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Hilary KornblithView profile

Professor

University of Massachusetts AmherstUnited States

Hilary Kornblith is a Distinguished Professor in the Department of Philosophy at the University of Massachusetts Amherst. He has been a faculty member at UMass since 2003, after teaching for 24 years at the University of Vermont. He has also held visiting roles at the University of Michigan, University of Cologne, and Zhejiang University. Education: BA, State University of New York at Buffalo (1975) PhD, Cornell University (1980) Research Focus: Kornblith’s research integrates cognitive science with traditional epistemological problems. He explores how scientific understanding of the mind can reshape philosophical theories of knowledge, justification, and rationality. His work spans inductive inference, animal cognition, the role of reflection, and philosophical methodology. Publications and Themes: His recent publications emphasize naturalistic epistemology, the limits of reflective endorsement, the epistemic role of disagreement, and the continuity between human and animal cognition. He critiques traditional reliance on intuition and armchair theorizing, advocating instead for empirically informed philosophy. Scientific Awards: While no specific awards are listed, his extensive publication record and international recognition reflect significant scholarly impact. Advising and Grants: Kornblith has directed over 20 PhD dissertations, many in epistemology and philosophy of mind. His students have gone on to contribute to debates in self-knowledge, memory, testimony, and moral epistemology. Labs and Teams: While no lab is explicitly mentioned, his work aligns with interdisciplinary research in cognitive science and philosophy, often collaborating with scholars in psychology and neuroscience.

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Marco Aurélio GerosaView profile

Academic

University of California, IrvineUnited States

Marco Aurélio Gerosa is a Professor at Northern Arizona University and was previously an Associate Professor at the University of São Paulo (USP), Brazil . He is affiliated with the School of Informatics, Computing, and Cyber Systems (SICCS) at NAU and the Department of Computer Science at USP. His research focuses on the Human Aspects of Software Engineering , including Software Engineering Education , Computer Supported Cooperative Work (CSCW) , and AI-Assisted Software Engineering . He has published extensively on topics such as Open Source Software development, Bots and Chatbots in software engineering, and Mining Software Repositories techniques. His recent work explores Using Large Language Models (LLMs) for educational purposes in programming, data science, and software engineering Developing chatbots to facilitate newcomer onboarding to OSS projects Investigating the evolution of Integrated Development Environments (IDEs) Assessing the impact of software bots on projects Understanding how to design effective chatbot languages Dr. Gerosa has received numerous scientific awards, including ACM SIGSOFT Distinguished Paper Award Best paper awards at ICSE and International Symposium on Open Collaboration IEEE Computer Society TCSE Distinguished Paper and Service Awards Productivity grants from CNPq (Brazilian Council for Scientific and Technological Development) He has graduated numerous PhD students who are now researchers in top institutions worldwide and has been a mentor to many more at various levels. His research projects have secured over USD 1 million in funding. Dr. Gerosa is also involved in the development of tools and environments for software engineering, including MetricMiner for repository analysis and various gamification platforms to enhance developer engagement. He brings over 25 years of teaching experience across multiple universities, teaching courses ranging from Introduction to Programming to Advanced Topics on Web Development and Collaborative Systems Development.

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Danna GurariView profile

Assistant Professor

University of ColoradoUnited States

Dr. Danna Gurari is an Assistant Professor in the Computer Science Department at the University of Colorado Boulder and Founding Director of the Image and Video Computing Group. She specializes in computer vision, human-computer interaction, accessibility, and biomedical data analysis, emphasizing interdisciplinary approaches. Since 2017, she has taught over 400 students in graduate and undergraduate courses while leading a multidisciplinary research team. Her research spans 60+ peer-reviewed articles and has been supported by NSF, CZI, Microsoft, Adobe, and Amazon. She mentors over 30 mentees annually, from undergraduates to postdocs. Her work bridges academia and industry, informed by prior roles at Boulder Imaging and Raytheon. Education: Ph.D. in Computer Science from Boston University, postdoctoral fellowship at University of Texas at Austin, and industry experience at Raytheon. Research focuses on visual interpretation for accessibility, biomedical image analysis, privacy preservation, and hybrid human-machine systems. Key lab projects include AI solutions for blind individuals, cancer radiation therapy optimization, and visual privacy tools. Awards: Recognitions at top venues including WACV, CHI, CSCW, and MICCAI. Active in funding and grants, including NSF Explore Access and Google Cloud Education grants. Labs/Teams: Leads the Image and Video Computing Group, collaborating with medical campuses and industry partners. Projects include VizWiz Grand Challenge and disability-first dataset development.

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Heiko GewaldView profile

Professor

Schloss Dagstuhl - Leibniz Center for InformaticsGermany

Heiko Gewald is a Professor in the Department of Information Systems at Technical University of Munich's School of Management, with a distinguished research career spanning over two decades. His scholarly work demonstrates deep expertise in information systems, particularly focusing on technology adoption by aging populations, healthcare information systems, and smart mobility services. Dr. Gewald's research interests center on the intersection of technology and human behavior, with special emphasis on older adults' adoption of digital health applications , smart mobility ecosystems , and DevOps implementation . His work consistently addresses the challenges of designing technology that accommodates diverse user needs, particularly for vulnerable populations. Through extensive field research, he has developed frameworks for understanding technology acceptance barriers among seniors and created interventions to improve digital inclusion. Analysis of his recent publications reveals a clear trajectory toward increasingly specialized work in aging technology, with approximately 60% of his 2020-2025 publications focusing on older adult technology adoption. His research employs diverse methodologies including qualitative case studies, cross-cultural surveys, and experimental designs, often with international collaborations spanning Germany, Australia, and Thailand. Principal investigator for multiple German research projects on digital health for elderly populations Co-organizer of the annual HICSS minitrack on 'Seniors' Use of Digital Resources' since 2018 Active contributor to the Association for Information Systems (AIS) special interest groups Dr. Gewald has mentored numerous doctoral students who have become active researchers in information systems, with several now holding faculty positions. His research has been supported by German research funding agencies and industry partnerships with healthcare technology companies. He maintains strong collaborative relationships with researchers across Europe and Australia, particularly in the healthcare IT domain.

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Michael DeWeeseView profile

Associate Professor

University of California, BerkeleyUnited States

Michael DeWeese is an Associate Professor of Physics and Neuroscience at the University of California, Berkeley. His research spans nonequilibrium statistical mechanics, machine learning theory, and systems neuroscience. He holds a BA in Physics from UC Santa Cruz (1988) and a PhD in Physics from Princeton (1995). Before joining UC Berkeley in 2007, he held postdoctoral positions at the Salk Institute and Cold Spring Harbor Laboratory. His work integrates principles from physics, neuroscience, and machine learning to address fundamental questions in theoretical and experimental biology, computation, and statistical mechanics. DeWeese Lab Website provides further details on ongoing projects and collaborations. Education: BA in Physics, UC Santa Cruz (1988) PhD in Physics, Princeton University (1995) Research Interests: Nonequilibrium Statistical Mechanics: Focuses on thermodynamic optimization, active matter, and non-equilibrium processes. Machine Learning Theory: Develops first-principles models to explain neural network performance and efficient algorithms for probabilistic models. Systems Neuroscience: Uses biologically inspired models to understand neural coding, sensory processing, and computational roles of neural networks. Advising & Grants: While no formal student advisees are listed, his lab actively collaborates across disciplines. Funding sources are not explicitly mentioned but likely involve NSF, NIH, or DOE grants based on research themes. His work on quantum control and neural networks suggests potential ties to interdisciplinary funding initiatives. Labs & Teams: Directs the DeWeese Lab, which bridges physics, neuroscience, and machine learning. Collaborations include institutions like the Helen Wills Neuroscience Institute (UC Berkeley).

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Rachael GrewView profile

Senior Lecturer

Loughborough UniversityUnited Kingdom

Rachael Grew is a Senior Lecturer in Art History and Visual Culture at Loughborough University, serving as UG Programme Lead for Liberal Arts. She holds a PhD from the University of Glasgow (2010) and completed a postgraduate certificate in academic teaching practice in 2017, earning Fellowship of the Higher Education Academy. Her research focuses on gender, bodies, and identities in visual culture, particularly exploring hybridity and monstrous imagery across art, costume, and film from the mid-19th century to the present. Rachael’s work emphasizes Surrealism, with a specialized focus on artist Leonor Fini. She is an editorial board member of the International Journal of Surrealism and has published extensively on Fini’s contributions to art and design. Her research often intersects with themes of alchemical symbolism, gender fluidity, and material culture. Before joining Loughborough in 2016, she held teaching positions at Plymouth University, The Glasgow School of Art, and the University of Glasgow. Her teaching prioritizes visual culture’s role in understanding socio-cultural dynamics, with a particular fascination for figures that challenge conventional boundaries of gender, organic matter, and artistic expression. Her academic awards include the Higher Education Academy Fellowship. Though no grants are explicitly listed, her editorial work and extensive publications reflect significant scholarly engagement. She advises students on topics related to visual culture and surrealism but no specific student names are provided. Office hours are held weekly in E.1.06B during term time without prior appointment.

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R. ManmathaView profile

Adjunct Professor

University of Massachusetts AmherstUnited States

R. Manmatha is an Adjunct Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst and a Principal Scientist at Amazon A9 since 2013. His academic journey includes a Ph.D. in Computer Science from University of Massachusetts Amherst (1997), an M.S. in Electrical Engineering from University of Hawaii (1986), and a B.Tech in Electrical Engineering from Indian Institute of Technology Kanpur (1983). Research Interests Manmatha's work spans Computer Vision , Information Retrieval , and Document Analysis . Key projects include: Developing Vision-Language Models for GUI grounding and OCR-free document understanding Creating Word Spotting techniques for historical manuscripts like George Washington's papers Advancing Image Retrieval through statistical and relevance models Building Meta Search systems using score distribution analysis Optimizing Diffusion Transformers for text-to-image generation Scientific Contributions His research has led to numerous publications in conferences like SIGIR , CVPR , and ICDAR , focusing on: Automatic Image Annotation using cross-media relevance models Scale Space Techniques for handwritten manuscript segmentation Alignment Methods for document-groundtruth generation Indian Language Document Search via locality-sensitive hashing Transformer-based architectures for multimodal and document tasks Advising & Collaborations Manmatha has mentored students including Jiwoon Jeon , Shaolei Feng , Toni Rath , Jamie Rothfeder , and Nitin Srimal . He co-founded Snaptell (acquired by Amazon) and contributed to Amazon's mobile search technology. Labs & Teams He leads the Multi-media Indexing and Retrieval (MIR) group at the Center for Intelligent Information Retrieval (CIIR) , focusing on non-textual information indexing through ASCII conversion and direct content analysis.

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Marie Kawthar DaoudaView profile

Lecturer

University of OxfordUnited Kingdom

Dr. Marie Kawthar Daouda serves as a Stipendiary Lecturer in French at Oriel College, University of Oxford, where she teaches both literature and language courses across the undergraduate curriculum. Her academic work is situated within the French Department of Oxford's Faculty of Medieval and Modern Languages, one of the leading language departments in the UK. Dr. Daouda completed her academic training in French and English literature at La Sorbonne and the Université de Bretagne Occidentale. She earned her PhD with a thesis titled "L'Anti-Salomé, représentations de la féminité bienveillante au temps de la Décadence (1850-1920)", which was published as a monograph by Oxford, Peter Lang in 2020. Her second book project, "La Prière désespérée, de Baudelaire à Bernanos", is forthcoming from Garnier, continuing her exploration of spiritual dimensions in French literary tradition. Dr. Daouda's research focuses on challenging conventional understandings of femininity in literary history, particularly examining benevolent feminine figures in fin-de-siècle novels who counter the dominant "femme fatale" stereotype. Her work spans multiple interdisciplinary domains including the evolution of exoticism and orientalism from the Napoleonic era to the Third Republic, intersections between visual arts and literature, children's literature of the Second Empire, and the religious dimensions of literary works from the late 18th century through the 1930s. She demonstrates particular expertise in the literary movements of Naturalism, Decadence, and Symbolism and their complex interrelationships. Her scholarly publications reveal a consistent engagement with French literary traditions from the 19th and early 20th centuries, with special attention to Baudelaire's enduring influence, the reinterpretation of classical myths and fairy tales, and the complex relationship between religious thought and literary production. Dr. Daouda's research methodology demonstrates remarkable interdisciplinary breadth, connecting literary analysis with historical, theological, psychological, and gender studies perspectives to examine how literary figures negotiate authority, legitimacy, and creative expression within specific historical contexts. Monograph: "L'Anti-Salomé, Représentations de la féminité bienveillante au temps de la Décadence (1850-1920)", Oxford, Peter Lang, 2020 Monograph (forthcoming): "La Prière désespérée, de Baudelaire à Bernanos", Paris, Garnier As an educator, Dr. Daouda teaches across the full undergraduate curriculum at Oxford, covering Prelims Papers I-IV and Finals Papers I, II, VIII, and X. Her teaching spans major periods of French literature, from 17th-century works by Pascal and Racine to 20th-century texts by Proust and Camus. She has developed particular expertise in fin-de-siècle literature, teaching both canonical figures like Baudelaire and Mallarmé alongside less-studied authors such as Rachilde, Vivien, and Lorrain. Additionally, she serves as the Visiting Students Coordinator at Oriel College, supporting international students in their academic journey at Oxford.

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Cindy XiongView profile

Assistant Professor

Georgia Institute of TechnologyUnited States

Cindy Xiong is an Assistant Professor in the School of Interactive Computing at Georgia Tech. She holds a Ph.D. in Cognitive Psychology from Northwestern University and undergraduate degrees in Applied Mathematics and Psychology from UCLA. Her research focuses on the intersection of visual perception, cognition, and data visualization, aiming to understand how humans interpret and make decisions from visualized data. She has pioneered work on mitigating confirmation bias, perceptual illusions in charts, and the impact of visualization design on decision-making. Her research has been recognized with an NSF CAREER Award (2023) and an NSF Medium Award (2024), as well as best paper awards at IEEE PacificVis (2024) and ACM CHI (2022). She co-founded VISxVISION, an initiative bridging visualization researchers and perceptual psychologists. She also serves on the Human Factors Task Group at NIST to evaluate forensic lab standards. Teaching: She designed a UX Research course at UMass Amherst, emphasizing user-centered design, experimental methods, statistical analysis, and effective communication of research findings. The course involves group projects analyzing UX challenges and presenting data-driven solutions. Grants/Awards: NSF funding totaling $1.2M supports her work on visual analytic decision-making and mitigating confirmation bias. Her honors include VGTC Dissertation Award recognition (2022) and IEEE CG&A Best Paper Runner-Up (2022). Research Labs/Teams: Active in NIST's Human Factors Task Group and leading the VISxVISION collaboration. Her work often involves interdisciplinary teams combining psychology and computational methods.

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Trang VuView profile

Lecturer

Monash UniversityAustralia

Trang Vu is a Lecturer in the Department of Data Science & AI at Monash University's Faculty of Information Technology. Her research focuses on trustworthy NLP methods, cultural-aware machine translation, and efficient ML techniques like active and transfer learning. She holds a PhD in AI and Machine Learning from Monash University, awarded in 2022. Education: Doctoral of Philosophy (AI and Machine Learning) - Monash University (2022) Research Interests: Safe and trustworthy NLP methods for LLM alignment and hallucination mitigation Cultural-aware machine translation systems Efficient NLP techniques including active learning and semi-supervised methods Recent Projects: TMLGenAI (2023-2026): Developing safe and aligned foundation models Knowledge-Intensive Multimodal ASR research (2024) Collaborations: International collaborations in generative AI and multilingual NLP Team leader roles in multiple large-scale AI projects

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E. Mara GreenView profile

Assistant Professor

Barnard CollegeUnited States

E. Mara Green serves as an Assistant Professor of Anthropology at Barnard College, where she teaches anthropological theory, linguistic anthropology, disability studies, and South Asian cultures through the lens of deaf, queer, and feminist frameworks. Her research program investigates the ethical foundations of communication, emphasizing that mutual understanding requires both linguistic resources and social commitment to connection. Green's ethnographic work in Nepal examines deaf communities using Nepali Sign Language (NSL) and natural sign systems, revealing how communication practices intersect with caste, ethnicity, and bodily experience. Current projects explore NSL signers' parenting experiences and communicative strategies of queer and trans Nepalis across modalities, employing methodologies including video ethnography, participant observation, and linguistic analysis to document embodied interaction. Her 10 publications (2014-2024) demonstrate consistent theoretical innovation at the intersection of linguistic anthropology and deaf studies, challenging Western linguistic frameworks by centering Nepali signers' own theories of language. Key contributions include analyses of gesture pragmatics, sign language ideologies, and moral dimensions of international deaf encounters, culminating in the 2024 monograph Making Sense: Language, Ethics, and Understanding in Deaf Nepal . At Barnard, Green advises anthropology majors and mentors linguistics special majors through petition processes. While specific grant details are unreported, her inclusion in Barnard's 2020 faculty awards announcement suggests institutional recognition of research excellence through mechanisms like Fulbright support.

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Vedhus HoskereView profile

Assistant Professor

University of HoustonUnited States

Vedhus Hoskere is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Houston. His research focuses on interdisciplinary areas at the intersection of civil engineering, computer science, and robotics, emphasizing automated infrastructure inspection, machine learning, and AI-driven solutions for structural health monitoring. He holds the Liu Huixian Earthquake Engineering Scholarship (2018) for his work on automated post-earthquake building inspections. Key research areas include image analysis, machine learning, robotics, scientific computing, and visualization. His work integrates computer vision with civil infrastructure challenges, such as flood modeling, structural damage assessment, and autonomous inspection systems using drones and robotics. Notable projects include developing digital twin frameworks for bridges, synthetic environment testing for inspection algorithms, and semi-supervised learning for disaster damage analysis. His recent publications highlight advancements in transformer networks for instance segmentation, physics-informed generative models for damage assessment, and AI-driven hurricane resilience strategies. Hoskere collaborates on platforms like InstaDam for automated damage segmentation and explores Bayesian neural networks for quantifying uncertainties in infrastructure monitoring. Key Awards: Liu Huixian Earthquake Engineering Scholarship (2018) Advising & Labs: While no specific student names or grant details are provided, his research group likely focuses on robotics, computer vision, and AI applications in civil engineering. He contributes to open-source tools like the InstaDam platform and collaborates with institutions like the University of Illinois and USACE.

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Andrew BaylissView profile

Professor

University of East AngliaUnited Kingdom

Professor Andrew Bayliss is a Professor in Psychology at the University of East Anglia's School of Psychology, where he serves as Social Cognition Research Group Lead and UEA UOA4 Psychology REF coordinator. He joined UEA in 2011 after completing his PhD at Bangor University and holding postdoctoral fellowships with the ESRC, Leverhulme Trust, and University of Queensland. Undergraduate Degree: Bangor University PhD: Bangor University Postdoctoral Fellowships: ESRC, Leverhulme Trust, University of Queensland His research spans social cognition, attention-action interactions, and individual differences, with specific focus on face perception, eye gaze processing, and objects in social contexts. Utilizing methodologies including eye tracking, motion capture, EEG, and fMRI, his work examines how social cues guide attention and influence behavior. Current projects investigate gaze understanding development, interpersonal agency, and autism interventions using natural scenes. Analysis of his recent publications reveals a strong emphasis on social attention mechanisms, particularly gaze leading phenomena, interpersonal distance effects, and neural correlates of shared attention. His work increasingly integrates autism research with social cognition paradigms while maintaining core investigations into attentional orienting and agency perception. Bayliss actively contributes to the academic community through editorial roles at Psychological Review and Psychonomic Bulletin and Review, peer review activities, and consultancy work including the Social Neuroscience of Cinema Attendance project. He maintains international collaborations, notably with Paris Nanterre University. As Social Cognition Research Group Lead, he oversees a dynamic team investigating the neural and cognitive mechanisms underlying social interactions. His lab employs multimodal approaches to study real-time social processing, with recent work expanding into human-robot interaction and pandemic-related social adaptations.

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Yongfeng ZhangView profile

Associate Professor

Rutgers, The State University of New JerseyUnited States

Yongfeng Zhang is an Associate Professor in the Department of Computer Science at Rutgers University. He is also the Director of the AIOS Foundation . His research focuses on Machine Learning, Data Mining, Recommender Systems, and Explainable AI , with notable contributions to fair and personalized AI, AI for science, and social good. Education and Experience: PhD in CS (2011–2016) from Tsinghua University Postdoc at UMass Amherst (2016–2017) Joined Rutgers as Assistant Professor (2018), promoted to Tenured Associate Professor (2024) Research Interests: Machine Learning, Data Mining, Information Retrieval, Recommender Systems, Natural Language Processing, ML Systems, AI Agents, Explainable AI, Fairness, and AI for Science. Recent Achievements: Received the 2024 ACM SIGIR Test of Time Award, 2024 Presidential Teaching Excellence Award, and multiple NSF grants. He has advised over 15 PhD students and led projects on trustworthy AI, generative recommendation, and causal inference. Awards: 2024 ACM SIGIR Test of Time Award 2021 NSF CAREER Award 2015 Microsoft PhD Fellowship Grants & Labs: Led NSF grants on explainable AI, conversational recommendation, and neural-symbolic AI. Active in the AIOS platform development and multiple research labs.

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Cristian SECCHIView profile

Professor

University of Modena and Reggio EmiliaItaly

Cristian Secchi is a Full Professor in the Department of Engineering Sciences and Methods at the University of Modena and Reggio Emilia. His research focuses on robotics, control systems, and human-robot collaboration with an emphasis on safety, automation, and industrial applications. He teaches courses such as Industrial and Collaborative Robotics and Control of Robotic Systems. Research Interests: Design and implementation of control architectures for collaborative robots. Development of safe human-robot interaction frameworks compliant with ISO/TS 15066 standards. Integration of AI (e.g., large language models) into robotic motion planning. Autonomous systems for urban environments and surgical robotics. Publications highlight advancements in: Energy-efficient trajectory planning. Adaptive control strategies for uncertain environments. Multimodal human-robot communication. Diagnosis of mechanical systems via signal analysis. He leads the ARSControl research group and actively contributes to evolving production systems through smart modular technologies. His work bridges theoretical control frameworks with practical industrial and medical applications.

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