Find Academic Supervisors

Muhammad Abu Bakar SiddiqueView profile

Assistant Professor

• Natural Language Processing
• Large Language Models
• Machine Learning
• +7 more

Muhammad Abu Bakar Siddique is an Assistant Professor in the Department of Computer Science at the University of Kentucky, part of the Stanley and Karen Pigman College of Engineering. His research focuses on natural language processing, large language models, and machine learning with particular emphasis on zero-shot learning and conversational AI systems that are safe, personalizable, and interpretable. Dr. Siddique earned his Ph.D. in Computer Science from the University of California, Riverside (2017-2021), his M.S. from Lahore University of Management Sciences, Pakistan (2008-2011), and his B.S. from International Islamic University, Pakistan (2003-2008). His research interests include: Natural Language Processing and Large Language Models Zero-shot and few-shot learning for conversational AI Safe, personalizable, and interpretable conversational systems Task-oriented dialog systems with domain generalization Mobile app recommendation systems Scalable machine learning methodologies Dr. Siddique's publications span top venues including WWW, SIGIR, KDD, and IEEE S&P, demonstrating his focus on developing practical AI solutions that can adapt to new domains without extensive retraining. His recent work shows increasing exploration of quantum software and the intersection of AI with mobile applications. His notable achievements include Best Paper Awards at the IEEE International Conference on Quantum Software (2025) and IEEE ICSC (2021). Dr. Siddique has secured significant funding from the National Science Foundation: CPS Medium: Calfhealth: Explainable AI for Pneumonia Detection in Dairy Calves ($941,359) SaTC CORE: Personalized and Trustworthy Mobile App Recommendations ($300,000) III Small: User-Centric Task-Oriented Dialog Systems ($599,898) DCL EPSCOR: Distributed Edge Intelligence ($100,000) He currently advises three PhD candidates (Adib Mosharrof, Moghis Fereidouni, and Muhammad Umair Haider) and has mentored several successful graduates. Dr. Siddique serves on program committees for major conferences including ACL, NeurIPS, ICML, and AAAI, and participates in outreach by hosting high school students through the University of Kentucky's Summer Youth Program.

• Robotics
• Artificial Intelligence
• Human-Robot Interaction
• +3 more

Dr. Robert Haschke serves as a Professor and Responsible Investigator in the Cognitive Systems and Social Interaction Group at Bielefeld University's Faculty of Engineering. He is affiliated with the Center for Cognitive Interaction Technology (CITEC) and serves on the Examination Board for the Intelligent Interactive Systems Master's program. His office is located at CITEC 2-035, and he can be reached at rhaschke@techfak.uni-bielefeld.de or +49 521 106-12122. Professor Haschke's research spans multiple domains of robotics and artificial intelligence, with particular emphasis on tactile sensing systems, robotic manipulation, and human-robot interaction. His work explores advanced methods for enabling robots to perceive their environment through touch, with applications in assistive robotics and industrial automation. He investigates how machines can learn from human interactions and adapt their behavior through reinforcement learning and sensor fusion techniques. His research bridges theoretical advances with practical implementations, focusing on transferring knowledge from simulation to real-world robotic systems. Analysis of Professor Haschke's recent publications reveals a strong trajectory toward more sophisticated tactile perception systems and their integration with language and vision for natural human-robot collaboration. His work consistently addresses the simulation-to-reality gap, developing methods for transferring control policies from virtual environments to physical robots. The research shows increasing integration of multimodal sensing (tactile, visual, linguistic) to enable more capable and adaptable robotic manipulation in unstructured environments. As an educator, Professor Haschke teaches advanced courses including Robot Manipulators (39-Inf-RM), Advanced Artificial Intelligence (39-M-Inf-AI-adv_a), Advanced Artificial Intelligence (focus) (39-M-Inf-AI-adv-foc), and Basics of Artificial Intelligence (39-M-Inf-AI-bas). His teaching reflects his research expertise, providing students with both theoretical foundations and practical skills in robotics and AI. Professor Haschke is an integral member of Bielefeld University's Cognitive Systems and Social Interaction Group within CITEC. His work contributes significantly to the university's Socio-Technical World research area, particularly in developing capabilities that enable agents (humans, robots, and AI systems) to act, communicate, and learn in complex environments. His research group focuses on creating robotic systems that can interact naturally with humans through advanced perception and adaptive control mechanisms.

• Artificial Intelligence
• Machine Learning
• Neural Networks
• +3 more

Dr. Alan Blair is a Senior Lecturer at the School of Computer Science and Engineering, University of New South Wales. His research spans artificial intelligence, machine learning, and neural networks, with applications in medical imaging, evolutionary computation, and cybersecurity. Key research areas: Artificial Intelligence, Machine Learning, Neural Networks, Evolutionary Computation, Medical Imaging, Computational Linguistics Recent publications focus on reinforcement learning for medical diagnosis, dialogue act tagging, and phishing detection using feature-free tools. Collaborations include work with Sowmya A, Iyer S, and Dawes L on 3D organ localization and fracture detection in CT scans. Blair's work integrates hybrid neural-logical reasoning models for visual question answering and hierarchical evolutionary algorithms for optimization tasks. He has contributed to adversarial image generation and game theory applications.

Utku NormanView profile

Researcher

• Human-Robot Interaction
• Artificial Intelligence
• Educational Technology
• +4 more

Dr. Utku Norman is a Researcher at the Institute for Technology Assessment and Systems Analysis (ITAS), part of the Karlsruhe Institute of Technology (KIT) . His work focuses on Human-Robot Interaction and Artificial Intelligence applications in educational contexts, particularly through collaborative learning systems. Since 2023, he has contributed to projects like the Real-World Laboratory for Robotic Artificial Intelligence and JuBot , exploring the intersection of technology, cognition, and social impact. Ph.D. , Computer and Communication Sciences, EPFL, Switzerland (2023) M.Sc. , Computer Engineering, Bilkent University, Türkiye (2018) B.A. , Philosophy, Middle East Technical University, Türkiye (2018) B.Sc. , Electrical and Electronic Engineering, Middle East Technical University, Türkiye (2016) Norman's research integrates Technology Assessment and Systems Analysis to study how autonomous, self-learning AI systems interact with humans in practical settings. His work spans disciplines like Computational Thinking , Educational Robotics , and Machine Ethics , often combining empirical studies with algorithmic development. His publications highlight trends in Human-Robot Interaction , focusing on collaborative learning, robot perception in children, and ethical frameworks for autonomous systems. Notably, he contributed to establishing empirical methods for analyzing robot-mediated educational activities and developed tools like the ST-Steiner algorithm for genetic research in earlier career stages. Awards : Marie-Skłodowska-Curie PhD Fellowship (2018–2022) Norman has collaborated with institutions such as EPFL , Télécom Paris , and Bilkent University , participating in EU-funded projects like ANIMATAS . His current work involves analyzing social and psychological dimensions of robotics and developing empirical research methods in human-machine interaction. Contact: utku.norman@does-not-exist.kit.edu

Martin BastkowskiView profile

Lecturer

• English Language Teaching Methodology
• Teacher Training
• Active Learning
• +5 more

Martin Bastkowski, M. Ed., OStR, serves as a Lecturer in English Language Education at the Faculty of Humanities and Cultural Studies at Otto-Friedrich University of Bamberg and at the University of Hildesheim. He maintains a dual career as both an academic lecturer and a practicing school teacher at KGS Ernst-Reuter-Schule in Pattensen, where he holds the positions of Teacher and Head of Foreign Languages Department as well as Deputy Head of Secondary School I. His research and teaching interests focus on practical English language teaching methodology, with emphasis on active learning approaches, methodological diversity, communicative media use, performance assessment, and optimizing teaching and learning processes. His work bridges theoretical frameworks with classroom practice, providing valuable insights for both pre-service and in-service teachers. Bastkowski's recent publications reveal a growing engagement with digital education tools, AI applications in language teaching, collaborative learning approaches, and innovative assessment methods. His work consistently addresses practical classroom challenges while incorporating contemporary educational technologies and pedagogical approaches. Co-editor of the specialist journal 'Englisch 5-10' Co-author of the 'Lighthouse' textbook series (General and Advanced Editions) Regular contributor to professional development for English teachers Consultant for ministry commissions on English language education As an educator who maintains active classroom experience while contributing to academic discourse, Bastkowski offers valuable perspective on the practical implementation of teaching methodologies. His consultation hours at the university demonstrate his commitment to supporting teacher trainees in bridging theory and practice.

• Natural Language Processing
• Applied Data Science
• Computational Linguistics
• +3 more

Dr. Pablo Mosteiro Romero is an Assistant Professor at Utrecht University's Faculty of Social and Behavioural Sciences within the Department of Methodology and Statistics . His work bridges Natural Language Processing (NLP) , Applied Data Science , and Human-centered Artificial Intelligence , focusing on language change, morphology-syntax trade-offs, and applications in healthcare and open societies. Education: B.Sc. in Physics, Rutgers University (Summa Cum Laude, 2007) Ph.D. in Computer Science, Princeton University (2014, Centennial Fellowship) Research Interests revolve around computational linguistics, information-theoretic approaches to linguistics, and ethical AI. He investigates synonym evolution, morphosyntactic interactions, and fairness in mental health-focused AI systems. Recent work includes de-identification in medical texts and taxonomy induction via reinforcement learning. Publications span top venues like ACL, IEEE, and Springer, covering topics such as topic modeling interpretability, bias discovery in ML, and multimodal negation processing. Collaborations with colleagues like Scheepers, Spruit, and Kaymak highlight interdisciplinary applications in electronic health records. Awards include the Centennial Fellowship at Princeton and Summa Cum Laude at Rutgers. As a University Teaching Qualification holder, he teaches courses in data science, Python programming, and research methods, supervising theses in AI and Business Informatics. His work aligns with Utrecht's Institutions for Open Societies (IOS) theme, addressing gender diversity and global justice in data-driven systems.

• Natural Language Processing
• Corpus Linguistics
• Computational Linguistics
• +5 more

Ludovic TANGUY is a Professor at the Department of Language Sciences, University of Toulouse 2, where he conducts research within the Cognition, Languages, Ergonomics (CLLE) research unit. His academic journey includes a Habilitation à diriger des recherches (HDR) from University Toulouse le Mirail - Toulouse II in 2012 and a PhD from University of Rennes 1 in 1997 with a thesis on Natural Language Processing and interpretation. Professor TANGUY's research spans multiple areas within computational linguistics, with particular focus on Natural Language Processing, corpus linguistics, and distributional semantics. His work demonstrates expertise in analyzing online discourse, particularly through Wikipedia talk pages, and applying computational methods to linguistic phenomena. He has developed innovative approaches for studying sociolinguistic variation using Twitter corpora and neural word embeddings, contributing significantly to understanding how language evolves in digital environments. His recent publications reveal a strong trend toward analyzing computer-mediated communication, with numerous studies examining Wikipedia interactions, conflict detection, and discourse patterns. TANGUY has also made substantial contributions to distributional semantics research, exploring how word embeddings can model semantic relationships in specialized domains like family vocabulary. His work bridges theoretical linguistics with practical applications in information retrieval and natural language processing. As an active researcher with publications spanning from 1997 to 2024, Professor TANGUY has established himself as a prominent figure in French computational linguistics. His collaborative work, particularly with researchers like Lydia-Mai Ho-Dac, Cécile Fabre, and Nabil Hathout, demonstrates a strong network within the academic community. His research has been published in reputable journals and presented at major conferences in computational linguistics and corpus linguistics.

Julie ShahView profile

Professor

• Robotics
• Human-Robot Interaction
• Autonomous Systems
• +4 more

Julie Shah is the H.N. Slater Professor at the Department of Aeronautics and Astronautics and leads the Interactive Robotics Group at MIT’s Schwarzman College of Computing . She focuses on creating robots that work effectively alongside humans in dynamic environments, combining expertise in artificial intelligence, human factors, and systems engineering. BS, SM: Aeronautics and Astronautics (MIT) PhD: Autonomous Systems (MIT) Her research explores human-robot collaboration , emergent communication , and trust calibration in automated systems, with applications in manufacturing, surgery, and space exploration. Recent publications highlight advancements in language-guided abstraction , human-in-the-loop policy adaptation , and ethics-aware AI . Julie Shah has received prestigious accolades including the NSF CAREER award and recognition in the MIT Technology Review TR35 . Her lab’s work on industrial human-robot collaboration was named one of the 10 Breakthrough Technologies of 2013 by Tech Review. She previously worked at Boeing Research and Technology , where she developed innovative methods for human-robot teamwork in safety-critical domains. Her lab at MIT continues to push boundaries in robot locomotion , situational awareness , and sociotechnical systems .

Fabio CiambellaView profile

Researcher

• Corpus Linguistics
• Shakespeare Studies
• Translation Studies
• +3 more

Fabio Ciambella is a Researcher at the Department of European, American, and Intercultural Studies of Sapienza University of Rome . His academic work focuses on Corpus Linguistics , Shakespeare Studies , Translation Studies , and Early Modern English pragmatics. Teaches Second Language Acquisition (first semester) and English Language 3 (second semester) Specializes in dance lexicon analysis, historical translation reception, and CLIL methodology His publications demonstrate interdisciplinary connections between: Shakespearean language and modern media (ads, news, memes) Italian Renaissance dance manuals and English theatrical practices AI-assisted translation of historical varieties Eco-discourse pragmatics in food columns Office hours available via individual scheduling through fabio.ciambella@uniroma1.it

• Geographic Information Systems
• Spatial Data Analysis
• Environmental Informatics
• +5 more

Phil Bartie is an Associate Professor in the Department of Computer Science at Heriot-Watt University's School of Mathematical and Computer Sciences in Edinburgh. His research integrates spatial analysis with environmental and social issues, focusing on how geographic information systems can address urban sustainability challenges. Current affiliations include active supervision of PhD students and collaboration with interdisciplinary teams across environmental science and social policy domains. His research interests center on Geographic Information Systems (GIS), spatial data analysis, and environmental informatics, with specific applications in blue space accessibility, urban planning, and energy policy analysis. Work examines how natural environments impact wellbeing, particularly during crises like the COVID-19 pandemic, and investigates public attitudes toward energy transitions using social media analytics and mixed-methods approaches. Key methodologies include geospatial modeling, Twitter activity mapping, and solicited research diaries for longitudinal wellbeing assessment. Recent publications reveal strong trends in spatial analysis of environmental-social intersections, particularly examining UK public discourse on fracking through Twitter geotagging, climate change belief systems influencing energy attitudes, and restorative benefits of inland blue spaces. His work consistently bridges technical GIS capabilities with societal challenges, contributing to UN Sustainable Development Goals related to sustainable cities and climate action. Phil Bartie actively supervises PhD students and contributes to research grants focused on urban environmental systems, though specific grant details aren't publicly enumerated. His REAL corpus dataset (2016) demonstrates expertise in creating multimodal language resources for spatial reference resolution. Research occurs within interdisciplinary teams addressing urban sustainability, with emphasis on translating geospatial analysis into practical urban planning applications and environmental policy recommendations. Current projects examine spatial dimensions of energy transitions and nature-based wellbeing interventions in urban contexts.

Debayan BanerjeeView profile

Researcher

• Artificial Intelligence
• Explainability
• Machine Learning
• +5 more

Dr. Debayan Banerjee is a Researcher at the Institute for Business Information Systems (IIS) and part of the Professorship for Business Informatics, especially Artificial Intelligence and Explainability at Leuphana University Lüneburg. His work bridges academic research with practical applications in knowledge management, network science, and AI systems. Institute: Institute for Business Information Systems (IIS) Professorship: Business Informatics, Artificial Intelligence and Explainability Location: Universitätsallee 1, C4.308b, Lüneburg (21335) Email: debayan.banerjee@leuphana.de Research interests focus on knowledge graph integration, hybrid intelligence systems, and explainable AI. His projects include USIN5G, ARDIAS, and INSTANT, emphasizing human-AI collaboration and scholarly data accessibility. Recent publications highlight SPARQL translation automation, hybrid question answering frameworks, and environmental impact analysis of language models. Collaborative work spans DBpedia-Wikidata interoperability, DBLP knowledge graph applications, and graph embeddings for QA systems. Education and advising : Mentored students include Mathias Gross, Fatemeh Ghoochani, and Soham Majumder, focusing on final theses related to AI-driven data extraction and knowledge graph development.

• Natural Language Processing
• Computational Linguistics
• Educational Technology
• +3 more

Rebecca Jane Passonneau is a Professor in Computer Science and Engineering, specializing in Natural Language Processing and its applications in Science Education . Her research focuses on developing NLP-enabled tools for automated assessment and feedback in science writing. Research Interests: Automated assessment, computational linguistics, discourse analysis, educational technology, and AI-human partnerships in science education. Grants: Multiple NSF-funded projects (2015–2026) addressing scientific literacy, argumentative essay analysis, and automated feedback systems. Publications: Emphasize formative assessment , scientific explanations , and AI-driven educational tools , with recent work on eliminating linguistic bias in NLP systems. Projects: Lead PI for initiatives like CAP (2016–2023), EAGER (2018–2021), and CLASSIFIES (2023–2026), targeting scalability in science education.

• Natural Language Processing
• Computational Linguistics
• Theoretical Linguistics
• +3 more

Stergios Hadjikyriakidis is a Professor of Computational Linguistics at the Department of Philology, University of Crete. He holds a BA in Greek Philology (Linguistics specialization) from Aristotle University of Thessaloniki, an MSc in Computational Linguistics and Formal Grammar from King's College London, and a PhD in Linguistics from the same institution. He has held academic positions at Royal Holloway (University of London), CNRS (France), Open University of Cyprus, and University of Gothenburg. Research interests include: Natural Language Inference Dialogue Modeling Retrieval-Augmented Generation (RAG) Semantic Parsing Sentiment Analysis Metaphor Detection Interactive Theorem Proving for Natural Language Semantics Computational Dialectology Constructive Type-Theoretical Semantics Probabilistic Semantics Developing language resources for under-resourced languages Interaction between symbolic logic-based approaches and neural methods His work bridges theoretical linguistics and machine learning, focusing on probabilistic NLP implementations and cross-disciplinary methodological synthesis. Literary work : 4 novels in Greek: Grover , Skalomenoi se ena bar , Mēn milās, den eīnai aparemphaton , and an unnamed fourth 2 short story collections: one in English and one in Greek (e.g., Bats'niēs: Pyknes kart-postal apo ta Valkania )

Niranjan BalasubramanianView profile

Assistant Professor

• Natural Language Processing
• Information Retrieval
• Question Answering
• +3 more

Niranjan Balasubramanian is an Assistant Professor in the Department of Computer Science at Stony Brook University with additional affiliations in the Department of Biomedical Informatics and the Center of Excellence in Wireless & Information Technology (CEWIT). His research focuses on Natural Language Processing and Information Retrieval systems that extract, understand, and reason over textual information. Education: PhD, University of Massachusetts Amherst (Center for Intelligent Information Retrieval) MS, Computer Science, University at Buffalo (2003) His research spans question answering for elementary education, event schema generation from news, machine learning for information retrieval, energy-efficient mobile search, and automatic Wikipedia content generation. Recent work explores causal reasoning in event extraction, multimodal claim verification, authorship fairness, and secure coding with large language models. Analysis of his 15 most recent publications (2024-2025) reveals intensive focus on advancing NLP through causal/temporal reasoning, multimodal verification, and LLM optimization. Key trends include psychological modeling of human language, energy-efficient architectures, and addressing misattribution in authorship analysis. Scientific Awards: No awards mentioned in provided text Advising and grants information was not provided in the source materials. His postdoctoral background at the University of Washington's Turing Center and industry experience at Syracuse University's Center for Natural Language Processing inform his applied research approach. Labs and Teams: Affiliated with Stony Brook's Center of Excellence in Wireless & Information Technology (CEWIT), contributing to interdisciplinary AI initiatives while maintaining primary focus in the Computer Science department.

Qi FengView profile

Assistant Professor

• Deep Learning
• Computer Graphics
• Computer Vision
• +5 more

Qi Feng is an Assistant Professor at the Faculty of Science and Engineering, Waseda University, specializing in deep learning applications for computer graphics and vision, with a focus on virtual and augmented reality. He holds a Doctor of Engineering (2022), Master of Engineering (2019), and Bachelor of Engineering (2017) from Waseda University. Research Interests: His work spans 3D reconstruction, depth estimation, occlusion handling, and multimodal systems integrating eye tracking and speech recognition. Notable projects include SyncViolinist for audio-driven motion generation and the Depth360 dataset for omnidirectional imaging. Publications: Qi's research has been featured in top conferences like CHI, ISMR, ICCVW, and journals such as The Visual Computer. His articles emphasize practical solutions for immersive environments, language learning, and synchronized audio-visual editing. Contact: Email: fengqi@ruri.waseda.jp