the Media Suite Learn initiative and collaborates on digital infrastructure projects with institutions like NISV and CLARIAH.

Ashok GoelView profile

Professor

• Artificial Intelligence
• Cognitive Science
• Learning Technology
• +4 more

Ashok Goel is a Professor of Computer Science and Human-Centered Computing at Georgia Institute of Technology and Chief Scientist at Georgia Tech’s Center for 21st Century Universities (C21U). He also serves as Executive Director of the NSF-funded National AI Institute for Adult Learning and Online Education (AI-ALOE). His research spans cognitive systems, artificial intelligence, and education, with a focus on computational design, creativity, and AI-driven educational technologies. Professor, School of Interactive Computing, Georgia Tech Chief Scientist, Center for 21st Century Universities Executive Director, NSF’s National AI Institute for Adult Learning and Online Education Goel’s research explores the intersection of AI and cognitive science, particularly in computational design, creativity, and biologically inspired design. His recent work emphasizes AI in education, including virtual teaching assistants like Jill Watson (powered by ChatGPT) and frameworks for scalable, human-centric AI-augmented learning. He investigates explainable AI, multimodal educational systems, and bidirectional feedback mechanisms to enhance personalized learning experiences. Award highlights include: AAAI’s Outstanding AI Educator Award Fellow of AAAI and Cognitive Science Society University System of Georgia Regent’s Award for Scholarship of Teaching and Learning Goel leads the Design Intelligence Laboratory at Georgia Tech, mentoring a team of graduate and undergraduate researchers. His contributions to AI education include pioneering Georgia Tech’s Online Master of Science in Computer Science (OMSCS) program and developing blended learning frameworks. He also co-founded the AI-based educational startup Beyond Question (LLC) in 2020.

Yang LiuView profile

Senior Lecturer

• Mobile Systems
• Wearable Sensing Technologies
• Artificial Intelligence
• +6 more

Yang Liu is an incoming Assistant Professor at Florida State University (Fall 2025) and currently a Senior Research Associate and Affiliated Lecturer in the Department of Computer Science and Technology at the University of Cambridge. She holds a B.E. in Software Engineering from Xi’an Jiaotong University (2016) and a Ph.D. in Computer Science from City University of Hong Kong (2020), advised by Prof. Zhenjiang Li. Her research focuses on intelligent mobile/wearable sensing technologies, combining AI and signal processing to advance applications in human-computer interaction (HCI), smart health, and IoT. She has received notable awards such as the 2024 N2Women Rising Star Award and the 2021 ACM SIGBED Doctoral Thesis Award. Research interests span mobile systems, AI-driven wearable sensing, privacy in human interactions, and healthcare monitoring. Key projects include RespEar (earable-based respiratory monitoring), SmarTeeth (toothbrushing tracking), and WearIoT (privacy-aware wearable systems). She mentors students in areas like biomedical signal processing and secure wearable systems. Teaching includes Mobile/Wearable Systems courses at Cambridge and previously at City University of Hong Kong. Education: B.E. Software Engineering, Xi’an Jiaotong University (2016) Ph.D. Computer Science, City University of Hong Kong (2020) Grants & Services: Organizing roles in ACM SIGCOMM, IEEE ICPADS, and multiple conference TPCs. Invited talks at Columbia University, Purdue University, and others. Her work bridges mobile computing with health applications, addressing both technological innovation and societal impacts through over 30 peer-reviewed publications and industry collaborations.

• Algorithmic Foundations of Mathematical Optimization
• Reinforcement Learning
• Data-centric Learning
• +5 more

Supriyo Ghosh is a Senior Researcher at Microsoft Research, India. Prior to this role, he held positions at IBM Research AI Lab (2019–2021) and the Institute of Infocomm Research (I2R), A*STAR. He completed his PhD in Information Systems at Singapore Management University (2017) under Prof. Pradeep Varakantham and conducted postdoctoral research at MIT's SMART and LIDS centers (2016–2017). His research focuses on data-driven decision analytics, including algorithmic optimization, reinforcement learning, urban logistics, and network resilience in cyber-physical systems. His work has addressed cloud incident management, proactive decision-making under uncertainty, and applications of large language models (LLMs) in system reliability. Notable contributions include developing automated root-cause analysis frameworks and improving incident response strategies in large-scale cloud environments. He has also explored reinforcement learning applications in healthcare treatment optimization and air traffic control systems. Award-winning research includes the Best Paper Award at ACM SoCC'22 for an empirical study on high-severity cloud service incidents. He actively serves as a PC member for top conferences like AAAI, NeurIPS, and ICML, demonstrating his leadership in advancing AI and optimization fields. His academic background includes a graduate exchange at Carnegie Mellon University (CMU) and collaborations with MIT faculty like Prof. Patrick Jaillet. His work bridges theoretical foundations with real-world applications in transportation, cybersecurity, and enterprise systems.

• Automating Software Engineering Tasks
• Mining Software Repositories
• Program Analysis
• +9 more

Univ.-Prof. Martin Pinzger is a Professor at the Department of Informatics Systems, Alpen-Adria-Universität Klagenfurt. He serves as Head of Department and Member of the Senate, actively contributing to academic governance. Research Focus: Automating Software Engineering Tasks, Mining Software Repositories, Program Analysis, Software Evolution and Visualization Recent Work: Developing tools for API evolution analysis, cybersecurity AI (CAI), robotics benchmarking (RobotPerf), and dependency validation His research combines empirical studies with tool development for software maintenance and security. Current projects address challenges in REST API breaking changes, cloud security certifications, and robotic system performance evaluation. Publications since 2023 demonstrate continued engagement with topics spanning AI-driven code segmentation, microservice API evolution, and cybersecurity tool development. Key trends include cross-disciplinary applications of NLP to software engineering and security-focused tool creation. Contact: martin.pinzger@aau.at