Find Academic Supervisors

Pier Luca Lanzi is a Full Professor at Politecnico di Milano, affiliated with the Department of Electronics, Information, and Bioengineering (DEIB). He leads the Artificial Intelligence and Robotics Lab (AIRLab), focusing on interdisciplinary research at the intersection of AI, robotics, and human-centric technologies. His work emphasizes applications in gaming, healthcare, and education, leveraging machine learning, evolutionary algorithms, and virtual reality. Education: Not explicitly stated in the provided texts. Affiliations: Director of the AIRLab; core member of DEIB. His research interests span artificial intelligence, multiagent systems, procedural content generation for games, serious games for rehabilitation, and AI-driven medical imaging. He explores how AI can enhance learning experiences (e.g., VR classrooms for physics and history) and improve therapeutic outcomes through interactive frameworks like the IGER system for stroke rehabilitation. Notable contributions include frameworks for automated level design in games (e.g., DOOM level generation via GANs), AI-assisted diagnostic imaging systems, and exergaming solutions for juvenile arthritis patients. His work often bridges computational intelligence with real-world applications, emphasizing human-centered design. Advising & Grants: While no specific grant details are provided, his prolific publication record suggests sustained research activity. Students and collaborators include prominent names in AI and robotics, though formal advisee名单 are not listed here. Labs/Teams: Directs the AIRLab, which develops cutting-edge technologies in AI, robotics, and human-technology interaction. Collaborates with industry and academic partners on projects ranging from VR educational tools to medical exergames.

• Artificial Intelligence
• Machine Learning
• Multiagent Systems
• +7 more

Diana Romei is a Temporary Part-Time Research Assistant affiliated with the Wolfson Institute of Population Health at Queen Mary University of London. She contributes to the SCENE project, focusing on population health research and primary care studies. Her work aligns with the institute's mission to advance understanding of health determinants and improve healthcare delivery. Research interests include epidemiological analysis, healthcare service evaluation, and clinical research methodologies. While specific publications are not listed here, her role suggests involvement in collaborative studies addressing public health challenges. No awards or grants are explicitly mentioned in the provided text. As part of the NIHR School for Primary Care Research ecosystem, she collaborates with multidisciplinary teams to advance translational research initiatives.

• Population Health
• Public Health Research
• Primary Care Studies
• +3 more

Professor David Forrest is a Professor of Music Education in the School of Art at RMIT University, Australia. He serves as HRD Coordinator and is actively involved in research supervision and academic leadership. His expertise spans music education policy, Russian/Soviet music pedagogy, and arts management, with a focus on the integration of music into educational curricula and community engagement initiatives. Professional Affiliations include the Association of Music Educators (Victoria), Australian Society for Music Education, and International Society for Music Education. He has received notable awards such as the 2021 Vice-Chancellor’s Award for Research Supervision Excellence and the 2015 Honorary Life Membership from the Australian Society for Music Education. Research interests center on music policy development, the legacy of composer Dmitri Kabalevsky, and the role of music in fostering intercultural understanding. His work emphasizes the importance of music for children and the symbiotic relationship between arts education and societal well-being. Professor Forrest supervises PhD and Master’s research in diverse areas including music education, arts policy, and creative practices. He has mentored over 17 research projects, ranging from music’s role in memory to contemporary musician career dynamics. He actively contributes to international academic discourse through editorial roles and peer-reviewed publications, advocating for the centrality of arts in education and policy frameworks.

• Music Education
• Arts Education
• Music Policy
• +5 more

Christine Holbo is an Associate Professor in the Department of English at Arizona State University, located on the Tempe campus. Her research focuses on American literature from the age of sentimentality to the modernist era, with a particular emphasis on how social values intersect with literary genres and forms. She explores the transformation of the novel in relation to competing forms of social knowledge and artistic expression. Dr. Holbo holds a Ph.D. in English from Stanford University. Her expertise lies in American literature, with a specialization in 19th-century works and the study of literary realism. Her first monograph, Legal Realisms: The American Novel under Reconstruction (Oxford UP, 2019), examines how social knowledge and empathy shaped American literary realism during post-Reconstruction America. Her research interests include the intersection of literature and social change, the evolution of narrative forms, and the role of literature in mediating cultural tensions. Her work frequently engages with authors like Albion W. Tourgée and Hamlin Garland, analyzing their contributions to understanding Reconstruction-era America and modernist literary movements. Dr. Holbo’s recent publications (2023–2025) focus on the legacies of Reconstruction-era literature, exploring themes such as racial reconciliation, economic narratives in fiction, and the political dimensions of narrative form. She has also contributed to discussions on modernist realisms and the cultural geography of American literature. While no formal awards are listed, her scholarship demonstrates sustained engagement with critical debates in American literary studies. Her advising activities and grants are not explicitly detailed in the provided materials, but her academic profile reflects an active research agenda in 19th- and early 20th-century American literature.

• American Literature
• 19th Century American Literature
• Literary Realism
• +3 more

Kasim Terzić is a Lecturer in the School of Computer Science at the University of St Andrews, where he conducts research and teaches in computer vision, machine learning, and robotics. He is affiliated with the Centre for Research into Ecological & Environmental Modelling and the Coastal Resources Management Group, reflecting his interdisciplinary focus on technology for environmental conservation. Education: PhD in Computer Science, University of Hamburg MSc in Information and Communication Systems, Hamburg University of Technology MSc in Global Technology Management, Hamburg University of Technology BEng (Hons) in Electronic Engineering, University of East Anglia His research interests center on computer vision and machine learning with applications in ecological monitoring and robotics. He focuses on bridging low-level pixel data with high-level semantic understanding, active vision, and the perception-action loop, often implemented on robotic platforms. He also advocates for open-source software and open data to democratize access to technology. Recent publications highlight his work in robotic manipulation of deformable objects like cloth and applications of deep learning in biological monitoring, such as fish age estimation and seal counting. His research spans computer science, ecology, and conservation, demonstrating a strong interdisciplinary approach. Professional Activities: External Examiner at Robert Gordon University (2020–2024) Invited speaker on machine learning in conservation and automated seal counting Organizing committee member for EAI MobiHealth conference Participant in public outreach events like Doors Open @ Computer Science Kasim Terzić supervises postgraduate research students and contributes to teaching in core and specialized computer science modules, including Computer Graphics, Machine Learning, programming, Operating Systems, and Databases. He is actively engaged in research output, dataset creation (e.g., Arctic charr re-identification), and promoting sustainable technology through open-source initiatives.

• Computer Vision
• Scene Understanding
• Machine Learning
• +7 more

Donald P. Land is a Professor of Chemistry at the University of California, Davis since 1991. His research focuses on surface chemistry at interfaces, including catalysis, biomedical implant interactions, and environmental remediation. He developed novel techniques like laser-induced thermal desorption (LITD) combined with Fourier transform mass spectrometry (FTMS) for studying surface reactions. His work integrates microscopy and molecular kinetics to understand structure-function relationships in surface chemistry. Education: Ph.D. in Chemistry (1989, UC Irvine), B.A. in Chemistry (1984, Lawrence University of Wisconsin). Postdoctoral training included Alexander von Humboldt Fellowships (1990-1991) and research at UC Irvine's Institute for Surface and Interface Science (1989-1990). Research emphasizes heterogeneous catalysis, surface reactivity of metals (e.g., Pd(111)), and analytical methods for studying adsorbate interactions. Recent work expanded into cannabis chemistry, forensic glass analysis, and polymer surface engineering. Publications span over three decades, with 15+ impactful articles since 2000. Notable contributions include studies on hydrocarbon decomposition on palladium surfaces and FTIR/FTMS-based surface characterization techniques.

• Surface Chemistry
• Catalysis
• Materials Science
• +5 more

Philippe Birgy is a Professor at the Center for Anglophone Studies (CAS), Université Toulouse – Jean Jaurès (UT2J), where he has been a faculty member since 2005, following his tenure as a Lecturer from 1996 to 2004. His academic home is within the Department of Cultures anglo-saxonnes, focusing on English and Anglo-Saxon languages, literature, and contemporary cultural history. His research interests include Modernist literature, literary theory, 20th-century British philosophy, the politics of literature, and the cultural significance of popular music—especially post-punk, techno, and electronic music. He explores the intersections between elitism and populism, reaction and revolution in literary and cultural movements, and has made significant contributions to Girardian criticism and Bakhtinian dialogics. His recent publications (2020–2023) reflect a sustained engagement with figures such as James Joyce, T.S. Eliot, H.G. Wells, and David Bowie, as well as subcultural movements like post-punk and PC music. His work spans journal articles, book chapters, edited volumes, and special issues, often appearing in journals like Miranda , Caliban , Europe. Revue littéraire mensuelle , and Volume! . He has co-edited works such as Understanding Bakhtin, Understanding Modernism (2023) and Landscapes and Legacies of David Bowie (2018), indicating a thematic focus on modernism, cultural memory, and artistic identity. Notable scientific contributions include explorations of sacrificial mechanisms in modernist literature, the role of forgetting in Eliot’s poetry, and the transnational circulation of electronic music. His articles frequently analyze narrative form, cultural resistance, and the ideological tensions between mainstream and underground movements. He has no listed scientific awards in the provided text, but his extensive publication record and editorial roles demonstrate recognition in his field. Philippe Birgy has supervised research and directed collective works, indicating an active role in mentoring and academic leadership. He has participated in conferences and roundtables on topics ranging from Sister with Transistors to modernist ethics, showing engagement with both literary and contemporary cultural debates. He has no listed grants in the provided text. He is affiliated with the Center for Anglophone Studies (CAS), a research unit dedicated to Anglophone cultures, where he contributes to seminars and academic events such as ARTLab and PoKES. The center serves as a hub for interdisciplinary research on literature, music, gender, and postcolonial studies.

• Modernist Literature
• Anglo-Saxon Languages and Literature
• 20th-Century British Philosophy
• +7 more

Prof. Katie Skinner is an Assistant Professor of Robotics at the University of Michigan, leading the Field Robotics Group (FRoG). Her research focuses on enabling autonomy in dynamic environments through advancements in perception, multi-sensor fusion, and robot learning. She specializes in underwater and space robotics, with applications in marine archaeology, autonomous vehicles, and planetary exploration. Her work has led to innovations in sonar-based perception, underwater SLAM, and neural radiance fields for 3D reconstruction. She has secured prestigious grants, including the NSF CAREER Award, and actively mentors PhD students like Advaith Sethuraman and Anja Sheppard. Prof. Skinner collaborates with institutions such as NOAA and NASA, contributing to real-world field deployments like the Thunder Bay National Marine Sanctuary surveys. The FRoG lab has developed datasets like AI4Shipwrecks, advancing machine learning for underwater exploration. Her educational background and prior roles are not explicitly detailed in the provided texts, but her extensive conference presentations (IROS, CVPR, ICRA) and leadership in major robotics initiatives underscore her expertise. She emphasizes bridging simulation and real-world deployments, with recent work on GPU-accelerated underwater simulation frameworks (OceanSim) and radar/sonar fusion techniques. Her lab’s contributions span both theoretical advancements and practical tools for autonomous systems in challenging environments. Awards: NSF CAREER Grant Key Collaborations: NOAA Ocean Exploration Program, Thunder Bay National Marine Sanctuary Labs/Teams: University of Michigan Field Robotics Group (FRoG)

• Field Robotics
• Underwater Robotics
• Space Robotics
• +5 more

John R. Kender is a Professor in the Department of Computer Science at Columbia University, affiliated with the Fu Foundation School of Engineering and Applied Science. He previously served as former Vice Dean of the same school and has been recognized as a Great Teacher by the Society of Columbia Graduates and a Distinguished Faculty Teacher by the Columbia Engineering School Alumni Association. His research focuses on computer vision, video understanding, gesture recognition, and artificial intelligence, supported by grants from DARPA, NSF, and industry partners like IBM and Microsoft. He has advised over 25 doctoral students and co-chaired the 2016 ACM International Conference on Multimedia Retrieval (ICMR). His teaching spans courses in object-oriented design, visual interfaces, and visual databases, with a strong emphasis on project-based learning. Kender's work includes pioneering contributions to semantic video indexing, multimodal analysis, and transfer learning techniques. Education: Advanced degrees in Computer Science (details not explicitly stated in texts). His research interests bridge computational methods and human-centric applications, including gesture-audience engagement correlations using EEG, cultural differences in news video production, and visual meme tracking in social media. His projects, such as the NSF-funded 'Tagging and Browsing Videos According to Affinity Groups,' highlight user-centered multimedia systems. Kender's work has been published in over 100 peer-reviewed articles and patents, addressing challenges in video segmentation, motion anticipation, and neuroimage alignment. Recent articles explore geometric approaches to transfer learning, 3D motion prediction, and cultural analysis through computational aesthetics. These reflect a trend toward cross-disciplinary methods combining AI, computer vision, and social sciences. Awards: Multiple teaching recognitions, including Columbia's top faculty teaching honors. Advising highlights include mentoring students across decades, with notable alumni contributing to academia and industry. His grants total over $10M from federal and industrial sources. Kender's lab focuses on real-world applications like educational video analysis, medical imaging, and event-driven multimedia systems. Current projects include developing explainable AI for video clustering and probabilistic GAN-based human motion prediction.

• Computer Vision
• Artificial Intelligence
• Video Understanding
• +7 more

Janine Incardona Scannella is a faculty member and teacher-researcher in the Department of French and Italian Philology at the Universitat de València, Spain. Her academic career is dedicated to the study of French Renaissance literature, with a particular focus on 16th-century sentimental narratives and the literary contributions of women. Her research interests include French Renaissance literature, onomastics, the literary emergence of women in Lyon, and the works of authors such as Hélisenne de Crenne and Claudine Scève. Her scholarship explores the interplay between narrative structure, naming practices, gender, and cultural identity in early modern French texts. The analysis of her 15 most recent publications reveals a consistent focus on textual analysis, translation history, and gender studies within the French Renaissance. Her work frequently examines the construction of female authorship, the adaptation of Italian texts in France, and the symbolic use of names in literature. She has contributed to major academic journals and edited volumes, often in collaboration with other scholars in the field. While no specific scientific awards are mentioned in the provided text, her sustained publication record in reputable journals and her co-editorship of significant volumes attest to her scholarly recognition. Her work bridges literary analysis, cultural history, and philology. She has been involved in academic advising and collaborative research, notably with Michèle Clément, and has participated in educational innovation projects related to language teaching. Her academic activities extend beyond her home institution, as evidenced by her participation in research seminars at UMR TELEMME in Aix-en-Provence. She has also contributed to pedagogical discourse on teaching French history and culture to diverse student populations.

• French Renaissance Literature
• Sentimental Narrative
• Onomastics
• +5 more

Ricardo Klein Caballero is an Associate Professor in the Department of Sociology at the Faculty of Social Sciences, Universitat de València, Spain. His academic work is deeply rooted in the sociological analysis of urban artistic expressions, particularly street art and graffiti. His research focuses on the intersection of culture, power, and identity, as reflected in his affiliation with the CECPI (Center for the Study of Culture, Power and Identities). His doctoral research explored street art scenes in Barcelona and Montevideo, positioning him at the forefront of cultural sociology in urban contexts. While no publications or awards are listed in the current profile, his academic trajectory emphasizes qualitative and ethnographic approaches to understanding subcultural dynamics and public space appropriation. He earned his PhD from the Universitat de Barcelona under the supervision of Dr. Arturo Rodríguez Morató. He is actively involved in research through the CECPI group, contributing to interdisciplinary studies on culture and social identity.

• Sociology of Art
• Street Art
• Graffiti
• +5 more

Malo Lucas Perez serves as a Doctoral Assistant at the Computer Vision Laboratory (CVLAB) within the Institute of Electrical Engineering at the School of Computer and Communication Sciences, Swiss Federal Institute of Technology in Lausanne (EPFL). He concurrently pursues doctoral studies in the Doctoral program in computer and communication sciences (EDIC). His research centers on Computer Vision and Machine Learning , with specialization in Artificial Intelligence and Image Processing . As part of CVLAB, he contributes to advanced projects in visual recognition systems, 3D scene reconstruction, and deep learning architectures for real-world vision applications. He maintains active affiliation with EPFL's Computer Vision Laboratory, a globally recognized research hub advancing state-of-the-art methodologies in computational imaging and visual understanding.

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +1 more

Ales Leonardis is a Professor at the University of Birmingham with significant contributions to computer vision, robotics, and artificial intelligence research. His work focuses on understanding complex visual scenes through physics-based and generative deep learning approaches. His research interests span computer vision, robotics, machine learning, and 3D generative models. Professor Leonardis explores how physical principles can be integrated with deep learning to create more robust and interpretable visual understanding systems. His work bridges the gap between theoretical computer vision and practical applications in robotics and scene understanding. His most notable publications demonstrate a consistent trajectory toward physically plausible 3D scene understanding and generation. The research shows increasing sophistication in modeling physical constraints within generative frameworks, with applications ranging from robotics to virtual environments. His work often combines classical computer vision techniques with modern deep learning approaches. His scientific achievements have been recognized through prestigious awards including the 2018 and 2023 Amazon Research Awards. These awards highlight his innovative work in understanding complex scenes in contained spaces and developing physically plausible controllable 3D generative models. Professor Leonardis has made significant contributions to advancing the field of computer vision through his research on scene understanding, 3D reconstruction, and physically grounded generative models. His work continues to influence both academic research and practical applications in robotics and artificial intelligence.

• Computer Vision
• Robotics
• Machine Learning
• +3 more

Xiaolong Wang is an Associate Professor in the Electrical and Computer Engineering Department at the University of California, San Diego with additional affiliations in the Computer Science and Engineering Department, Center for Visual Computing, Contextual Robotics Institute, and Artificial Intelligence Group. He serves on the Robotics team for the TILOS NSF AI Institute and has been faculty since 2020 after promotion from assistant to associate professor. Wang earned his Ph.D. in Robotics from Carnegie Mellon University under Abhinav Gupta, followed by a postdoctoral fellowship at UC Berkeley with Alexei Efros and Trevor Darrell. His academic journey includes collaborations with Berkeley AI Research, Facebook AI Research, and the Allen Institute for Artificial Intelligence. His research program focuses on exploiting structural information in data for visual representation learning, emphasizing spatial-temporal structures in videos and connections to 3D geometry and semantics. Key thrusts include self-supervised learning to eliminate manual labeling, video understanding for activity analysis, common sense reasoning for scene affordances, and robotic applications in dexterous manipulation and humanoid learning. The group develops comprehensive representations enabling robots to generalize across diverse physical environments through supervision signals from data, language, and common sense knowledge. Wang has received elite recognition including the Sloan Research Fellowship (2025), J.K. Aggarwal Prize (2024), and NSF CAREER Award (2023), alongside faculty honors from Intel, Cisco, Adobe, and multiple Amazon Research Awards. His fellowship pedigree includes Facebook, Nvidia, and Baidu Fellowships. Sloan Research Fellowship (2025) J. K. Aggarwal Prize (2024) NSF CAREER Award (2023) Intel Rising Star Faculty Award (2023) Cisco Faculty Award (2023) Adobe Data Science Research Award (2023) Amazon Research Award (2022 Spring) Amazon Research Award (2022 Fall) Amazon Research Award (2023 Fall) Sony Research Award (2021) Facebook Fellowship Nvidia Fellowship Baidu Fellowship He actively mentors award-winning students including Qualcomm Innovation Fellowship recipients (Jianglong Ye, An-Chieh Cheng, Yuzhe Qin, Yang Fu, Yinbo Chen, Jiarui Xu) and NVIDIA Graduate Fellow Nicklas Hansen. His research is funded by NSF, Amazon, Adobe, Sony, and industry grants while he serves as Area Chair for top AI conferences including ICLR, NeurIPS, CVPR, and ICCV. Wang leads a high-impact research group at UC San Diego with extensive industry partnerships (Amazon, NVIDIA, Qualcomm), producing award-winning work like the IROS 2024 Best Paper on Mobile Manipulation and ICRA 2024 Best Paper for Open X-Embodiment. The group's research spans foundational computer vision and machine learning to real-world robotics applications, with strong emphasis on technology transfer and embodied AI systems.

• Computer Vision
• Machine Learning
• Robotics
• +5 more

Wei Tang is an Assistant Professor at the Department of Computer Science , University of Illinois Chicago , focusing on computer vision and machine learning with emphasis on visual compositionality and data-efficient approaches. PhD from Northwestern University (2019) Research Interests : Computer Vision Machine Learning Visual Compositionality Data-Efficient Vision 3D Reconstruction Human Pose Estimation Recent Publication Trends : Pioneering part-whole structure modeling for 3D objects (CVPR'25, ECCV'24) Advancing visual dependency modeling in semantic segmentation (CVPR'21, PR'22) Innovating graph networks for pose estimation (ICCV'21, BMVC'20) Developing compositional networks integrating stochastic grammars (ECCV'18, ICCV'17) Academic Service : Associate Editor for Pattern Recognition (2024-present) Area Chair for ICCV'25 , BMVC'25 , ICME'25 , etc. NSF Panelist (2023-2024) Teaching : CS 515 Advanced Computer Vision (Spring 2025) CS 415 Computer Vision I (Fall 2024) CS 412 Introduction to Machine Learning (Spring 2024)

• Computer Vision
• Machine Learning
• Visual Compositionality
• +3 more