Find Academic Supervisors

• AI Ethics
• Epistemic Logic
• Philosophy of Language
• +3 more

Simon David Goldstein is an Associate Professor at the Dianoia Institute of Philosophy within the Faculty of Theology and Philosophy. His research focuses on epistemic logic, formal epistemology, philosophy of language, and AI ethics. He explores topics such as knowledge norms, epistemic modalities, and ethical implications of AI systems. Research Interests: AI Ethics: Examining AI safety, deception, and existential risks Epistemic Logic: Investigating knowledge fragility, contextualism, and modal credence Philosophy of Language: Analyzing dynamic semantics and attitude reports Formal Epistemology: Probability and modal reasoning in epistemic contexts Recent Work Trends: Recent publications emphasize interdisciplinary approaches to AI ethics, integrating technical AI challenges with philosophical frameworks. His work on epistemic modals and contextualism bridges semantics and epistemology. Advising & Grants: No specific grants or advisees listed. Active in collaborative research with institutions like the Dianoia Institute. Labs/Teams: Affiliated with the Dianoia Institute's research groups on ethics and epistemology.

Cutcha Risling BaldyView profile

Associate Professor

• Indigenous feminisms
• Decolonization
• California Indian politics & culture
• +3 more

Cutcha Risling Baldy is an Associate Professor and Program Leader of the Environment & Community Masters Program at California Polytechnic State University, Humboldt. She holds a Ph.D. from the University of California, Davis. Her work focuses on Indigenous feminisms, decolonization, California Indian politics, environmental justice, and community-based research. She co-directs the Rou Dalagurr Food Sovereignty Lab & Traditional Ecological Knowledges Institute. Dr. Baldy has received the 2025 James Irvine Foundation Leadership Award for her contributions to Indigenous education and activism. Her research emphasizes revitalizing Indigenous traditions, particularly through women’s coming-of-age ceremonies and ceremonial practices. She is affiliated with the Native American Studies department and collaborates with the Native Women's Collective. Her articles address topics like Indigenous STEM education, social media activism (#NoDAPL movement analysis), and decolonizing pedagogy. She advocates for integrating Traditional Ecological Knowledge (TEK) into academic and community frameworks while challenging colonial policies impacting Indigenous communities. Dr. Baldy’s book We Are Dancing for You explores Native feminisms through the lens of Yurok coming-of-age ceremonies, emphasizing cultural survivance and community knowledge. She also co-leads the Food Sovereignty Lab, advancing Indigenous food systems and ecological stewardship.

Peter BellView profile

Professor

• Automatic Speech Recognition (ASR)
• Cross-domain and Cross-lingual Adaptation
• Speech Representation Learning
• +4 more

Roles: Prof Peter Bell holds a personal chair in speech technology at the University of Edinburgh's School of Informatics and is a core member of the Centre for Speech Technology Research (CSTR). His primary research focus is automatic speech recognition (ASR), particularly in cross-domain adaptation, lightly supervised training, and minority language systems. He teaches the Automatic Speech Recognition course and advises multiple PhD students. Research Interests: Prof Bell's work spans ASR system development for diverse domains, audio-visual integration, end-to-end models, and under-resourced languages. His projects include the CoG-MHEAR healthcare initiative and the Unmute project addressing language marginalization. He has pioneered techniques for speaker adaptation, raw-waveform modeling, and multi-task learning. Commercial Activities: He advises industry on speech tech adoption, co-founded Quorate Technology (acquired by LSEG), and provides consultancy to firms developing speech solutions. His work bridges academic research with commercial impact through projects like the BBC's MGB Challenge and EU-funded SUMMA platform. Grants & Projects: Leads EPSRC-funded CoG-MHEAR and Unmute initiatives, collaborates on IARPA MATERIAL for low-resource ASR, and contributed to the SpeechWave waveform-based ASR project. His research has been supported by Bloomberg, Ericsson, Samsung, and Toshiba. Labs & Teams: Active in CSTR, leading teams in speech representation learning, adaptation techniques, and multi-modal ASR. His lab supports interdisciplinary work with NLP, HCI, and biomedical engineering groups. Personal: A passionate hillwalker, he explores Scottish Highlands and Corbetts. Previously active in Edinburgh University Hillwalking Club, his outdoor pursuits reflect his disciplined approach to research exploration.

Bill HoweView profile

Associate Professor

• Data Science
• Algorithmic Fairness
• Urban Computing
• +7 more

Bill Howe is an Associate Professor at the University of Washington's Information School, with adjunct appointments in Computer Science & Engineering and Electrical Engineering. He serves as Founding Program Director and Faculty Chair of the UW Data Science Masters Degree, Founding Associate Director and Senior Data Science Fellow at the UW eScience Institute, Director of the Urbanalytics Lab, and Co-Founding Director of the Center for Responsible AI Systems and Experiences. He also co-founded Urban@UW and created the first Data Science MOOC through Coursera. His research focuses on making data science accessible in public sector applications with emphasis on equity, privacy, and compliance. Current interests include: Algorithmic fairness in urban and social contexts Privacy-preserving synthetic data generation Machine learning for heterogeneous data Database systems and high-performance computing Human-computer interaction for data systems Responsible AI development and deployment Publication analysis reveals strong focus on responsible data science, with recent work emphasizing differential privacy, COVID-19 data equity, urban mobility fairness, and relational data systems. Earlier foundational work established contributions to scientific workflow systems and data pricing models. Awards and Honors: Runner-up Best Paper Award (VLDB 2023) Best Paper Award (SIGMOD 2019) Best Paper Award (VIs 2019) Best Paper Award (InfoVis 2018) He leads the Urbanalytics Lab and advises multiple students including An Yan (fairness in urban mobility), Sean Yang (machine learning embeddings), and Dominik Moritz (visualization systems). His projects span EZLearn for automatic claim validation, privacy-preserving synthetic data, and Myria middleware for polystores.

Santiago OntañónView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Game AI
• +10 more

Santiago Ontañón is an Associate Professor in the Department of Computer Science at Drexel University's College of Computing and Informatics. He is also a Senior Research Scientist at Google DeepMind, reflecting a strong dual affiliation in both academic and industrial AI research. His work bridges theoretical AI with practical applications in gaming and machine learning. PhD in Computer Science (Artificial Intelligence), cum laude, Autonomous University of Barcelona Postdoctoral Researcher, Georgia Institute of Technology Researcher, Artificial Intelligence Research Institute (IIIA), Barcelona, Spain Dr. Ontañón's research focuses on artificial intelligence, machine learning, and robotics, with a particular emphasis on game AI. His interests span case-based reasoning, reinforcement learning, Monte Carlo tree search, player modeling, and procedural content generation. He has made significant contributions to AI in real-time strategy games and explainable AI systems. His recent publications reflect a consistent trend in AI for games, hierarchical planning, and learning from demonstration. The articles span topics such as reproducible deep reinforcement learning, adaptive player modeling, and integrating domain knowledge into search algorithms, indicating a mature and impactful research trajectory in AI and game technologies. Senior Research Scientist, Google DeepMind Organizer, microRTS AI Competition Advising multiple PhD students in AI and game-related topics He has advised numerous PhD students, many of whom have completed their theses on advanced AI topics in games and reasoning. His research is supported by access to substantial computational resources and collaborative networks in both academia and industry. He actively promotes open science by releasing software, data, and teaching materials. He leads research efforts in AI for games and maintains an active lab focused on game AI, with projects like microRTS, FTL, and Darmok. His team develops systems for reinforcement learning, planning, and natural language understanding in game environments.

Marcella MenegaleView profile

Associate Professor

• Language Education
• Multilingualism
• Learner Autonomy
• +7 more

Marcella Menegale is an Associate Professor in the Department of Comparative Linguistic and Cultural Studies at Ca' Foscari University of Venice. She is affiliated with the Research Institute for Digital and Cultural Heritage. Her teaching responsibilities include courses on instructional design for language education, theories of language education, and multilingualism, across various degree programs such as Master’s in Languages and Civilizations, and Language Sciences. Her research focuses on multilingual education frameworks (CLIL, intercomprehension), learner autonomy, digital tools in language learning, and well-being in educational contexts. She has contributed to EU-funded projects like DigLit (combating social inequalities via digital tools) and EVAL-IC (evaluating intercomprehension skills). She has also served as an expert evaluator for the European Commission’s Horizon 2020 and ANVUR’s research evaluations. Key research areas include CLIL methodology, learner autonomy development, and the integration of technology in language pedagogy. She collaborates with international teams on projects like Transition from Secondary School CLIL to University EMI (funded by the British Council). Her work bridges theory and practice, addressing challenges in second-language teaching and digital-age curricula.

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +7 more

Maxime CORDY is a Research Scientist at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) , University of Luxembourg, within the Security, Design and Validation group (SerVal) . He holds a PhD from the University of Namur (Belgium, 2014) and specializes in software engineering, applied artificial intelligence, and cybersecurity. His work focuses on adversarial machine learning, deep learning robustness, and model checking for critical systems. Research interests include adversarial attacks on tabular data , energy system optimization , code understanding models , and software quality assurance . Recent projects address challenges in secure AI deployment, automated test generation, and fault detection in large language models. Publications emphasize empirical studies on adversarial defenses, data augmentation for code models, and energy consumption forecasting. He contributes to tools like Daedalux (variability-aware model checking) and benchmarks like Tabularbench for adversarial robustness evaluation. Current affiliations include leadership within the SerVal group and collaborations on interdisciplinary projects such as MALETSQUE (Machine Learning Techniques for Software Quality Evaluation). His work bridges theoretical computer science with practical applications in energy systems, medical imaging, and space program design.

Torsten SteinhoffView profile

Professor

• Writing Didactics
• Vocabulary Didactics
• Digital Communication in Education
• +7 more

Torsten Steinhoff is a Professor of Didactics of the German Language at the Department of Germanic Studies, University of Siegen, Faculty of Arts and Humanities. His research and teaching focus on theoretical, methodological, and empirical aspects of language acquisition and instruction from elementary to university levels. His primary research interests include: Writing didactics (Schreibdidaktik) Vocabulary didactics (Wortschatzdidaktik) Language-specific and disciplinary learning (Sprache im Fach) Digital communication and AI in education Development of complex learning arrangements (Lernarrangements) Steinhoff investigates how digital tools like ChatGPT can be integrated into writing instruction, promoting argumentative writing through structured learning tasks. His recent work (2023–2025) analyzes human-AI collaboration in writing, proposing models such as GPT as Ghost, Partner, or Tutor. He emphasizes a post-digital didactic approach, balancing traditional literacy with digital competencies. His publications reflect a strong trend in digital transformation of writing, multilingual education, and empirical interventions in secondary classrooms. He leads research projects funded by BMBF and MKW NRW, including the "AI Writing Arrangements" project tested in 8th-grade classes. Scientific contributions and collaborations: Co-editor of research handbooks on empirical writing didactics Collaborator with scholars like Nicole Marx, Katrin Lehnen, and Joachim Grabowski Active contributor to journals such as Didaktik Deutsch , BiSS-Journal , and Waxmann publications Hosts a research team at lernarrangements.de He advises on academic language development, text procedures, and vocabulary transfer across modalities and subjects. His lab develops open educational resources (OER) for digital writing and communication, contributing to platforms like Twillo.

Marcel MierwaldView profile

Researcher

• History Education
• Epistemological Beliefs
• Digital Media in Education
• +3 more

Dr. Marcel Mierwald is a researcher at the Department of History Didactics at Ruhr University Bochum, specializing in empirical studies of historical learning. He collaborates on the oral history project "People in Mining" and focuses on digital learning, epistemological beliefs, and language-sensitive history teaching. His work bridges theoretical frameworks with classroom practice. Education: Doctoral degree (2019) at Ruhr University Bochum; Master of Education in social studies and history (Free University of Berlin, 2012). Research Trends: His recent publications emphasize authenticity in learning materials, media comparison studies, and assessment tools for historical argumentation. Collaborations with Nicola Brauch and others highlight interdisciplinary approaches to history education. Scientific Awards: Doctoral scholarship from Professional School of Education (PSE) at Ruhr University Bochum (2013-2016). Teaching: Offers courses on subject didactics, practical semester preparation, and language-sensitive history teaching. Led seminars on migration history, the Weimar Republic, and National Socialism in school labs. Labs & Teams: Active in the Alfried Krupp Student Laboratory and Ruhr University Bochum's student laboratory for humanities, focusing on empirical history education research and innovative teaching methods.

• 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.

Jakub SzymanikView profile

Associate Professor

• Cognitive Science
• Computational Linguistics
• Theoretical Computer Science
• +5 more

Dr. Jakub Szymanik is an Associate Professor affiliated with the Center for Brain/Mind Sciences and the Computer Science Department at the University of Trento . His research bridges computational modeling, formal logic, and cognitive neuroscience to investigate the relationship between linguistic structures and cognitive processes. Research Focus : Semantic universals, quantifiers, Boolean concepts, and decision-making strategies. Methodology : Combines neural networks, logical complexity analysis, and neurobehavioral experiments. Recent Publications (2020-2023) : Explores quantifier emergence, semantic representation optimization, and computational models of cognitive trade-offs, published in Cognition , Cognitive Science , and Open Mind . Scientific Recognition : ERC Starting Grant: Cognitive Semantics and Quantities NCN Hybrid Reasoning Models NWO VENI Grant: What makes social interactions hard? Research Collaborations : Mentored former group members now at institutions including the University of Washington, Tel Aviv University, and Polish Academy of Sciences.

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.

Randy HarrisView profile

Professor

• Rhetoric
• Computational Rhetoric
• Cognitive Linguistics
• +8 more

Randy Harris is a Professor in the Department of English Language and Literature at the University of Waterloo, with a cross-appointment to the David Cheriton School of Computer Science. His career spans over three decades, focusing on the intersection of rhetoric , cognitive science , and computational linguistics . He holds a PhD in Communication and Rhetoric from Rensselaer Polytechnic Institute, with postdoctoral experience at the University of Alberta. Education : PhD (Rensselaer), MSc (Rensselaer, Alberta), MA (Dalhousie), BA (Queen's) Research Interests : Cognitive Rhetoric, Computational Rhetoric, Rhetorical Figures, Construction Grammar, Rhetoric of Science, and Neurocognitive Stylistics. His work explores how rhetorical figures like chiasmus and antimetabole reflect brain structure and cognitive processing. Recent projects involve building the Rhetoricon , a collocational database of rhetorical figures, and investigating their role in large language models . He has received numerous awards, including the University of Waterloo Arts Award for Excellence in Research (2023) and Fellow of the Royal Society of Canada (2022) . Harris has supervised graduate students in professional communication , linguistics , and science writing . His grants include NSERC Discovery Horizon (2024-2029) and multiple SSHRC grants for Computational Rhetoric and Rhetorical Figure Ontology . He actively organizes interdisciplinary workshops like Computing Figures and contributes to media discussions on language, AI, and rhetoric.

• Software Engineering
• Programming Languages
• Systems
• +4 more

Manuel Rigger is an Assistant Professor at the National University of Singapore (NUS), leading the TEST Lab (Trustworthy Engineering of Software Technologies) within the PL/SE group at the School of Computing. His research focuses on improving the reliability of data-centric systems through automated testing frameworks and formal methods. Education : PhD from Johannes Kepler University Linz (supervised by Hanspeter Mössenböck), postdoctoral work at ETH Zurich (Advanced Software Technologies Lab under Zhendong Su). Research Interests : Automated testing of database systems Programming language design and verification Incremental build systems Formal methods for software reliability Key Contributions : Developed tools like SQLancer (for finding bugs in databases) and CERT (performance issue detection). His work has uncovered over 800 bugs in real-world systems. Awards : Recipient of the ERC Consolidator Grant (2025) for groundbreaking research in software security and testing. Service Roles : Organizer of ICFP/SPLASH 2025 Outdoor Activities, committee member for OOPSLA Review, PLDI Artifact Evaluation, and ICSE Program Committee. Also actively involved in organizing workshops (e.g., Fuzzing & Software Security Summer School 2025).

Per-Arne AndersenView profile

Associate Professor

• Artificial Intelligence
• Reinforcement Learning
• Tsetlin Machines
• +7 more

Per-Arne Andersen is an Associate Professor at the Department of Information and Communication Technology within the University of Agder . His research focuses on artificial intelligence , reinforcement learning , Tsetlin machines , and deep learning , with applications in real-time strategy games , industrial environments , and IoT systems . Projects: RESTORE Research Groups: CAIR - Center for Artificial Intelligence Research, CIEM - Center for Integrated Crisis Management, Intelligent Mechatronics (iTron) His work explores safe and sustainable reinforcement learning , interpretable AI , and generative environment modeling . He has developed frameworks like CaiRL and CostNet for high-performance RL environments and goal-directed learning. Recent publications include advancements in Tsetlin automaton analysis , GNSS jamming classification , and road quality detection . Articles from 2025-2016 span machine learning , computer vision , and environmental modeling . He contributes to IEEE , Springer , and LNCS publications, with a focus on interdisciplinary AI applications in crisis management , cybersecurity , and industrial optimization .