Find Academic Supervisors

Aravind RajeswaranView profile

Researcher

• Reinforcement Learning
• Representation Learning
• World Models
• +5 more

Aravind Rajeswaran is a Research Scientist at Meta AI (FAIR) and Visiting PostDoc/Collaborator at Berkeley AI Research Lab (BAIR) at UC Berkeley's College of Engineering, Department of Electrical Engineering and Computer Sciences. He completed his PhD in Computer Science at the University of Washington under Profs. Sham Kakade and Emo Todorov, with additional collaborations with Sergey Levine and Chelsea Finn, and previously earned his bachelor's degree with the best undergraduate thesis award from IIT Madras working with Balaraman Ravindran. His research focuses on building generalist AI agents that operate in open worlds, combining reinforcement learning, representation learning, and world models. Key projects include Locate 3D for real-world object localization, OpenEQA for embodied question answering with foundation models, VC-1 as an artificial visual cortex for embodied intelligence, and R3M as a universal visual representation for robot manipulation. His work demonstrates how pre-trained visual representations can significantly enhance robotic capabilities with minimal supervision. Rajeswaran's publication record shows consistent high-impact contributions across premier AI conferences including NeurIPS, ICML, CVPR, and RSS from 2018 through 2025, with research spanning reinforcement learning, representation learning, robotics, and computer vision. His work on Decision Transformer demonstrated how sequence modeling frameworks can effectively train reinforcement learning policies. Best Paper Award, Scaling Robot Learning Workshop at ICRA 2022 best undergraduate thesis award from IIT Madras As an educator and mentor, Rajeswaran has guided numerous PhD students who have gone on to positions at Stanford, MIT, CMU, Berkeley, and top AI companies including Meta, DeepMind, and Anthropic. He designed and co-taught the Deep Reinforcement Learning course (CSE599G) at UW in 2018, with materials adopted by courses at MIT and CMU, and served as lead TA for Machine Learning for Big Data (CSE547). His research has been supported through his role as Principal Investigator for the Cortex Team at FAIR.

• Crisis Communications
• Sustainability Literacy
• Hospitality Management
• +3 more

Dr. Laura Zizka is a Professor at the EHL Hospitality Business School, part of the HES-SO university network. She specializes in higher education strategies, crisis communication, and sustainability in hospitality and STEM sectors. Her research bridges academic theory with industry practice, focusing on organizational resilience during crises, digital education transformation post-pandemic, and embedding sustainability literacy in curricula. Education**: BSc HES-SO in Hospitality and Tourism Management Research Themes**: Crisis communication strategies in tourism and hospitality Digital transformation in higher education Pro-environmental behavior in hospitality operations Sustainability integration in STEM and business programs Her work emphasizes bridging educational practices with real-world challenges, such as pandemic communication, stakeholder engagement in sustainability, and employability skills for STEM graduates. Recent studies include analyzing Swiss hoteliers' pandemic communication evolution and exploring AI's role in academic writing through Microsoft Copilot case studies. Grants & Projects**: HES-SO Rectorate-funded project (2019–2020) on destination image and pictorial content impact (CHF 99,000) Longitudinal studies on student/faculty perceptions of digital education (2020–2023) Dr. Zizka collaborates with industry partners like KITRO (food waste tech) and actively contributes to conferences on topics ranging from trauma-informed pedagogy to blended learning models. She advocates for holistic sustainability education and has advised on CSR communication strategies for airlines and hospitality firms.

• Computational Linguistics
• Natural Language Processing
• Multilingual Models
• +7 more

Malvina Nissim is a leading researcher in computational linguistics and NLP at the University of Groningen's Department of Artificial Intelligence, with a focus on multilingual modeling, bias mitigation, and human evaluation frameworks. Key Contributions : Developed CALAMITA (Italian LLM benchmark), IT5 models for Italian language processing, and ReproHum framework for NLP evaluation reproducibility Research Pillars : Multilingual reasoning consistency, perspective-based text analysis, and figurative language modeling Her work spans activation steering techniques, cross-lingual transfer learning, and the creation of specialized language resources like the EurekaRebus dataset and MAGPIE idiom corpus. She pioneered methods for gender bias measurement in BERT and developed the SocioFillmore tool for perspective visualization. Recent publications explore model uncertainty as MCQ difficulty proxy, Italian headline generation benchmarks, and multilingual multi-figurative language detection. She actively participates in teaching initiatives like the "NLP with Bracelets" workshop for Italian high school students. Scientific Awards : ACL Best Paper Award (2025) EMNLP Outstanding Reviewer (2023) EVALITA Leadership Recognition (2024) She advises PhD students in model bias analysis and has contributed to the development of the Dutch Abusive Language Corpus (DALC) and the ReproNLP reproducibility framework. Her collaborations span institutions in Italy, Netherlands, and international NLP communities.

Patricia SpyerView profile

Professor

• Cultural Anthropology
• Southeast Asian Studies
• Visual Anthropology
• +6 more

Patricia Spyer is a Professor of Anthropology & Sociology at The Graduate Institute Geneva since 2016. She holds affiliate positions at the Albert Hirschman Centre on Democracy. Her expertise spans cultural anthropology of Indonesia, visual media studies, and material culture. She has held prestigious roles including Chair of Cultural Anthropology at Leiden University (2001–2015) and Global Distinguished Professor at NYU (2009–2012). Her research focuses on violence, visuality, religion, and urban-rural dynamics in Southeast Asia. Education: PhD in Anthropology from the University of Chicago. Earlier positions included Visiting Fellowships at ANU (2014), NYU Shanghai (2017), and Cambridge University (2020). Research interests include: Visual anthropology and media representations Conflict dynamics and post-war societies Religion-politics intersections Urban and rural sociocultural landscapes Her publications include Orphaned Landscapes: Violence, Visuality, and Appearance in Indonesia (2021), The Memory of Trade (2000), and co-edited volumes like Images That Move (2013) and Handbook of Material Culture (2013). Editorial roles: Vice-chair of the Prince Claus Fund, member of Wenner-Gren Foundation Advisory Council, and editorial boards for Annual Review of Anthropology and Positions: Asia Critique . Her work bridges academic research with public engagement through museum collaborations and policy advisory roles.

• Sociological Theory
• Media Theory
• Monetary Theory
• +4 more

Prof. Cornelia Bohn is a Professor of General Sociology at the University of Lucerne's Department of Sociology, within the Faculty of Humanities and Social Sciences. She holds a Ph.D. from the University of Bielefeld and a habilitation from the University of Trier. Her career includes roles as Associate and Assistant Professor at several institutions, and she has been a visiting scholar at Toyo University, Stanford, and the University of Chicago. Bohn's research focuses on sociological theory, media theory, monetary systems, and inclusion/exclusion dynamics. She co-edits the journal Soziale Systeme and collaborates with prestigious research networks like NCCR 'Iconic Criticism' and SFB 600 'Strangers and Poor People'. Her work bridges historical and contemporary social analysis, emphasizing visual and monetary systems. Key achievements include a fellowship at the Institute for Advanced Study (University of Constance), editorial leadership, and international research engagements. Her theoretical contributions address autonomy, societal structures, and cultural representation. Current research explores the intersection of art, documentation practices, and modern sociological frameworks.

Karen MullenersView profile

Associate Professor

• Fluid Dynamics
• Unsteady Flow Phenomena
• Bio-inspired Robotics
• +4 more

Karen Mulleners is an Associate Professor at the École polytechnique fédérale de Lausanne (EPFL), affiliated with the School of Engineering (STI), the Institute of Mechanical Engineering (IGM), and the UNFOLD Laboratory (Laboratoire de diagnostic des écoulements instationnaires). She also serves in the SGM-ENS teaching department and is a member of the EDEY-GE doctoral program commission. Her research focuses on experimental fluid dynamics, particularly unsteady flow phenomena and vortex dynamics. Professor Mulleners specializes in the intersection of fluid dynamics and bio-inspired engineering, with research interests including: Unsteady vortex-dominated flow phenomena Fluid-structure interaction in flexible systems Experimental methods for flow visualization and measurement Application of fluid dynamics principles to bio-inspired robotics Aerodynamic performance optimization of wind turbine systems Vortex dynamics in flapping and rotating wing systems Her recent publications (2022-2025) demonstrate a strong experimental focus on understanding complex fluid phenomena, particularly in bio-inspired robotics and renewable energy applications. Mulleners' work consistently addresses fundamental questions about vortex formation, flow control, and fluid-structure interactions, with significant contributions to understanding dynamic stall in wind turbines and undulatory swimming mechanics. Her research group employs advanced diagnostic techniques to study unsteady flows, often bridging engineering and biological principles. Professor Mulleners actively supervises PhD students and has directed multiple EPFL theses. Her teaching responsibilities include courses on Measurement Techniques and Aerodynamics, where she imparts knowledge on experimental methods for observing and measuring physical variables such as force, resistance, temperature, flow velocity, and structural deformation. The UNFOLD Laboratory, which Professor Mulleners leads, focuses on diagnostic techniques for unsteady flow phenomena, employing advanced experimental methods including flow visualization, particle image velocimetry, and force measurement systems to study complex fluid dynamics problems with applications in renewable energy and bio-inspired engineering.

Natalia Díaz RodríguezView profile

Assistant Professor

• Artificial Intelligence
• Deep Learning
• Reinforcement Learning
• +6 more

Natalia Díaz Rodríguez is an Assistant Professor of Artificial Intelligence at ENSTA ParisTech, where she works in the Computer Science and Systems Engineering department within the Autonomous Systems and Robotics Lab (U2IS). She is also affiliated with the INRIA Flowers team, focusing on developmental robotics. Her research spans deep learning, reinforcement learning, continual learning, and symbolic AI, with applications in explainable AI, computer vision, and robotics for social good. Her academic background includes a double PhD in Artificial Intelligence from Abo Akademi University and the University of Granada, alongside MSc degrees in Soft Computing and Computer Engineering from the University of Granada. She contributes to interdisciplinary AI, particularly in robotics, ethics, and healthcare applications, and co-organizes workshops on continual learning. Double PhD in Artificial Intelligence (2015), Abo Akademi University and University of Granada Doctoral diploma on Innovation and Entrepreneurship (2017), EIT Digital MSc in Soft Computing and Intelligent Systems (2012), University of Granada MSc in Computer Engineering (2010), University of Granada Her recent publications focus on trustworthy AI, including bias identification, counterfactual explanations, and continual learning strategies, reflecting her commitment to ethical and robust AI systems. She also explores AI applications in structural engineering, climate visualization, and financial risk assessment, emphasizing practical deployment and interpretability.

Desmond ElliottView profile

Associate Professor

• Vision-Language Models
• Multimodal Machine Learning
• Natural Language Processing
• +5 more

Desmond Elliott is an Associate Professor and Villum Young Investigator at the Department of Computer Science, University of Copenhagen. His research focuses on vision-language models, multilingual and multimodal processing, with particular emphasis on tokenization-free language modeling approaches. He leads a research group actively working on pixel language models and cross-lingual multimodal understanding. University of Copenhagen, Department of Computer Science Villum Young Investigator Associate Editor for JAIR (2025-2028) Senior Area Chair for ACL 2025 Elliott's research spans vision-language integration, multilingual NLP, and multimodal machine learning. His work explores how language models can operate directly on visual pixels without traditional tokenization, enabling more seamless integration of vision and language processing. He investigates compositional generalization in multimodal systems, retrieval-augmented image captioning, and cross-lingual transfer in vision-language tasks. His group develops methods for low-resource language processing and creates benchmarks for evaluating multimodal systems across diverse cultural contexts. His recent publications demonstrate strong trends in pixel-based language modeling, synthetic dataset generation through retrieval augmentation, and multilingual vision-language processing. The work spans theoretical advances in model architectures and practical applications in areas like medical text analysis, food culture understanding, and social media content moderation. His research often bridges computer vision and natural language processing with a focus on making these technologies accessible across diverse languages and cultures. Best Paper Honorable Mention at CVPR Visual Concepts Workshop 2025 Best Long Paper Award at EMNLP 2021 Area Chair Favourite paper at COLING 2018 Elliott actively supervises student projects in BSc and MSc programs related to his research interests. His research has received substantial funding from Google (2024-2025), Facebook (2022-2024), Villum Foundation (2021-2026), Novo Nordisk Foundation (2019-2024), and European Union (2023-2026). He regularly recruits postdocs for projects including the Danish Foundation Models project and the Responsible AI for the People Project. His group holds regular meetings on Tuesdays from 13:00-14:00 in IF G.03, with an active mailing list for announcements. The research environment appears collaborative, with frequent co-authorship across institutions and regular participation in major NLP and computer vision conferences.

Ulrik BrandesView profile

Professor

• Social Network Analysis
• Graph Theory
• Network Science
• +3 more

Ulrik Brandes serves as Full Professor and Head of the Department of Humanities, Social and Political Sciences at ETH Zurich, holding the Professorship for Social Networks. He actively teaches courses including Network Analysis and Applied Network Science: Sports Networks for Fall semester 2025, with office location at WEP J 14, Weinbergstr. 109, Zurich. His research spans Social Network Analysis, Graph Theory, and Network Science, with significant applications in sociology, sports analytics (particularly soccer and Australian Football League), and archaeological networks. As a longstanding member of the International Network for Social Network Analysis (since 2001) and the Academy of Sociology (since 2017), he bridges theoretical graph algorithms with practical interdisciplinary applications, recently expanding into sports analytics through the Football Scouting Association (2023). Analysis of his recent publications reveals strong thematic continuity in network centrality, temporal dynamics, and robustness, with increasing application diversity across sports analytics, archaeological trade networks, and decentralized social media platforms. His work consistently emphasizes efficient computational methods for real-world network problems. Honors: Simmel Award (2024) Prof. Brandes maintains active research leadership through departmental oversight and course development, though specific grant details and student advisement records are not publicly documented in available sources. His departmental role indicates substantial administrative responsibilities alongside research and teaching commitments.

Emily CrossView profile

Professor

• Cognitive Neuroscience
• Social Neuroscience
• Embodied Cognition
• +5 more

Emily Cross is a Full Professor at the Department of Humanities, Social and Political Sciences at ETH Zurich, leading the Social Brain Sciences Professorship since spring 2023. She previously held professorships at Bangor University (Wales), University of Glasgow (Scotland), Macquarie University (Australia), and Western Sydney University's MARCS Institute (Australia). Her research centers on how embodied experience shapes social learning and perception across diverse contexts. Key contributions include identifying neural signatures of embodied expertise using dancers, developing embodied neuroaesthetics theory, uncovering neurocognitive foundations of visual learning across lifespans, and pioneering paradigms for human-robot social engagement. Her interdisciplinary approach bridges technology, performing/visual arts, and social sciences to explore experience-dependent plasticity at brain and behavioral levels. Recent publications (2024-2025) demonstrate intense focus on human-robot interaction dynamics, aesthetic movement perception, and context-dependent social cognition. Work increasingly examines self-disclosure mechanisms to robots, cultural influences on robot acceptance, and neural correlates of movement synchrony, reflecting her expanding influence at the neuroscience-robotics intersection. Scientific awards include: Philip Leverhulme Prize for Psychology Jacob Bronowski Award from British Science Foundation Young Talent Award from Dutch Neuroscience Society RoboHub and Insight Analytics top women in robotics listings Australia’s Superstars of STEM (2022) Cross passionately trains next-generation scientists with emphasis on research ethics. Her work attracts major funding from ERC, NIH, Fulbright Commission, ESRC, EPSRC, and UK Ministry of Defence. She serves on UNESCO’s International Bioethics Committee (co-rapporteur for neurotechnology ethics report) and as Associate Editor for International Journal of Social Robotics. She leads ETH Zurich's dynamic Social Brain Sciences group, which embraces interdisciplinarity through research paradigms bridging technology, performing/visual arts, and biological/social sciences, while maintaining active roles in editorial boards and conference committees including Intelligent Virtual Agents and Affective Computing meetings.

Valentina BoevaView profile

Assistant Professor

• Machine Learning
• Bioinformatics
• Genomics
• +3 more

Prof. Valentina Boeva is an Assistant Professor at the Department of Computer Science, ETH Zürich, specializing in biomedical informatics. Her research focuses on integrating machine learning and computational methods to address challenges in genomics, oncology, and precision medicine. She holds a position in the Professur für Biomedizininformatik (Biomedical Informatics) and is based at CAB G32.2, Universitätstrasse 6, Zürich, Switzerland. Her work emphasizes applications such as cancer biomarker discovery, tumor heterogeneity analysis, and epigenetic profiling. She teaches courses including Machine Learning Seminar, Data Science Lab, and Machine Learning for Genomics. Her research group develops computational tools like CDState and UniversalEPI to decode complex biological systems. She actively publishes in top-tier journals, with recent work on exosome-driven diagnostics and chromatin interaction modeling. Her scientific contributions span methodologies for single-cell data analysis, survival modeling, and drug response prediction. She collaborates across disciplines to bridge computational science with clinical applications in cancer research.

Lisa BeinbornView profile

Professor

• Natural Language Processing (NLP)
• Multilingual Language Models
• Cognitive Plausibility in NLP
• +5 more

Lisa Beinborn is a Professor for Human-Centered Data Science at the University of Göttingen, leading the Human-Centered Data Science group. Her research bridges natural language processing with cognitive science, focusing on multilingual models and interpretability. PhD in Computer Science (2016), Technische Universität Darmstadt MSc in Computational Linguistics (2010), Saarland University & Bolzano, Italy BSc in Computational Linguistics (2008), Saarland University & Barcelona, Spain Her research explores cognitive plausibility in NLP, analyzing how language models process language differently from humans. Key areas include multilingual model interpretability, semantic drift, eye-tracking, and readability prediction. Recent work examines input representation stability in neural models, cross-lingual transfer of complexity, and aligning language models with human cognitive patterns. Her team has presented findings at EMNLP, CoNLL, ACL, and CoLING. VENI Grant for "Interpretability of Transfer in Multilingual Models" Early Career Partnership by Royal Dutch Academy of Science "Most Interesting Paper" Award at BabyLM Challenge "Best Project Award" by Network Institute She has taught courses like Language as Data and Advanced NLP at University of Göttingen, VU Amsterdam, and TU Darmstadt. Her group collaborates with institutions like Gemeente Amsterdam and NT2 on multilingual text simplification and learner correction.

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.

Matthias StürmerView profile

Professor

• Digital Sustainability
• Artificial Intelligence
• Natural Language Processing (NLP)
• +4 more

Matthias Stürmer is a Professor at Bern University of Applied Sciences (BFH) and Head of the Institute for Public Sector Transformation (90%) while also serving as Head of the Digital Sustainability Research Center at the University of Bern's Institute of Computer Science (10%). His roles include teaching, research, and consulting on digitalization topics such as digital sustainability, open source software, AI, NLP, open data, and public procurement. He earned a Dr. sc. ETH Zurich in 2009 and habilitation in 2020. His career includes senior roles at EY and Liip AG, and he holds leadership positions in organizations like CH Open and the Parliamentary Group for Digital Sustainability. **Education**: PhD (ETH Zurich, 2009), Licentiate in Business Administration (University of Bern, 2005). Studies included computer science and business administration, with an Erasmus semester at the University of Oviedo (Spain). **Research Interests**: Focus on digital sustainability, digital sovereignty, AI ethics, open source governance, smart cities, and public procurement strategies. His work bridges technical innovation with public sector challenges, emphasizing long-term societal benefits over short-term vendor dependencies. **Publications**: Over 38 peer-reviewed articles and book chapters, including foundational work on digital sustainability frameworks, open government data impact analysis, and collaborative innovation models. Recent focus areas include data colonialism risks and sustainable environmental data management. **Awards**: While no explicit awards listed, his leadership roles and prolific publications highlight recognition in academic and policy circles. **Advising & Grants**: Advises on public sector digitalization policies, contributes to Swiss federal IT strategies, and leads research projects funded by organizations like the University of Bern. Active in shaping Open Source adoption policies for public institutions. **Labs/Teams**: Directs the Research Center for Digital Sustainability at the University of Bern, collaborating with industry and government partners on projects like the Open Data Impact Framework and Open Finance initiatives.

• 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.