Find Academic Supervisors

Zheng ZhangView profile

Researcher

• Human-AI Interaction
• Human-Computer Interaction
• Machine Learning
• +3 more

Zheng Zhang is a Ph.D. candidate in the Department of Computer Science and Engineering at the University of Notre Dame, where he focuses on human-AI interaction. He also works as an Applied Scientist in Adobe's GenAI team, developing interactive AI systems for user experience enhancement. He has held internships at Apple, AWS AI, and Meta Reality Labs. Education: Ph.D. (in progress) at University of Notre Dame M.S. in Computer Science from University of Rochester and University of Minnesota B.Eng. in Software Engineering from Shaanxi Normal University His research explores the intersection of human-computer interaction (HCI) and machine learning (ML), emphasizing systems that provide adaptive, context-sensitive support for complex cognitive tasks. Key areas include collaborative tools for team ideation, incremental learning from user demonstrations, and multimodal context-aware interfaces. Recent publications demonstrate a focus on AI-augmented collaboration through large shared displays (LADICA), audio-visual annotation (PEANUT), and interactive qualitative coding (PaTAT). His work increasingly integrates generative AI with real-time human input, particularly for co-located teams and educational applications. He serves as a Program Committee member and reviewer for top HCI/ML conferences including CHI, UIST, IUI, and ACL. Teaching experience spans courses in human-AI systems, algorithms, and data structures.

• Natural Language Generation
• Human Evaluation of NLP Systems
• Data-to-Text Generation
• +6 more

Ehud Reiter is a Professor of Natural Language Generation at the University of Aberdeen's School of Natural and Computing Sciences, Department of Computing Science. With over three decades of research experience, he is recognized as one of the world's leading experts in Natural Language Generation (NLG), particularly in data-to-text systems, evaluation methodologies, and healthcare applications. Reiter's research primarily focuses on creating systems that generate accurate, useful, and understandable natural language from structured data. His work spans multiple domains including healthcare (medical note generation, patient-facing systems), sports reporting, and explainable AI. A significant portion of his recent research addresses the critical challenge of evaluating NLG systems, with particular emphasis on human evaluation methodologies, reproducibility of results, and factual accuracy in generated text. His work on Bayesian Networks and causal graph discovery represents his ongoing interest in knowledge representation and reasoning behind natural language explanations. His research has evolved from foundational work on reference generation and document planning to current projects addressing large language models, reproducibility crises in NLP evaluation, and human-AI collaboration frameworks. The SPHERE evaluation card framework he co-developed represents a systematic approach to evaluating human-AI interaction systems across five key dimensions. Reiter has been instrumental in organizing multiple shared tasks focused on reproducibility in NLG evaluations, demonstrating his commitment to improving research methodology in the field. His work on consultation checklists for medical note evaluation has introduced standardized protocols that increase objectivity in clinical text assessment. Through projects like BabyTalk (generating neonatal intensive care unit summaries) and DrivingBeacon (providing driving behavior feedback), Reiter has demonstrated the practical applications of NLG technology in critical domains. His research consistently bridges theoretical advances with real-world implementation challenges.

Rhodri Ivor LengView profile

Lecturer

• Sociology of Science
• Scientometrics
• Metascience
• +4 more

Rhodri Leng is a Lecturer in Science and Technology Studies at the University of Edinburgh's School of Social and Political Science, where he has been employed since January 2024. His academic journey includes a PhD and MSc(R) in Science and Technology Studies from Edinburgh, an MA in Political and Legal Theory from the University of York, and an MA in Politics from the University of Glasgow. Research Focus: Leng specializes in the sociology of scientific development, examining how scientific knowledge spreads, influences opinion, and evolves within communities. His mixed-method approach combines computational techniques like citation network analysis and text mining to study: Dynamics of scientific literature and citation practices Detection of citation bias and distortion Integration of computational methods in scientific reviews Research integrity and impact assessment His work spans biomedical, astrophysics, and policy domains. Publications: Leng's 13 most recent journal articles (2018-2024) demonstrate consistent focus on scientometrics, genomics, neuroscience, and policy studies. Key themes include citation network analysis (10 papers), scientific controversies (5 papers), and computational methods in humanities (8 papers), with increasing attention to metascience and research evaluation in recent years. Awards & Honors: ESRC Postdoctoral Fellowship (2020-2021) ESRC Advanced Quantitative Methods PhD Studentship (2016-2019) EUSA Teaching Award for 'Best Student Who Tutors' (2019) Supervision & Grants: He welcomes PhD/Master's students interested in science policy, field development, or evidence-use practices. Previously secured ESRC funding for projects on selective citation analysis. Developed online courses in systematic literature review and network analysis for biomedical/social sciences. Professional Background: Before academia, Leng worked in UK politics as parliamentary/policy officer. From 2021-2024, he conducted industry research at Baillie Gifford, focusing on sociotechnical transitions and scientific mapping for investment strategies.

Sylke FrahnertView profile

Researcher

• Ornithology
• Evolutionary Biology
• Biodiversity Research
• +5 more

Dr. Sylke Frahnert is a Researcher at the Museum of Natural History Berlin (Leibniz Institute for Evolution and Biodiversity Research), where she serves as Curator of the Ornithological Collection and Women's Representative. Her work spans ornithology, taxonomy, and historical collection studies, focusing on avian systematics, evolutionary morphology, and the legacy of colonial-era expeditions like Ernst Schäfer's Tibet missions. She employs advanced techniques such as 3D geometric morphometrics to analyze corvid skulls and bird footscale patterns. Research Interests: Evolutionary morphology of birds, type specimen documentation, historical context of colonial collections, and functional integration of avian species in urban ecosystems. Publications: Her publications (2004–2011) emphasize type specimen cataloging, taxonomic revisions, and the intersection of ornithology with cultural heritage. Notable works include analyses of the Oppenheim Collection, Nauru bird specimens, and 3D morphometric studies on corvid skulls. Team Involvement: She collaborates on projects like the digital catalog of German ornithological type specimens under GBIF and contributes to museum-wide initiatives such as the 'Class, Order, Art' anniversary volume.

Gary SchindelmanView profile

Professor

• Biochemistry
• Molecular Biology
• Genomics
• +7 more

Gary Schindelman is a Professor of Biochemistry at Occidental College and a biological curator for WormBase at Caltech. He earned his B.S. from the State University of New York at Binghamton and his Ph.D. from New York University. Appointed in 2005, he also serves as a Department Co-Chair in Biochemistry. Email: schindelman@oxy.edu Office: Bioscience 208A Office Hours: Tuesday 9:45 – 11:45 a.m., Wednesday 1:00 – 2:00 p.m., and by appointment (Zoom or in person) Dr. Schindelman's research focuses on Biochemistry, Molecular Biology, Genomics , and Computational Biology , particularly in C. elegans and Arabidopsis models. His work spans enzyme kinetics, RNA biology, cellulose microfibril orientation, and bioinformatics tools for nematode research. He has contributed to WormBase, a key resource for nematode genomics, and explored ventral nerve cord functions in C. elegans behavior. His publications highlight expertise in genomic databases , phenotype ontologies , and plant cell expansion mechanisms . He received the Donald R. Loftsgordon Memorial Award for Outstanding Teaching in 2015. Dr. Schindelman teaches courses including Molecular Biology (BIO 221) , Principles of Biochemistry (BIO 322) , and Biochemistry I (BIO 349) , covering DNA/RNA/protein structure, enzyme function, intermediary metabolism, and biochemical techniques.

Kinan Dak AlbabView profile

Assistant Professor

• Data Privacy
• Systems Security
• Secure Computation
• +7 more

Kinan Dak Albab is an Assistant Professor at the Faculty of Computing and Data Sciences (CDS) at Boston University, where he joined in summer 2024. His research spans systems, cryptography, and programming languages, focusing on building practical tools for data privacy and compliance-by-construction. He has developed influential systems such as Sesame, K9db, and DP-PIR, which have been published in top venues like SOSP, OSDI, and USENIX Security. PhD in Computer Science, Brown University MS in Computer Science, Boston University (2020) BS in Computer Science, American University of Beirut (2015) Kinan's research centers on data privacy , secure computation , and systems security . He designs tools that allow developers to build applications that are privacy-compliant by construction. His work leverages systems design, cryptographic protocols, and language-level enforcement to reduce developer burden while ensuring strong privacy guarantees. He is particularly interested in GDPR compliance, private information retrieval, and usability of secure systems. His publications span high-impact areas including end-to-end privacy enforcement (Sesame), database systems with built-in privacy (K9db), and efficient private information retrieval (DP-PIR). These works combine systems performance with strong theoretical foundations, enabling real-world deployment in domains like wage gap analysis and public policy. Presidential Award for Excellence in Teaching, Brown University (2025) Teaching Excellence Award, Boston University (2020) Vivli and Microsoft datatheon Outstanding Graduate Submission (2019) Hariri Institute Graduate Fellow (2017–2020) Mark Sawaya Excellence Award, AUB (2015) 1st Place, ACM Lebanese Collegiate Programming Contest (2015) Kinan has advised and collaborated on real-world secure computation deployments, including a project with the Boston Women's Workforce Council and the Greater Boston Chamber of Commerce to measure wage gaps across over 100 companies. His work contributed to the formation of the startup nthparty and has been cited in the White House’s National Strategy on Privacy-Preserving Data Sharing, the UN Handbook on Privacy-Preserving Computation, and the European Commission’s report on Technological Enablers for Privacy. He is the lead developer of the JIFF framework for secure multi-party computation on the web and has created tools like Carousels for resource estimation in secure programs. He leads the ETOS group and is affiliated with multiparty.org , an initiative focused on advancing privacy-preserving technologies through open-source tools and real-world applications.

• Computer Graphics
• Virtual Reality
• Cultural Heritage Visualization
• +7 more

Carlos Antonio Andújar Gran is a faculty member at the Faculty of Informatics of Barcelona (FIB), Universitat Politècnica de Catalunya (UPC), where he is affiliated with the Department of Computer Science. He actively contributes to the academic community through teaching and supervising numerous student projects, particularly in advanced computing domains. His research interests center on the application of computer graphics, virtual reality, and artificial intelligence to real-world problems. Key areas include the 3D visualization and virtual reconstruction of cultural heritage, physically accurate rendering, intelligent segmentation of images, and the use of machine learning and reinforcement learning in sports analytics, particularly for padel. His work bridges technical innovation with practical applications in cultural preservation and sports technology. The recent publications under his supervision reflect a strong trend in digital cultural heritage, with multiple projects focused on tools for virtual visits, reconstruction, lighting simulation, and web-based 3D visualization of heritage models. Another significant trend is the application of AI to padel, including ball and player tracking, virtual coaching, and training virtual agents using reinforcement learning. These projects demonstrate a consistent focus on computer vision, interactive systems, and data-driven modeling. Carlos Antonio Andújar Gran has supervised a substantial number of students, guiding both undergraduate and master's theses. While specific grant information is not available in the text, his sustained supervision across many years suggests active involvement in research projects. He plays a key role in mentoring the next generation of computer scientists at UPC. His work is closely tied to the Department of Computer Science at FIB, where he collaborates with other faculty members such as Imanol Muñoz Pandiella, Núria Pelechano Gómez, and Mohammadreza Javadiha on various student projects, indicating a collaborative research environment focused on graphics, AI, and VR applications.

Geoffrey BartonView profile

Professor

• Bioinformatics
• Computational Biology
• Protein Structure Prediction
• +4 more

Professor Geoffrey Barton is the Chair of Bioinformatics at the Computational Biology department within the School of Life Sciences at the University of Dundee . With a career spanning decades, he has been pivotal in advancing bioinformatics tools and methodologies for analyzing biological data, particularly in protein structure prediction and RNA sequencing. Core Research Interests : Protein structure and function prediction, computational methods for large biological datasets, small RNA analysis, and integration with wet-lab collaborations across plants, model organisms, and human disease. Awards : Fellow of the Royal Society of Edinburgh (2019) Fellow of the Royal Society of Biology (2011) Brian Cox Prize for Excellence in Public Engagement with Research (2023) Publications and Software : He leads the development of widely used tools like JPred (25,000+ predictions/month) and Jalview (55,000+ installations). His group's work spans proteomics, transcriptomics, and structural genomics, addressing questions in basic science and clinical applications. Media and Collaboration : Available for media commentary on bioinformatics and computational biology, he collaborates extensively with international institutions, including the University of Cambridge and Oxford.

• Computer-Supported Collaborative Learning
• Virtual Reality in Education
• Science Education
• +5 more

Rolf Steier serves as Professor at Oslo Metropolitan University within the Faculty of Education and International Studies, Department of Primary and Secondary Teacher Education, holding the position of Head of Studies for Area of Responsibility 5. His office is located at Pilestredet 52, 0167 Oslo (B534), with contact details including mobile +47 906 92 626, office +47 672 36 014, and email rolf.steier@oslomet.no. He actively contributes to the Digital Learning Arenas research group, focusing on technology-enhanced educational environments. Steier's research centers on computer-supported collaborative learning (CSCL) and virtual reality applications in education, with specific expertise in embodied cognition, science education, museum learning, and narrative structures in STEM. His work examines how learners co-construct knowledge through digital interactions, particularly investigating the role of physical embodiment in virtual environments and the integration of narrative techniques to facilitate engagement in informal learning contexts. Recent projects explore immersive VR experiences for collaborative meaning-making and the adaptation of interaction analysis methodologies for technology-mediated educational research. Analysis of Steier's 2021-2025 publications reveals a clear trajectory toward increasingly sophisticated integration of virtual reality in educational research, with growing emphasis on interdisciplinary applications in science education. Key thematic developments include the refinement of interaction analysis frameworks for digital contexts, the exploration of perspective-taking across blended realities, and the strategic use of narrative to enhance STEM engagement in informal settings. His work consistently bridges theoretical learning science with practical educational technology implementation. The Digital Learning Arenas research group serves as the primary platform for Steier's collaborative work, functioning as an interdisciplinary hub for developing and studying innovative digital learning solutions. This group facilitates partnerships across educational sectors to transform teaching practices through emerging technologies, with recent focus on VR-based collaborative learning environments and cross-contextual knowledge transfer.

• Genomics
• Non-coding RNA research
• Phenotype-genotype relationships
• +7 more

Professor Marcel Dinger is a prominent academic and researcher currently serving as Professor and Head of School for Biotechnology and Biomolecular Sciences at UNSW Sydney. With over 20 years of experience in genomics, he has established himself as a leading figure in both academic and entrepreneurial spheres within the field. He has published 153 papers with over 24,000 citations and maintains an h-index of 61 on Google Scholar. His leadership extends beyond academia as he serves as President of the Australasian Genomics Technologies Association (AGTA) and holds director positions at Pryzm Health and the National Centre for Indigenous Genomics (NCIG). Professor Dinger's research laboratory focuses on establishing new links between phenotype and genotype, particularly examining rare and complex diseases in relation to underexplored regions of the genome including pseudogenes, repetitive elements, non-canonical DNA structures, and noncoding RNAs. His work harnesses population-scale genomic datasets and sophisticated data science methods to bring an objective perspective to understanding how the genome stores information and how it is transacted in biology. His research interests span genomics, non-coding RNA biology, clinical applications of genomic medicine, and the development of computational approaches for analyzing complex genomic data. Analysis of Professor Dinger's recent publications reveals a strong emphasis on non-coding RNA research, particularly long noncoding RNAs and their roles in disease mechanisms. His work spans cancer genomics, neurological disorders, and fundamental genomic mechanisms including DNA secondary structures like i-motifs and G-quadruplexes. His research combines experimental approaches with advanced bioinformatics to address fundamental questions in genomic medicine and has significant translational implications for disease diagnosis and treatment. Highly Cited Researcher in Cross-Field category (2019, 2020, 2021) Fellow of the Faculty of Science (Research), Royal Society of Pathologists of Australasia (2016) NHMRC Career Development Award (2010) Queensland Government Smart Futures Fellowship (2009) Foundation of Research, Science and Technology New Zealand Postdoctoral Fellowship (2005) Professor Dinger has been instrumental in establishing and leading several significant research initiatives including Genome.One, one of the first companies globally to provide clinical whole genome sequencing services, and the Kinghorn Centre for Clinical Genomics at the Garvan Institute of Medical Research. His entrepreneurial experience includes founding four biotechnology and IT startups. He serves on multiple governance boards including the National Centre for Indigenous Genomics, focusing on using genomics to improve health outcomes for Australia's First Peoples. His laboratory at UNSW continues to advance our understanding of genomic regulation and its implications for human health and disease.

Laura LUPOView profile

Research Fellow

• 19th-century Italian Literature
• Verismo Movement
• Digital Philology
• +6 more

Laura Lupo is a Research Fellow (SSD L-FIL-LET/10) at the Department of Humanities, University of Catania, working on XML/TEI-based annotated digital editions of 19th-century Italian literature within the EU-funded Extended Partnership Changes – Spoke 3 project (PE0000020, CUP E63C22001960006). Concurrently, she has held a permanent high school teaching position in literary subjects and Latin (Competition Class A011) since 2022, following her success in the national Ordinary Competition for teaching staff. Education: PhD in Interpretation Sciences (2023, University of Catania, cum laude), Master's in ITALS (2018, Ca' Foscari), Specialization in Special Education (2022, Kore University of Enna), and advanced degrees in Modern Philology (2016, LM-14) and Modern Literature (2015, University of Catania). Her research focuses on Verismo, particularly Giovanni Verga's short stories, with a specialization in digital philology, gender studies, and Sicilian cultural context. She has contributed to projects like the TEI-encoded Mastro-don Gesualdo edition and collaborated with the Verga Foundation (2017-2019) on archival cataloging and 19th-century text digitization. Scientific contributions include publications in journals like Annali della Fondazione Verga (Class A) and proceedings for international conferences such as the MOD Society's Literature & Anthropology (2019) and ADI's Literature & Power (2021). She has presented at venues including the University of Debrecen's North/South Italy literary dynamics seminar (2020) and organized events like the National ADI Congress (2021) and Verga-themed Literacy Day (2022). Her methodological approach bridges formal stylistic analysis with contemporary sociological and gender perspectives, examining brief narrative forms in dialogue with European literary traditions. Current work includes digital editions of Verga's texts and studies on post-unification Italian women's roles in media and literature.

• Schema discovery for Semantic Web data
• Data mining
• Recommendation systems
• +5 more

Kenza Kellou-Menouer is a researcher affiliated with the ETIS Laboratory at ENSEA, France, and part of the MIDI research group . Her work focuses on schema discovery for Semantic Web data, data mining, and big data optimization. Research: Semantic schema discovery, clustering/classification algorithms, and association rules. Teaching: Semantic Web technologies, database design, algorithms, and programming languages (Java, C++, C#, C). Research Interests center on Semantic Web data integration, RDF schema inference, and hybrid machine learning approaches. She has contributed to scalable schema discovery systems and real-time profiling techniques for large datasets. Publications include work on schema inference tools (SchemaDecrypt++, HInT) and methodological frameworks presented at top-tier venues like VLDB (A*), ICDE (A*), SSDBM (A), and ISWC . Her research bridges theoretical advancements with practical implementations for RDF datasets. Community Contributions include organizing tutorials at the International Semantic Web Conference (ISWC) 2022 and developing educational materials for database and programming courses.

Alessandro Lameiras KoerichView profile

Professor

• Machine Learning
• Computer Vision
• Pattern Recognition
• +6 more

Alessandro Lameiras Koerich is a Professor in the Department of Software Engineering and IT at École de technologie supérieure (ÉTS), part of the Université du Québec network in Montreal, Canada. He is affiliated with the LIVIA (Imaging, Vision and Artificial Intelligence Laboratory), where he conducts research in machine learning, computer vision, and pattern recognition. His work focuses on developing AI solutions for real-world applications in healthcare, security, and multimedia analysis. His research interests span multiple domains of artificial intelligence, with particular emphasis on multimodal machine learning, affective computing, and trusted machine learning systems. Dr. Koerich's work explores how AI can interpret human emotions through facial expressions and audio analysis, develop robust models resistant to adversarial attacks, and create efficient learning systems that can adapt to changing data streams. His research bridges theoretical advances with practical applications in healthcare monitoring, security systems, and multimedia content analysis. Analysis of his recent publications reveals a strong focus on multimodal emotion recognition, with increasing emphasis on transformer architectures, knowledge distillation techniques, and addressing challenges in real-world settings (in-the-wild recognition). His work consistently combines computer vision with audio processing, demonstrating expertise in both visual and auditory modalities for affective computing applications. Recent trends show growing interest in large language models for audio classification and addressing challenges of concept drift in text stream mining. Dr. Koerich actively supervises numerous graduate students across various research projects, with a particular focus on multimodal expression recognition, music genre classification, and robust machine learning systems. His collaborations span multiple institutions and research groups, reflecting the interdisciplinary nature of his work in artificial intelligence. He is a key member of the LIVIA laboratory, which has established ÉTS as a leading institution in computer vision research in Canada (ranked 6th according to CSRankings). The laboratory focuses on solving real-life problems through AI engineering, particularly in developing complex deep learning models with massive amounts of data that have incomplete annotations.

Simone Kügeler-RaceView profile

Lecturer

• Medieval German Literature
• Female Mysticism
• Devotional Literature
• +7 more

Dr. Simone Kügeler-Race serves as an Affiliated Lecturer in the Department of German within the Faculty of Modern and Medieval Languages and Linguistics at the University of Cambridge, affiliated with St John's College. Her expertise centers on medieval German literature and language, with specialized focus on female mystical traditions and devotional texts from the 14th-15th centuries. Education: Completed her doctorate at the University of Cologne under Professor Ursula Peters, supported by a full-time stipend from the a.r.t.e.s Graduate School for the Humanities Cologne and a DAAD research scholarship for manuscript analysis at major European libraries. Research Focus: Investigates Female Mysticism, Devotional Literature, and Material Philology through manuscript transmission studies, text typology, and narratological frameworks. Her work contextualizes The Book of Margery Kempe within continental women mystics' traditions, examining Carthusian reader annotations and devotional practices in late medieval Europe. Publication Trends: Recent works (2012-2022) demonstrate consistent exploration of women's mystical writings through material philology lenses, with emphasis on cross-cultural transmission, reader reception, and textual adaptations of works by Margery Kempe, Julian of Norwich, and Mechthild of Magdeburg. Scientific Awards: Full-time stipend from the a.r.t.e.s Graduate School for the Humanities Cologne DAAD research scholarship for manuscript analysis at British Library, Bodleian Library, and Cambridge University Library Pembroke College, Cambridge stipend (2011-2012) Academic Service: Served as Director of Studies in German at St John's College (2015-2018), providing undergraduate academic guidance. Current research on Carthusian reader annotations is supported by DAAD and college-level funding mechanisms, with active contributions to international symposia including the DFG-Symposion 'Migrationen der Lyrik um 1300, um 1800'.

• Artificial Intelligence in Education
• Open Educational Resources (OER)
• Writing Pedagogy
• +2 more

Anna Mills is a community college writing teacher, open textbook author, and advocate for critical AI literacy, Open Educational Resources (OER), and social annotation in writing instruction. She actively contributes to discussions on AI's impact on education through articles in The Chronicle of Higher Education , Inside Higher Ed , and JSTOR Daily , emphasizing strategies to balance creativity and critical analysis when integrating AI tools like ChatGPT into writing curricula. Key Projects: Co-developer of How Arguments Work (a free OER textbook), contributor to the AI Pedagogy Project at Harvard's metaLAB, and founder of the Peer and AI Review + Reflection (PAIRR) initiative for human-centered AI feedback. Collaborations: Works with teams including @pairrfeedback.bsky.social, Equity Unbound, and UC Davis researchers on AI-driven writing feedback tools. Research Focus: Explores AI's role in undergraduate writing, ethical implications of generative AI, and equitable pedagogical frameworks. Her work highlights tensions between technological adaptation and preserving human creativity, advocating for iterative prompt design and reflective writing practices. Recent Trends: Analyzes LLMs (ChatGPT, GPT-4) in assignment design, AI detection tools (Turnitin), and institutional responses to AI-driven academic integrity challenges. Advising & Outreach: Facilitates workshops on AI literacy, collaborates on open resource integration, and leads international professional development initiatives like MYFest25.