Find Academic Supervisors

• Museology
• Art Education
• Museum Education
• +4 more

Claire Robins serves as Professor of Museology and Art at University College London's Institute of Education, leading the Art, Design & Museology Academic Group and acting as Department Graduate Tutor for the Department of Culture, Communication and Media. Her work critically bridges art practice, museum studies, and educational theory to advance democratic engagement in cultural institutions. Education: PhD in Museum Education, University of London (2009) Master's degree in Gallery/Museum Education, University of London Bachelor's degree in Fine Art, St Martins School of Art (now University of the Arts London) Research Focus: Robins investigates the intersection of artists' practices with critical pedagogy, emphasizing progressive education and avant-gardist strategies in twentieth-century knowledge production. Her scholarship examines how contextual forces shape learning definitions in museums, with particular attention to materialities, pedagogic forms, and democratic potential within institutional frameworks. This work consistently challenges conventional museum narratives through artist-led interventions. Publication Trends: Her 15 most recent publications (2012-2025) reveal sustained exploration of museology-art education synergies, highlighting pedagogic innovation through artists' interventions, critical assessment frameworks, and democratic museum practices. Key thematic threads include narrative disruption in galleries, sustainability in art education assessment, and the transformative role of fiction in reimagining museum epistemologies. Advising & Leadership: Robins has supervised PhD/EdD students since 2010 and directed the MA Art Education, Culture and Practice program (2011-2023). She currently teaches MA modules in Museums and Galleries in Education and leads the Education and Curation component, while mentoring MA dissertations. Her leadership extends to developing gallery-based short courses with Engage. Professional Engagement: As editorial board member for Arts & Communication and Engage , and active participant in ICOM and NSEAD, Robins shapes global discourse through international keynotes (e.g., Korean Society for Education in the Arts, 2019) and curated seminars like Soft Subjects: Material Practice in Gallery Education (2024). Her review work for Routledge and Intellect Books further demonstrates scholarly stewardship.

Helma WennemersView profile

Professor

• Organic Chemistry
• Chemical Biology
• Peptide Chemistry
• +5 more

Prof. Dr. Helma Wennemers serves as a Full Professor at ETH Zurich's Department of Chemistry and Applied Biosciences, leading the Laboratory for Organic Chemistry. Her research group operates from HCI H 313 at Vladimir Prelog Way 1-5/10 in Zurich, Switzerland, with active teaching responsibilities including Organic Chemistry I and Chemical Biology - Peptides for the Fall 2025 semester. Her research program centers on the intersection of organic chemistry and chemical biology , with particular emphasis on collagen triple helix engineering , peptide-catalyzed asymmetric synthesis , and development of chemical tools for tissue remodeling diagnostics . Key focus areas include designing hyperstable collagen heterotrimers for fibrosis monitoring, creating fluorophore-based probes for collagen cross-linking visualization, and pioneering organocatalytic methodologies for complex heterocycle synthesis. Her group actively explores how hydrophobic modifications and proline derivatives influence collagen stability and cellular uptake mechanisms. Analysis of her 15 most recent publications (2024-2025) reveals three dominant research trajectories: (1) collagen structural engineering for biomedical applications, (2) innovative peptide/organocatalysis enabling stereoselective transformations, and (3) chemical probe development targeting tissue remodeling processes. These works consistently integrate synthetic chemistry with biological validation, demonstrating translational potential in fibrosis diagnostics and regenerative medicine. While specific grant details aren't provided in available sources, her research program clearly supports advanced laboratory infrastructure including peptide synthesis facilities and photochemical reaction systems like the ETHos photoreactor. Her group maintains strong industry and clinical collaborations evident in applications targeting liver cancer cells and prostate cancer diagnostics. The Laboratory for Organic Chemistry functions as an interdisciplinary hub where synthetic organic chemists collaborate with biologists to develop collagen-based diagnostic platforms and catalytic systems. Current projects focus on lysyl oxidase-responsive probes for real-time tissue monitoring and engineered peptide catalysts for sustainable chemical synthesis under environmentally relevant conditions.

• Molecular Imaging
• Biomedical Imaging
• Optical Coherence Tomography
• +3 more

Adam de la Zerda is an Associate Professor at Stanford University's Department of Structural Biology (School of Medicine) and Electrical Engineering (by courtesy). He develops advanced optical molecular imaging technologies combining nanoparticle contrast agents and adaptive OCT systems for cancer and ophthalmic disease research. Technion-Israel Institute of Technology (BSc, 2005) Stanford University (PhD, 2011) UC Berkeley (Postdoctoral Fellowship) Research Themes : Virtual biopsy using machine learning-enhanced OCT Gold nanorod-based molecular contrast agents Speckle noise reduction for cellular resolution Needle beam optical coherence tomography angiography His 15 most recent publications demonstrate technical innovations in: Metasurface optics for extended depth-of-field Spectral deconvolution of multiple contrast agents Speckle modulation for improved diagnostic clarity Noninvasive lymphatic system mapping Scientific Honors : Pew-Stewart Scholar for Cancer Research AFOSR Young Investigator NIH Early Independence Award Forbes 30 Under 30 (x2) Chan Zuckerberg BioHub Investigator His lab team has developed clinical prototypes including OcuBell Inc. 's ophthalmic imaging systems and Visby Medical 's diagnostic platforms. Current research spans from in vivo glycoprotein imaging to de novo biosensor development for real-time disease monitoring in awake animal models.

• Multimodal Learning
• Multilingual NLP
• Vision-Language Models
• +4 more

Desmond Elliott is an Associate Professor in the Natural Language Processing section at the Department of Computer Science, University of Copenhagen (UCPH). His research focuses on multimodal and multilingual models with specific emphasis on vision-language integration and tokenization-free NLP approaches. He teaches Bachelor and Master's level courses including Advanced Topics in Natural Language Processing (since 2019), Grundlæggende Data Science (since 2023), and previously Data Science (2021-2023). His research interests center on building and understanding multimodal and multilingual models , particularly exploring vision and language interactions through billion-parameter systems. Current work investigates cultural representation disparities in vision-language models, parameter-efficient captioning, and multimodal distributional semantics across diverse domains including food culture and medical imaging. His methodology emphasizes real-world applicability in non-English contexts and ethical considerations in multimodal systems. Elliott's recent publications (2025) demonstrate leadership in multimodal NLP, with significant contributions to vision-language pretraining, multilingual evaluation frameworks, and clinical NLP applications. His work spans theoretical advancements in model architectures and practical implementations addressing challenges in low-resource languages and domain adaptation. Best Long Paper Award at EMNLP 2021 Best Poster Award at COLING 2019 As an active educator, Elliott contributes to courses on Fair and Transparent Machine Learning and previously taught Information Retrieval. His research collaborations span international institutions with particular focus on European and non-English language contexts, reflecting UCPH's recognition as Europe's #1 institution for HCI research over the past decade.

• Medical Imaging
• Molecular Imaging
• Neuroscience
• +3 more

Steven Meikle is a Professor of Medical Imaging Physics and Head of the Imaging Physics Laboratory at the Brain and Mind Centre, University of Sydney. He also serves as Deputy Director (Preclinical) of Sydney Imaging and Deputy Director of the National Imaging Facility's Sydney node. His expertise spans advanced imaging technologies, with a focus on PET/SPECT instrumentation and molecular imaging. He holds a B.App.Sc.(Hons) from the University of Technology Sydney and a PhD from the University of New South Wales. Research focuses include developing novel PET systems like Open-field PET (for freely moving rodents) and Total Body PET, which enhance imaging sensitivity and enable real-time behavioral studies alongside brain function analysis. Collaborations include Tsinghua University (China) and UC Davis (USA). He leads projects on motion correction, quantitative imaging, and AI-driven analysis. Key achievements include over 180 peer-reviewed publications, editorial roles in Physics in Medicine and Biology , and leadership in professional societies. Awards include IEEE Senior Membership and Australian Institute of Physics Fellowship. Current student projects explore Total Body PET applications, motion correction, and radiopharmaceutical evaluation. Teaching roles include medical physics courses in diagnostic radiography and medical physics programs. He advises on imaging ethics, facility implementation, and translational research bridging basic science and clinical applications.

Ji Hwan ParkView profile

Assistant Professor

• Data Visualization
• Digital Twins
• Human-AI Teaming
• +5 more

Ji Hwan Park is an Assistant Professor in the School of Interactive Games and Media at RIT's Golisano College of Computing and Information Sciences (GCCIS). He holds a PhD from Stony Brook University under Prof. Arie Kaufman. His research focuses on accessible data visualization, digital twins, human-AI collaboration, and VR/AR applications. Notable contributions include developing tools for ADHD-friendly visualizations and interactive protein motif identification. He has received funding from the Department of Defense for biomedical research and earned an Honorable Mention at CHI 2024. Current teaching includes courses on game design and advanced algorithms. Research activities span medical imaging analytics (e.g., CMed framework for crowd-sourced diagnostics), climate modeling through Bayesian deep learning, and creative visualization techniques like Graphoto. His work bridges technical innovation with human-centered design principles, particularly in healthcare and neurodivergent accessibility contexts.

Andrew LanView profile

Associate Professor

• Artificial Intelligence in Education
• Educational Data Mining
• Personalized Learning
• +5 more

Andrew Lan is an Associate Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst, where he also serves as the CS Undergraduate Program Director. He was granted tenure by the UMass Board of Trustees in June 2025 and is currently on leave through Spring 2026. His research focuses on developing human-in-the-loop machine learning methods to enable scalable, effective, and personalized learning experiences in education. Dr. Lan received his BS in Physics and Mathematics from the Hong Kong University of Science and Technology, followed by his MS (2014) and PhD (2016) in Electrical and Computer Engineering from Rice University. He completed postdoctoral research at Rice University (2016) and Princeton University's EDGE Lab (2017-2018). His research spans artificial intelligence for education, with particular expertise in educational data mining, knowledge tracing, personalized learning systems, and human-AI collaboration in educational contexts. Dr. Lan's work leverages massive and multimodal learner and content data collected from both traditional classrooms and online learning platforms to develop systems that deliver high-quality, affordable, and personalized learning experiences. He has made significant contributions to areas including computerized adaptive testing, math word problem generation, student affect detection, and automated grading systems. His recent work increasingly focuses on leveraging large language models for educational applications while maintaining rigorous scientific validation of these approaches. Best Student Paper Award at the 2024 AIED Conference (with Alexander Scarlatos) Best Paper Nominee at LAK 2021 Best Student Paper Award at IEEE Big Data 2020 NAEP Math Automated Scoring Challenge Grand Prize Winner Dr. Lan actively mentors graduate students and postdoctoral researchers, with several of his advisees receiving recognition for their work. He has secured substantial funding from the National Science Foundation, including a $90M grant for the SafeInsights project, a secure cyberinfrastructure for educational research. His research group collaborates with institutions including Worcester Polytechnic Institute, University of Pennsylvania, and Rice University. He teaches undergraduate and graduate courses including COMPSCI 240 (Reasoning under Uncertainty) and COMPSCI 590OP (Applied Numerical Optimization), with a focus on the practical application of theoretical concepts in machine learning and artificial intelligence. His educational philosophy emphasizes bridging the gap between theoretical foundations and real-world implementation in educational technology.

Kerrin v. EngelhardtView profile

Senior Lecturer

• History of Education
• History of Science
• Educational Film Studies
• +3 more

Dr. Kerrin v. Engelhardt is an Associate Scientist at the Humboldt University Berlin's Department of History of Education within the Faculty of Humanities and Social Sciences. She also holds roles as Project Leader in the BMBF-funded collaborative project 'MythErz' and as a lecturer in science history at the Technical University of Berlin. Her research focuses on Cold War educational practices, historical pedagogical technologies, and the Abitur examination system in Germany. She has held positions including Research Assistant at the Humboldt University’s Institute of Education Studies and the Friedrich-Schiller University Jena, and led projects on educational film analysis and university collection utilization. Education: PhD in History of Natural Science from Friedrich-Schiller University Jena (2013), M.A. in Cultural History/Folklore Studies (2011), and Diploma in Fine Art from Bauhaus University Weimar (2003). Her work integrates interdisciplinary approaches to explore the intersection of education, science, and cultural history. Research Interests: Cold War pedagogical media, history of educational assessment practices, cultural history of science education, and institutional practices in historical education systems. She emphasizes praxeological methods to analyze historical educational materials and rituals. Key Projects: Leadership in the 'MythErz' project examining GDR educational myths through films; co-coordination of the 'Abitur examination practices' project; development of interdisciplinary teaching strategies using university collections. Publications: Over 20 peer-reviewed articles and book chapters on topics such as East German educational spaces, historical examination rituals, and Weimar-era art education. Notable works include analyses of GDR science education films and the socio-cultural dimensions of Abitur practices.

• Data Mining
• Machine Learning
• Clustering Algorithms
• +6 more

Claudia Plant is a Professor in the Faculty of Computer Science , leading the Research Group Data Mining and Machine Learning . Her research focuses on clustering algorithms, data mining, and machine learning applications in areas like biomedical data, wind energy, and causality inference. She has contributed to projects such as Knowledge-infused Deep Learning for Natural Language Processing (2020–2028) and Hybrid Computational Sciences (2021–2021). Plant has authored over 160 publications, with recent work emphasizing deep learning, anomaly detection, and GPU-optimized algorithms. She actively engages in academic activities, including talks on clustering methods and interdisciplinary projects like Governing Algorithms: The Politics of Data and Decision-Making . Her research interests span clustering algorithms , graph neural networks , causality discovery , and ethical digital transformation . Notable projects include causal analysis of wind farm dynamics and AI-enhanced education tools. Plant’s work bridges computational methods with societal challenges, such as empowering marginalized communities through ethical technology adoption.

Jacob KrügerView profile

Assistant Professor

• Software Engineering
• Software Evolution
• Variant-Rich Systems
• +5 more

Jacob Krüger is an Assistant Professor at Eindhoven University of Technology , specializing in the development and evolution of variant-rich software systems. He holds a PhD from Otto-von-Guericke University Magdeburg (2021) and has held academic and research positions at institutions including Ruhr-University Bochum, Chalmers University of Technology, and the University of Toronto. His research focuses on the interplay between human cognition and software quality, particularly in complex systems requiring frequent adaptation. Education: PhD in Computer Science, Otto-von-Guericke University Magdeburg (2021) MSc Business Informatics, Otto-von-Guericke University Magdeburg (2016) Research Interests: Variant-Rich Systems Program Comprehension Software Product Lines Human Factors in Software Engineering Architecture Smells and Quality Assurance Articles Trends: Recent work emphasizes fork ecosystem visualization (VisFork tool), the impact of AI on scientific practices, and crisis-driven software development (e.g., Corona-Warn-App). Key themes include empirical studies, tool development, and industry collaboration. Awards: Best Dissertation Award (2022) Frank Anger Memorial Award (2019) Multiple conference best-paper and review awards Advising & Grants: Supervises 12+ PhD students across multiple institutions. Active in funding projects like INKleSS (German Research Foundation) and FOSD Meeting 2024 (NWO). Leads collaborations with ASML, Danfoss, and Axis AB. Labs/Teams: Member of the Software Engineering and Technology (SET) group at TU Eindhoven, focusing on industrial-strength software systems and cognitive aspects of development.

Mykola PechenizkiyView profile

Professor

• Data Science
• Machine Learning
• Predictive Analytics
• +5 more

Mykola Pechenizkiy is a Full Professor at the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e), holding the Data Mining Chair. He also serves as an Adjunct Professor in Data Mining for Industrial Applications at the University of Jyväskylä. His research focuses on predictive analytics, data mining, and responsible AI, addressing real-world challenges in industry, healthcare, and education. He leads the Customer Journey research program at the Data Science Center Eindhoven, emphasizing ethical and transparent analytics. Academically, he holds a PhD from the University of Jyväskylä (2005) and has held visiting researcher positions at institutions like Columbia University and NYU. He has co-authored over 300 peer-reviewed publications and serves on editorial boards and committees for leading conferences (e.g., AAAI, IJCAI). He is the President of the International Educational Data Mining Society (IEDMS). His research interests include concept drift adaptation, sparsity techniques in neural networks, and fairness-aware AI. He has led projects such as the TKI PPS KPN Smart Two initiative and collaborates with industries like ASML, Philips, and Rabobank. His work contributes to UN SDGs, particularly in sustainable development through AI-driven solutions. Awards: Best Demo Paper Award (IEEE ICDE 2023), Best Paper Awards (ALA 2022, LoG 2022), and SensorKDD 2009 recognition. Grants/Projects: Active projects include TKI PPS KPN Smart Two (2019–2025) and Smart One W&I TKI KPN Flagship (2018–2022). Labs/Teams: Affiliated with EAISI Health, SIKS Scientific Board, and the University of Waikato’s AI Institute.

Tara BoroushakiView profile

Assistant Professor

• Wireless Networking
• Cyber-Physical Systems
• Robotics
• +3 more

Tara Boroushaki is an incoming Assistant Professor in Electrical & Computer Engineering at Yale University. She completed her Ph.D. at MIT (expected May 2025), advised by Prof. Fadel Adib, with a focus on sensing and mobile technologies. Her research spans wireless networking, robotics, and human-computer interaction, emphasizing multi-modal sensing for environmental perception. Key achievements include the Microsoft Research PhD Fellowship (2022–2024) and the IEEE RFID '23 Best Paper Award. Her work on RF-based 'X-ray vision' has been featured in TEDxMIT and media outlets like the BBC and World Economic Forum. She co-founded Cartesian Systems, deploying sensing technologies in retail and supply chain. Research interests include non-line-of-sight perception, RFID localization, and robotic grasping. She has developed systems like FuseBot and RFusion, highlighted as transformative in MIT's '103 Ways to Make the World Better' initiative.

Matilde MarcolliView profile

Professor

• Noncommutative Geometry
• Mathematical Physics
• Number Theory
• +5 more

Matilde Marcolli is the Robert F. Christy Professor of Mathematics and Computing and Mathematical Sciences at the California Institute of Technology (Caltech). She holds joint appointments in the Division of Physics, Mathematics, and Astronomy (PMA) and the Division of Engineering and Applied Sciences (EAS). Her research spans noncommutative geometry, mathematical physics, number theory, and mathematical linguistics. She has been recognized with prestigious awards such as the Sofja Kovalevskaya Award (2001) and the Heinz Maier Leibnitz Prize (2001). Marcolli has advised numerous PhD students and contributed to over 300 publications. Her work bridges abstract mathematics with applications in cosmology, quantum field theory, and computational linguistics. Education : PhD in Mathematics, University of Chicago, 1997 M.Sc., University of Chicago, 1994 Laurea in Mathematics, University of Pavia, 1993 Research Interests : Marcolli’s research explores the intersection of geometry, number theory, and physics. Key areas include noncommutative geometry models of particle physics and cosmology, motives in quantum field theory, and algebraic models of generative linguistics. She applies advanced techniques such as Feynman integrals, spectral action principles, and Hopf algebras to interdisciplinary problems. Grants & Awards : NSF grants DMS-2104330, DMS-1707882, and others NSERC Discovery Grant RGPIN-2018-04937 FQXi grant FQXi-RFP-1804 Collaborations & Labs : Marcolli collaborates with institutions like the Perimeter Institute and Florida State University. She leads research groups on topics such as quantum statistical mechanics, holography, and neural information networks. Her work on syntax-semantics interfaces and quantum gravity models has been pivotal in interdisciplinary studies.

Fethiye Irmak DoganView profile

Researcher

• Human-Robot Interaction
• Machine Learning
• Deep Learning
• +4 more

Fethiye Irmak Dogan is a Postdoctoral Research Associate at the University of Cambridge's Department of Computer Science and Technology, working in the Affective Intelligence and Robotics Laboratory. She holds a Ph.D. in Computer Science from KTH Royal Institute of Technology (2023), an M.Sc. and B.Sc. in Computer Engineering from Middle East Technical University (METU). Her research focuses on human-robot interaction, continual learning, and socially appropriate robot behaviors leveraging explainability. She has conducted robotics research at KTH's Division of Robotics, Perception and Learning and collaborated internationally, including a visiting scholar stint at Georgia Institute of Technology. Education highlights include: B.Sc., Computer Engineering, METU (2015) M.Sc., Computer Engineering, METU (2018), with research at Kovan Robotics Lab Ph.D., Computer Science, KTH (2023), with visiting research at Georgia Tech Research interests emphasize deploying autonomous robots in human environments, resolving ambiguous user instructions through explainability, and enabling socially intelligent robot behaviors. Recent work explores continual learning for context adaptation, multimodal frameworks for human-robot collaboration, and vision-language models for wellbeing assessment in children. Key projects include BT-ACTION (modular instruction understanding), GRACE (LLM-driven socially appropriate actions), and STREAK (continual learning for household tasks). Her contributions span robotics, AI ethics, and human-centered design, with a focus on real-world applications in healthcare and education.

Jonathan CohenView profile

Professor

• Philosophy of Perception
• Philosophy of Language
• Cognitive Science
• +3 more

Jonathan Cohen is a Professor of Philosophy at the University of California, San Diego (UCSD), and serves as an Associate Dean in the School of Arts and Humanities. Previously, he held a Killam Postdoctoral Fellowship at the University of British Columbia (2000-2001). He earned his Ph.D. in Philosophy from Rutgers University (2000), and holds a M.A. (1995) and B.A. (1993) in Philosophy and Mathematics from the University of Chicago. His research primarily focuses on the philosophy of perception and language, with a special emphasis on their intersections with cognitive science. Key areas include relationalist theories of color properties, multimodal perception, and the semantics/pragmatics of context-sensitive expressions. Recent work explores perceptual interactions across modalities, synesthesia, and the role of extrasemantic expansion in communication. Cohen’s publications span over two decades, with recent trends emphasizing perceptual architecture, phenomenal contrasts, and interdisciplinary approaches to cognitive penetration. His work often bridges analytic philosophy with empirical findings in psychology and neuroscience. While no formal grants or awards are explicitly noted, his extensive bibliography reflects sustained engagement with foundational questions in philosophy of mind and language. No lab affiliations or student advisees are listed in the provided materials.