Find Academic Supervisors

Kate FrenchView profile

Associate Professor

• Educational Equity
• Urban Education
• Teacher Development
• +5 more

Kate French is an Associate Professor of Education at Hope College , specializing in the intersections of power, privilege, and oppression in teacher development. She teaches courses such as Foundations of Education and Secondary Principles, with a focus on clinical experiences for urban education. Education: Dual Ph.D. in Educational Policy and K–12 Educational Administration, Michigan State University, 2017 M.Ed. in Educational Policy and Leadership, Southern Methodist University, 2011 B.S. in Biomedical Sciences, Lee Honors College of Western Michigan University, 2009 Research Interests: Dr. French investigates educational equity for marginalized groups, contrasts early-career and seasoned educators, and challenges systemic assumptions in teacher education. Her work emphasizes inclusive learning environments and sociocultural contexts. Publication Trends: Her recent work focuses on teacher evaluation instruments, social justice in urban education, and the sociocultural influences on early-career educators. She employs humanistic inquiry and critical theory frameworks. Advising & Leadership: Dr. French previously chaired Madonna University's teacher education program and served as a postdoctoral fellow at Wayne State University. She mentors preservice teachers but no student names are listed in the provided text.

Jiyoung KimView profile

Senior Lecturer

• Korean language and linguistics
• Korean language pedagogy
• Second language acquisition
• +1 more

Jiyoung Kim serves as a Senior Lecturer in the Department of East Asian Languages and Cultures at Indiana University Bloomington's Hamilton Lugar School of Global and International Studies. She teaches elementary and third-year Korean courses (EALC KOR 101/301) and holds a PhD in Linguistics from the University of Hawaii at Manoa (2014), specializing in Korean language structures and pedagogy. Her academic background includes: PhD, University of Hawaii at Manoa, 2014 Dr. Kim's research centers on Korean grammatical phenomena—including imperfective aspect markers and modal verbs—and their acquisition by second language learners. She develops project-based curriculum frameworks for college-level Korean while integrating visual culture into pedagogical approaches, bridging theoretical linguistics with classroom practice to address learner challenges in morphosyntax and discourse. Publication analysis reveals consistent focus on Korean linguistic structures within acquisition and discourse contexts, with evolving emphasis from grammatical analysis (2009-2013) toward curriculum innovation through project-based learning (2015), demonstrating applied scholarship for Korean language education. No scientific awards are documented in the source material. Details regarding student advising, research grants, laboratory facilities, or collaborative research teams are unavailable in the provided documentation.

Musa KAYAView profile

Associate Professor

• Turkish Language Teaching
• Foreign Language Acquisition
• Educational Sciences
• +4 more

Musa KAYA is an Associate Professor at the Department of Turkish Education within the Faculty of Education at Bayburt University. His academic work focuses on Turkish language teaching, foreign language acquisition, and multicultural education. He actively contributes to curriculum development and analysis, particularly in alignment with European language standards. Research Interests : Turkish as a foreign language, language transfer phenomena, text simplification, cultural integration, value education, and reading comprehension. Article Trends : Recent publications examine Tunisian students' attitudes toward learning Turkish, comparative analyses of language programs, text complexity in Turkish instruction, and integration of cultural values through literature. Contact : Email - musakaya@bayburt.edu.tr | Phone - (458) 333-2033

Craig ChambersView profile

Professor

• Human Communication
• Cognitive Science
• Psycholinguistics
• +2 more

Craig Chambers is a Professor and Department Chair in the University of Toronto Department of Psychology. His research focuses on human communication , cognitive science , and psycholinguistics , particularly language processing across the lifespan and communication with social robots . Education: B.A. in Linguistics, York University M.A. in Linguistics, University of Toronto M.A. in Brain & Cognitive Sciences, University of Rochester Ph.D. in Brain & Cognitive Sciences and Linguistics, University of Rochester His lab investigates how speakers balance verbal and non-verbal information (gestures, intonation, environmental context) to convey meaning, and how listeners integrate these cues during comprehension. Recent studies explore pragmatic inferences , lexical competition , age-related differences in language processing, and social robotics applications . Key article trends include child language acquisition , speech perception in aging populations, multimodal communication , and language prediction mechanisms . Lab activities blend rigorous scientific inquiry with playful experimentation, including initiatives like "The PAL LAB PLAYS!"

Francesco LeofanteView profile

Research Fellow

• Explainable AI
• Counterfactual Explanations
• Robustness
• +3 more

Francesco Leofante is a Research Fellow at Imperial College London , affiliated with the Centre for Explainable AI . His work focuses on Explainable AI (XAI) , particularly counterfactual explanations with formal robustness guarantees against perturbations. Imperial College Research Fellowship DAAD AINet Fellowship (Safety and Security in AI) Imperial PFDC Supporting Research Staff and Students Award 2023 Research Interests center on Explainable AI , emphasizing counterfactual explanations , robustness , model multiplicity , and formal verification in critical systems like energy and aviation. His work bridges AI , formal methods , and human-AI collaboration . Publications include studies on robust counterfactual explanations , parametric ReLUs for verification, and multi-agent systems with formal guarantees. These appear in top venues like AAAI , KR , IJCAI , and AAMAS , often addressing AI safety and trustworthy systems . Scientific Awards include the Imperial PFDC Supporting Research Staff and Students Award 2023 , DAAD AINet Fellowship , and Imperial College Research Fellowship . He also contributes to workshops and program committees at conferences like AAAI, KR, and IJCAI. Future Work includes expanding robust XAI into critical infrastructure systems (energy, aviation) and developing tools like OMTPlan for AI planning and verification .

Jeffrey SteeleView profile

Professor

• Second Language Acquisition
• Laboratory Phonology
• Language Assessment
• +3 more

Jeffrey Steele is a Professor in French Studies at the University of Toronto. His research focuses on second language acquisition, laboratory phonology, and bilingual literacy. He explores how phonological and phonetic factors influence language learning, particularly the acquisition of French and Spanish segmental and prosodic features by Mandarin, Japanese, and English speakers. Steele also investigates the role of phonological awareness in bilingual children's literacy development. PhD in Linguistics, McGill University MA in French Linguistics, Queen’s University BA Hons in French, University of Manitoba Steele’s work employs electropalatography (EPG) to analyze articulatory timing, assimilation, and cluster simplification in native and non-native speech. His publications address topics like cross-linguistic influence on coda voicing, syllable position effects, and the impact of phonetic input variability on L2 learning. Recent studies highlight gradient and categorical effects in bilingual phonology, phonological licensing asymmetries, and prosodic prominence acquisition. He co-developed the University of Toronto Test of French and maintains the Romance Phonetics Database (2004–Present). SSHRC Insight Development Grant (2022–2027) on Reading Comprehension in French Immersion Learners Steele teaches courses in French language skills, linguistic analysis, and individual differences in language acquisition. His collaborations with researchers like Colantoni and Kochetov bridge theoretical linguistics and applied pedagogy.

Jeff LichtmanView profile

Professor

• Connectomics
• Neural Circuit Mapping
• Developmental Neuroscience
• +2 more

Jeff Lichtman serves as the Jeremy R. Knowles Professor of Molecular and Cellular Biology and Santiago Ramón y Cajal Professor of Arts and Sciences at Harvard University, where he leads research within the Department of Molecular and Cellular Biology in the Faculty of Arts and Sciences. His laboratory focuses on the physical basis of long-lasting memory and experience-driven neural circuit restructuring through advanced connectomic approaches. Dr. Lichtman's research program centers on connectomics and neural circuit development , utilizing transgenic Brainbow models for in vivo visualization and automated serial electron microscopy for nanometer-resolution mapping. His lab investigates synaptic competition during mammalian development, circuit rearrangement in peripheral nervous systems, and the structural underpinnings of memory formation. Key research areas include cellular and molecular neuroscience with emphasis on developmental processes, synaptic connectivity dynamics, and experience-dependent circuit refinement. Analysis of his 2021-2025 publications reveals dominant methodological innovation in machine learning-guided microscopy (e.g., SmartEM) and correlative imaging techniques , with expanding applications across model systems including zebrafish, octopus, and human tissue. Recent work increasingly addresses Alzheimer's disease pathology within connectomic frameworks while maintaining core focus on developmental circuit formation. The Lichtman Lab maintains active development of high-throughput tools for neural circuit mapping, including Fishexplorer for zebrafish circuit dissection and large-scale human cerebral cortex reconstructions, with ongoing projects examining both peripheral and central nervous system connectivity.

• Pharmacokinetics
• Transplantation
• Immunosuppressive Drugs
• +6 more

Anders Åsberg is a Professor at the Department of Pharmacy, University of Oslo, with a focus on pharmacokinetics and its application in organ transplant recipients. He leads the Section of Pharmacology and Pharmaceutical Biosciences and is actively involved in clinical studies related to immunosuppressive drug therapy. Current affiliation: Professor II, University of Oslo Previous roles: Managing Director, Renal Physiology Laboratory (2013–present); Medical Director, Roche Norge AS (2000–2003) Research Interests : Pharmacokinetics of immunosuppressive drugs Drug interactions in transplantation Role of transporters in drug disposition Population modeling for therapeutic drug monitoring Clinical trials in transplant recipients Effects of metabolic changes (e.g., gastric bypass) on drug metabolism Scientific Awards : Best Young Investigator, European Renal Association (2001) Collaborations span institutions such as the Clinical Pharmacokinetic Research Laboratory at the University of Rhode Island and the Laboratory of Applied Pharmacokinetics at the University of Southern California. His work frequently addresses the interplay between drug therapy, patient physiology, and long-term outcomes in kidney transplantation.

Antonio Calà LesinaView profile

Professor

• Computational Electromagnetics
• Nanophotonics
• Metamaterials
• +7 more

Antonio Calà Lesina is a Full Professor in Computational Photonics at the Leibniz University Hannover , leading research at the Hannover Centre for Optical Technologies . His academic journey includes a PhD in Information and Communication Technology from the University of Trento (2013), followed by postdoctoral and associate professor roles at the University of Ottawa (2013–2020). His research spans Nanophotonics , Metamaterials , and Plasmonics , focusing on inverse design, topology optimization, and dynamic control of optical systems via multiphysics simulations. Education : PhD (University of Trento, 2013); MSc in Telecommunications Engineering (University of Catania); BSc in Electronics Engineering (University of Catania) Current Position : Full Professor (Leibniz University Hannover, 2020–2025) His work explores Light-Matter Interactions and Nanostructures , with recent publications on anapole states , multiresonant metasurfaces , and hyperbolic metamaterials . He employs Finite-Difference Time-Domain (FDTD) simulations and deep learning for inverse design in nanophotonics. Collaborations include institutions like the University of Ottawa and research centers in Europe, aligning with the EULiST alliance . Despite no explicit awards mentioned, his contributions to optical beam steering , nonlinear metasurfaces , and machine learning integration highlight his impact in the field.

Sukalpa ChandaView profile

Associate Professor

• Machine Learning
• Zero-Shot Learning
• One-Shot Learning
• +7 more

Sukalpa Chanda is an Associate Professor at the Department of Computer Science and Communication, Halden University College. His research focuses on Machine Learning with applications to Document Image Analysis, Computer Vision, and Video Image Analysis, including advanced methods like Zero-Shot Learning, Deep Learning, and Transformer Networks. PhD in Computer Science from NTNU Appointments: Postdoctoral Researcher at Uppsala University (2018-2019) and Groningen University (2016-2018) Research Interests: Chanda specializes in Zero-Shot and One-Shot Learning for document and image analysis, with applications in handwriting recognition, face generation, and biomedical imaging. His work bridges theoretical machine learning with practical implementations in cultural heritage preservation and healthcare diagnostics. Scientific Collaboration: He collaborates with institutions like Indian Institute of Technology (Pallakad/Patna) and leads the Hugin Munin Project under The Digital Society research priority area. His team includes Master’s students and research assistants working on Transformer Networks and generative models. Key Publications: Recent works include frameworks for zero-shot action recognition (T2L, 2025), Nordic manuscript writer identification (2023), and advanced medical image segmentation networks (PAANet, 2021). His research spans document analysis, deep metric learning, and biomedical applications.

• Interactive AI
• Human-Centered AI
• Fairness in AI
• +3 more

Elizabeth M. Daly is a Research Scientist at IBM Research Laboratory, Dublin, and an Adjunct Assistant Professor at Trinity College Dublin's School of Computer Science and Statistics. Her work focuses on interactive AI , human-centered design , and fairness in algorithmic systems . She contributes to AI governance and LLM safeguarding through projects like AutoFair and Granite Guardian. Ph.D. in Computer Science (2007), Trinity College Dublin Thesis: Social Network Analysis for Routing in Disconnected Delay-Tolerant MANETs Her research interests span: Interactive AI : Facilitating AI-human negotiation for common objectives Trustworthy AI : Addressing fairness, accountability, and transparency in industrial applications Explainable AI : Developing tools like AIMEE for model exploration and editing She serves on the program committees of top conferences (RecSys, IUI, WWW, UMAP, ICWSM) and the Royal Irish Academy’s committee on Engineering and Computer Science. Notable scientific award: ACM Distinguished Member . Projects: AutoFair : Human-compatible automation of fairness in AI AIMEE : AI model explorer and editor tool Usage Governance Advisor : Translating AI intent into governance frameworks She leads the Interactive AI Group at IBM Research Europe - Ireland.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +6 more

Tengda Han is a Research Scientist at Google DeepMind , specializing in neural networks for video understanding. He earned his PhD from the University of Oxford under Andrew Zisserman and a BEng in Mechanical & Material Engineering from the Australian National University . Prior to his PhD, he studied business administration and law at Renmin University of China for one year. PhD in Computer Science, University of Oxford (2022) BEng in Mechanical & Material Engineering, Australian National University (2016) One year of business administration and law at Renmin University of China His research focuses on video representation learning , self-supervised methods , multimodal learning , and efficient prompting techniques . He has pioneered training-free frameworks for audio description, zero-shot object counting, and hyper-realistic movie generation. Recent publications demonstrate trends in temporal alignment , discriminative prompting , 5D video modeling , and open-world counting . His work often bridges computer vision with natural language processing and speech recognition . Scientific Awards : Best Paper Award at ACCV2024 Best Poster Award at BMVC2023 BMVA Sullivan Doctoral Thesis Prize Runner-up He has co-organized workshops at ICCV25 , NeurIPS23 , and BMVA Symposium on Vision & Language . Collaborators include Andrew Zisserman, Dima Damen, and Flamingo project members at DeepMind.

• Natural Language Processing
• Computational Linguistics
• Distributional Semantics
• +5 more

Ana-Sabina Uban is an Associate Professor at the Faculty of Mathematics and Computer Science, University of Bucharest . She earned her Ph.D. in Computer Science in 2020 under the supervision of Professor Liviu Dinu with a thesis on distributional and stylistic aspects of natural language. She teaches and coordinates courses in natural language processing, AI, and machine learning for both computer science and digital humanities students. Education: Ph.D. in Computer Science, University of Bucharest (2020) – Thesis: "Distributional aspects of natural language. Semantic and stylistic dimensions of text" Research Interests: Dr. Uban’s research is strongly interdisciplinary, bridging natural language processing , computational linguistics , psychology , and cognitive science . She explores historical computational linguistics , distributional semantics , and multilingualism , while also investigating explainability in AI models and mental health disorder detection using social media data. Research Trends & Publication Focus: Her recent publications span clinical NLP , mental health detection , historical linguistics , and multilingual cognate identification . A recurring theme is the application of advanced NLP techniques—such as transformer models, contrastive learning, and ensemble classification—to real-world problems in health, literature, and historical language study. Teaching & Student Supervision: Dr. Uban currently teaches and coordinates the following courses: Bio-medical NLP – Master’s level (English) Artificial Intelligence – Bachelor’s level for Mathematics students Practical Introduction to Machine Learning – Master’s level for Digital Humanities students Natural Language Processing 1 & 2 – Master’s labs and projects Contact: auban@fmi.unibuc.ro

Ivy WongView profile

Research Fellow

• Second Language Acquisition
• Cognitive Linguistics
• Applied Linguistics
• +3 more

Dr Ivy Wong serves as a Bowland Research Fellow at the Department of Education, University of York, while concurrently holding an Assistant Professor position at Hong Kong Shue Yan University (currently on sabbatical). Her research program centers on second language acquisition, specifically investigating how cognitive linguistics-inspired instruction enhances grammar learning through innovative digital tools and pedagogical frameworks. Her academic credentials include: PhD in Applied English Linguistics, The Chinese University of Hong Kong (2015-2018) MPhil in Applied English Linguistics, The Chinese University of Hong Kong (2013-2015) BA in English, The Chinese University of Hong Kong (2011-2013) Dr Wong's research bridges cognitive theory with practical language pedagogy, specializing in concept-driven grammar instruction for challenging structures like prepositions and conditionals. She pioneers computer-assisted methodologies using animated schematic diagrams and Bayesian statistical modeling to analyze individual learning trajectories. Her work emphasizes open science practices, with research materials publicly accessible via Gorilla platform. Recent publications reveal a methodological evolution toward Bayesian approaches in replication studies and neurocognitive investigations, while maintaining consistent focus on translating theoretical linguistics into classroom applications. Key themes include technology-enhanced grammar instruction, cross-linguistic influences on L2 acquisition, and evidence-based material development. Her scholarly recognition includes: Bowland Research Fellowship (2023-2025) Fulbright Visiting Scholar award (2017-2018) Dr Wong has secured substantial research funding including the SCOLAR Language Fund (£110,203; 2021-2023) for developing the English Preposition Tutor and the Bowland Fellowship for her current conditional acquisition project. Her teaching portfolio spans undergraduate modules in Psycholinguistics and Second Language Acquisition to postgraduate courses in Cognitive Linguistics, demonstrating comprehensive mentorship across academic levels. She actively contributes to the Centre for Advanced Studies in Language and Education (CASLE) at York, collaborating on interdisciplinary projects that integrate computational methods with language education research.

Samantha LaporteView profile

Assistant Professor

• Corpus Linguistics
• Construction Grammar
• World Englishes
• +3 more

Samantha Laporte is an Assistant Professor in English Linguistics at the University of Lille , affiliated with the Faculty of Languages, Cultures, and Societies and the Department of Anglophone Studies . Her research focuses on the cognitive representation of language through corpus linguistics and construction grammar , particularly in English as first, second, and foreign language . She investigates how grammar emerges from use and explores the link between social and cognitive dimensions of language. Key methods : Corpus-based analysis, Construction Grammar, Learner Corpus Research Labs : Affiliated with UMR 8163 - Laboratory of Knowledge, Texts, and Language