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John Gallagher is Associate Professor in English and Information Sciences at UIUC. His research examines how writers adapt to participatory audiences in digital environments, including social media interactions and AI writing tools. Using case studies and computational methods, he explores algorithmic audiences, ethical implications of AI, and technical communication in institutional contexts. He teaches courses in professional writing, digital rhetoric, and research methodologies. Recent projects analyze content creators' narratives about platform algorithms, inclusive emoji design, and academic integrity challenges posed by generative AI.

• Digital Writing
• Audience Analysis
• AI Communication
• +1 more

Rachel Rudinger is an Assistant Professor at the University of Maryland, affiliated with the Department of Computer Science and the University of Maryland Institute for Advanced Computer Studies (UMIACS). Her research focuses on Natural Language Processing (NLP), Machine Learning, and AI ethics, particularly addressing sociocultural biases and fairness in large language models (LLMs). She holds a PhD from Johns Hopkins University (2019) and a B.S. from Yale University (2013). Rudinger's work explores equitable cultural alignment in AI systems, common ground misalignment in dialog systems, and the mutual influence of gender and occupation in LLMs. She received the NSF CAREER Award in 2024 for her project on robust, fair, and culturally aware commonsense reasoning. Her recent publications investigate empathy gaps in LLMs, synthetic data effectiveness in disaster response, and bias measurement techniques across domains. As an advisor, she guides seven PhD students including Christabel Acquaye and Haozhe An. Her research spans diverse topics from legal language analysis to maternal health question answering, reflecting her commitment to interdisciplinary AI ethics. She actively contributes to workshops on commonsense representation and serves as a reviewer for top conferences in NLP and AI.

• Natural Language Processing
• Machine Learning and Data Science
• AI and Robotics
• +1 more

Katherine Isbister is a full professor in the Department of Computational Media at the University of California, Santa Cruz, where she directs the Center for Computational Experience. She was previously an associate professor jointly appointed between the Computer Science department at New York University’s Tandon School of Engineering and the NYU Game Center, and served as the founding Research Director of the Game Innovation Lab at NYU. Her research lies at the intersection of Human-Computer Interaction and digital games, focusing on emotion, social connection, and playful experiences. Key research themes include emotion in games , social play , fidget technologies , social VR , and digital characters . Her work combines technical prototyping, design research, and empirical evaluation to understand how interactive systems can support emotional and social experiences. Her publications span top venues such as CHI, DIS, and IEEE Transactions on Affective Computing. Trends in her recent work show a strong emphasis on embodied interaction, affective design, and socio-technical systems for emotional regulation and social connection. She explores how movement, touch, and presence in virtual spaces can enhance human experience. MIT Technology Review TR100 Young Innovator (1999) Best Paper Award, ACM CSCW (2018) New Voices New Visions Award (for SimWorks art series) She has advised numerous students and led research projects involving social wearables, movement-based games, and mental health interventions. Her lab has received recognition from media outlets including NPR, Scientific American, and The Guardian. She has also collaborated with industry partners such as Microsoft, Electronic Arts, and Ubisoft. She leads the Center for Computational Experience at UCSC and has previously directed the Game Innovation Lab at NYU. Her team has produced over 100 peer-reviewed publications and several exhibition-ready games and art installations.

• Human-Computer Interaction
• Digital Games
• Emotion in Design
• +12 more

Roberto Manduchi is a Professor of Computer Science and Engineering at the University of California, Santa Cruz, within the Baskin School of Engineering. His primary affiliation is with the Computer Science and Engineering department where he leads research in assistive technology for visual impairments. He holds a Dottorato di ricerca in Electrical Engineering from the University of Padova, Italy, and previously worked at Apple and NASA JPL before joining UCSC in 2001. His research focuses on mobile computer vision, inertial sensors, and location-aware systems to enhance spatial awareness and information access for blind and low-vision individuals. Key research areas include indoor navigation systems, screen magnification for low-vision readers, obstacle detection using augmented reality, and text accessibility assessment through specialized OCR pipelines. His work bridges computer vision, human-computer interaction, and accessibility design. Analysis of his recent publications (2022-2025) reveals strong emphasis on inertial-based indoor navigation (e.g., PALMS localization system, backtracking algorithms), screen magnification usability studies, and novel approaches to scene text access for blind users. His research consistently targets practical applications for visual impairment, with significant contributions to pedestrian dead reckoning, magnetic signature localization, and gaze-contingent interfaces. Manduchi serves on the scientific advisory board of Aira and is a board member of the Vista Center for the Blind and Visually Impaired. He leads the UCSC Computer Vision Lab where his team develops accessible computing solutions. His work includes both theoretical contributions to computer vision and tangible assistive applications, with recent projects focusing on smartphone-based inertial odometry, multi-scale tactile maps, and real-time obstacle cueing systems.

• Computer Vision
• Assistive Technology
• Human-Computer Interaction
• +2 more

Dr. Chandranath Adak is an Assistant Professor at the Department of Computer Science and Engineering, Indian Institute of Technology Patna (IIT Patna), and concurrently serves as a Visiting Fellow at the School of Computer Science, University of Technology Sydney (UTS), Australia. He holds a Ph.D. in Analytics from UTS (2019) and previously served as an Assistant Professor at Indian Institute of Information Technology Lucknow (IIITL) and the Centre for Data Science at JIS Institute of Advanced Studies, Kolkata. Education: Ph.D. (Analytics), University of Technology Sydney (2019) M.Tech., Computer Science and Engineering, University of Kalyani (2014) B.Tech., Computer Science and Engineering, West Bengal University of Technology (2012) Research Interests: His work spans Computer Vision, Deep Learning, Reinforcement Learning, Document Image Analysis, and AI-driven solutions for healthcare, forensics, and industrial automation. He has pioneered methods in biomarker detection using electrochemical sensors combined with ML models, handwriting analysis for educational and forensic applications, and anomaly detection in industrial systems. His research bridges theoretical advances with real-world applications, such as medical diagnostics and quality control systems. Publications: His recent work includes innovations in biosensor-based medical diagnostics, handwriting evaluation systems, and transformer networks for historical document analysis. These contributions reflect a focus on interdisciplinary applications of AI across healthcare, cultural heritage preservation, and industrial automation. Awards: Start-up Research Grant, SERB, India (2022) Dr. Kalam Doctoral Scholarship, UTS (2018) IEEE CIS Graduate Student Research Grant (2017) Senior Member, IEEE (2024) Teaching & Supervision: Taught courses at UTS including 'Introduction to Data Analytics' and supervised research in machine learning and computer vision. His mentorship emphasizes hands-on experience with AI tools and real-world problem-solving. Labs & Teams: Engaged in collaborative projects at UTS's CIBCI Centre and Griffith University's IIIS, focusing on computational intelligence and sensor-driven AI systems.

• Computer Vision
• Deep Learning
• Reinforcement Learning
• +7 more

Thomas Pape is a Professor at The Natural History Museum of the University of Copenhagen, specializing in the systematics, taxonomy, phylogeny, biogeography and evolution of Diptera (two-winged insects), with special emphasis on Calyptratae families including Sarcophagidae, Oestridae, and Calliphoridae. He has been a professor since 2025 after serving as an Associate Professor from 2004-2024. PhD from Copenhagen University (1990) Docent at Stockholm University (1998) Associate Professor at Danish Bilharziasis Laboratory (1990-1992) Research Entomologist at Naturhistoriska Riksmuseet, Stockholm (1994-2004) His research spans taxonomy, systematics, phylogeny, biogeography and evolution of Diptera with special emphasis on calyptrate families. He collaborates on Systema Dipterorum, conducts comparative larval morphology studies, and investigates the phylogeny of Calyptrata. His work includes Diptera nomenclature and large-scale biodiversity inventories. Analysis of his recent publications reveals a strong trend toward molecular phylogenetics (using RAD-seq and anchored phylogenomics), forensic entomology applications, and biodiversity informatics. His research spans entomology, systematics, evolutionary biology, and increasingly intersects with bioinformatics and conservation science, with significant contributions to understanding flesh flies, bot flies, and blow flies. President of the International Council of Zoological Nomenclature (since 2016) Chair of the Council for the International Congresses of Dipterology (2010-2018) Member of editorial boards for Entomotropica, Studia dipterologica, Stuttgarter Beiträge zur Naturkunde, and Tijdschrift voor Entomologie Dr. Pape teaches courses in Entomology (structure, phylogeny and biology of terrestrial arthropods), Field Biology II - Zoology, and Ecology and Evolution of East Africa (a 2-week field course in Tanzania with Nikolaj Scharff). He has served on scientific panels for SYNTHESYS and as chair of the scientific advisory committee for Museum Koenig in Bonn (2006-2009). His research group employs both morphological and molecular approaches to address evolutionary questions in Diptera, with particular expertise in calyptrate families. The laboratory maintains active international collaborations across multiple continents, as evidenced by his extensive publication record and research network.

• Systematics
• Taxonomy
• Phylogeny
• +7 more

Toby Jia-Jun Li is an Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame, where he leads the SaNDwich Lab. He also serves as the Director of the Human-Centered Responsible AI Lab in the Lucy Family Institute for Data & Society and is a Faculty Fellow at the Institute for Educational Initiatives (IEI). Previously, he was affiliated with Carnegie Mellon University's Human-Computer Interaction Institute (HCII) and GroupLens Research. Dr. Li's research spans the intersection of Human-Computer Interaction (HCI), End-User Software Engineering, Machine Learning (ML), and Natural Language Processing (NLP), with recent work focusing on addressing societal challenges in the future of work through human-AI collaborative approaches. His work has resulted in over 40 publications at premier venues including CHI, UIST, CSCW, ACL, and ICSE, with 8 papers winning Best Paper or Honorable Mention awards. His recent publications demonstrate a strong focus on human-AI collaboration across various domains, including code understanding, privacy, accessibility, and creative tools. The work shows a trajectory toward increasingly sophisticated integration of human-centered design with AI capabilities, particularly using large language models to enhance human productivity and address societal challenges. Google Research Scholar Award recipient Recipient of Yahoo! Fellowship ($100,000/year) Best Paper Award at UIST 2020 Best Paper Honorable Mention Award at CHI 2021 Best Paper Award at CSCW 2024 Best Paper Award at CHI 2025 Dr. Li actively mentors Ph.D. students and has established collaborations with Google, Microsoft Research, IBM Research, Adobe, Verizon, and J.P. Morgan. His research has been supported by NSF, Google Research Scholar Program, AnalytiXIN Initiative, Yahoo! InMind project, and J.P. Morgan. He is currently recruiting Ph.D. students and undergraduate researchers for his SaNDwich Lab, which focuses on developing interactive systems to empower individuals to create, configure, and extend AI-powered computing systems.

• Human-Computer Interaction
• Artificial Intelligence
• Machine Learning
• +6 more

Prof. Anya Belz is Full Professor of Computer Science at Dublin City University's School of Computing and Science Lead at ADAPT Research Centre. A leading NLP researcher with PhD-level expertise, she specializes in natural language generation, evaluation methodologies, and multimodal systems. Recipient of multiple best paper awards and NAACL Test of Time Award nomination. Research innovations include foundational work on statistical language generation (deployed in weather forecasting systems), comparative evaluation frameworks, vision-language integration, and reproducibility quantification. Current EPSRC-funded ReproHum project coordinates 20 global labs studying evaluation consistency. Achievements : Developed industry-deployed generation systems for accessibility applications Pioneered cross-modal alignment techniques for image description Authored 100+ publications spanning generation, evaluation, and reproducibility

• Natural Language Processing
• Natural Language Generation
• Machine Learning
• +4 more

Kyle Treiber is a University Professor in Neurocriminology at the Institute of Criminology, University of Cambridge , with a focus on integrating psychological, neuroscientific, and criminological theories to explain criminal behavior. She serves as Deputy Director of the Peterborough Adolescent and Young Adult Development Study (PADS+) and has developed its neurocognitive dimensions and theoretical foundation, Situational Action Theory (SAT) . Education: BS in Psychology (University of North Carolina at Chapel Hill, 2001, Phi Beta Kappa), MPhil (2003), and PhD (2008) in Criminology (University of Cambridge). Leadership: Director of Criminological Research Programmes (2016–2019), Editor-in-Chief of the European Journal of Criminology , and member of the European Society of Criminology Executive Board. Her research examines how neurocognitive machinery (e.g., prefrontal brain functioning, self-control) and social environments interact to shape crime propensities. She specializes in multi-method longitudinal studies, dual process models of decision-making, and cross-comparative research grounded in SAT. Key themes include: Neurocognitive and moral decision-making in criminal behavior Gene-environment interactions in crime causation Space-time budgets and criminogenic environments Policy implications of integrated biosocial frameworks Recent publications highlight SAT’s application to diverse contexts like corruption , intimate partner abuse during the pandemic , and gender gaps in juvenile crime . She emphasizes refining theoretical models through empirical testing and advancing analytical criminology. Awards: Lopez-Rey Graduate Prize (2008), Nigel Walker Prize (2008). Dr. Treiber contributes to teaching programs in criminological theory, research methods, and neurocriminology. She leads the Centre for Analytic Criminology and collaborates on international comparative studies of crime causation.

• Neurocriminology
• Situational Action Theory
• Developmental Criminology
• +7 more

Bruce W. Smith is an Associate Professor at the University of New Mexico, College of Arts and Sciences, Department of Psychology. His research focuses on resilience , mindfulness interventions , and positive psychology with applications in health and stress management. Ph.D., Arizona State University (2002) Director, The Phoenix Lab Email: bwsmith@unm.edu Smith's research investigates how individuals bounce back from stress and adversity, including through mindfulness , positive psychology , and narrative-based approaches like the "hero’s journey". He developed the Brief Resilience Scale , widely used in stress and health research. His work spans health psychology, examining stress responses in chronic illness (cancer, cardiovascular disease) and emergency responders (firefighters). He has also explored mindfulness-based adaptations for Latino communities and positive psychology classes that improve student well-being. Smith teaches courses in Health Psychology , Positive Psychology , and Psychology Teaching Practicum . Current graduate students in his lab include Kaitlyn Schodt and Naila deCruz-Dixon . He is not accepting new students for Fall 2025 or 2024. Key themes across his publications (2008-2023) include: Resilience measurement and applications Mindfulness in stress reduction Positive psychology interventions Cultural adaptations for mental health His work emphasizes practical applications in both clinical settings and educational environments , with a focus on undergraduate well-being and trauma-informed approaches to personal growth.

• Clinical Psychology
• Positive Psychology
• Resilience and Thriving
• +3 more

Hiroshi Ishikawa is a Professor in the Department of Computer Science and Engineering at Waseda University's Faculty of Science and Engineering. He also serves as a Visiting Professor at the National Institute of Informatics since 2016. Previously, he held positions at Nagoya City University from 2004-2010 as Assistant Professor, Associate Professor, and Professor. His academic journey includes being a JST PRESTO Researcher from 2009-2013 and an Associate Research Scientist at New York University's Courant Institute of Mathematical Sciences from 2000-2001. Ph.D. in Computer Science, New York University (2000) Master of Science, Kyoto University Bachelor's degree in Mathematics, Kyoto University Faculty of Science (1991) Hiroshi Ishikawa's research spans perceptual information processing, computer vision, artificial intelligence, deep learning, and discrete optimization. His work focuses on developing algorithms for image restoration, segmentation, and understanding, with significant contributions to energy minimization techniques in computer vision. He has pioneered approaches in sketch simplification, medical image segmentation, and higher-order graph cuts. His research bridges theoretical advances in mathematical optimization with practical applications in medical imaging, computer graphics, and consumer electronics. Ishikawa's recent publications demonstrate a strong focus on leveraging deep learning for image enhancement and understanding. His work spans super-resolution techniques, colorization methods, human avatar generation, and medical image analysis. A notable trend is the increasing integration of attention mechanisms and generative models to solve complex vision problems, with growing emphasis on real-world applications in medical imaging and computer graphics. His research group consistently produces high-impact work that appears in top-tier computer vision conferences. 75th Annual IEICE Best Paper Award (2019) Innovative Technologies 2016 Special Prize for Culture (Ministry of Economy, Trade and Industry) MIRU Nagao Award (Best Paper Award) (2009) Young Author Award (IEEE Computer Society Japan Chapter, 2006) MIRU2006 Excellent Paper Award (2006) Harold Grad Memorial Prize (Courant Institute of Mathematical Sciences, NYU, 2000) As a professor at Waseda University, Ishikawa has mentored numerous students who have become active researchers in computer vision, including Yuya Masuda, Edgar Simo-Serra, and Satoshi Iizuka. His research has been supported by various grants, including JST PRESTO funding from 2009-2013. He has served on editorial boards for prestigious journals including IEEE Transactions on Pattern Analysis and Machine Intelligence and has held leadership roles in major computer vision conferences such as ICCV, CVPR, and ACCV. Ishikawa leads a vibrant research group at Waseda University focused on computer vision and image processing. His laboratory collaborates extensively with researchers at Nagoya City University, National Institute of Informatics, and international institutions. The group maintains strong connections with industry partners, particularly in medical imaging and consumer electronics sectors, translating theoretical advances into practical applications.

• Perceptual information processing
• Computer Vision
• Artificial Intelligence
• +3 more

Hannes Zacher is a Professor of Work and Organizational Psychology at Leipzig University's Wilhelm Wundt Institute of Psychology. He previously held academic positions at Queensland University of Technology (Australia) and the University of Groningen (Netherlands). His research focuses on occupational health, proactive employee behavior, aging in the workplace, and sustainable organizational practices. He has been awarded grants from institutions like the German Science Foundation (DFG) and the Volkswagen Foundation. Zacher earned his Ph.D. in Psychology from Justus-Liebig-University Gießen in 2009, following a Diploma (equivalent to B.Sc./M.Sc.) in Psychology from the Technical University of Braunschweig (2000–2006). His research interests include occupational health and well-being, proactive and adaptive employee behavior, aging at work and career development, and environmentally sustainable behavior in organizations. He employs methodologies such as longitudinal surveys, experience sampling, and experiments. Key themes in his work address the interplay between work environments and employee well-being, with a focus on fostering sustainable practices and mitigating age-related challenges in the workplace. Zacher leads projects such as the Centre for Digital Work and studies like 'The Role of Work in the Development of Civilization Diseases.' His publications span topics from green workplace behavior to leadership dynamics during crises. He has no listed scientific awards but has secured significant grant funding for his research. Advising and grant details reflect his commitment to impactful research, though specific student names are not provided. His lab and team efforts emphasize translating psychological insights into organizational practices for sustainability and employee well-being.

• Work and Organizational Psychology
• Occupational Health and Well-being
• Proactive Employee Behavior
• +3 more

Adam Finkelstein is a Professor in the Department of Computer Science at Princeton University, where he has been a faculty member since 1997. He holds a PhD and Master's in Computer Science from the University of Washington and a dual degree in Physics and Computer Science from Swarthmore College. Finkelstein is renowned for his interdisciplinary work at the intersection of computer graphics, audio processing, and machine learning, and he co-organized the Art of Science exhibition at Princeton. Education: PhD, Computer Science, University of Washington MS, Computer Science, University of Washington BA, Physics and Computer Science, Swarthmore College His research spans audio processing (e.g., speech enhancement, voice conversion, audio metrics), computer graphics (e.g., line drawing algorithms, stylized rendering, image manipulation), and machine learning (e.g., self-supervised learning, differentiable programming). His work often bridges technical and creative domains, exemplified by collaborations at Pixar and Adobe Creative Technologies Lab. Recent publications highlight advancements in audio super-resolution and voice conversion using deep learning frameworks, as well as stylized line rendering for animated 3D models. His contributions to perceptual audio metrics and shader optimization further underscore his impact on human-centric computational systems. Scientific Awards: NSF CAREER Award Alfred P. Sloan Fellowship Fellow of the Association for Computing Machinery (ACM) Finkelstein has secured foundational grants for his research and actively mentors students, though no specific advisees are listed. He also explores collaborative tools for internet music performance, reflecting his broader interest in distributed systems and user interfaces.

• Computer Science
• Audio Processing
• Image Processing
• +3 more

Paul Taele is an Instructional Assistant Professor and Deputy Lab Director in the Sketch Recognition Lab at Texas A&M University's Department of Computer Science & Engineering. He holds a Ph.D. (2019), M.S. (2010), and dual B.S. degrees in Computer Science and Mathematics from the University of Texas at Austin (2006). His research focuses on sketch recognition, haptics, and intelligent interfaces for education and accessibility, with notable work in mid-air gesture recognition, educational sketching tools, and assistive technologies for disabilities. He has contributed to projects like Kanji Workbook , Hashigo , and HaptiMoto , and has published over 50 peer-reviewed articles across venues like CHI, IUI, and AAAI. Taele has received awards including the NSF Student Travel Grant (2014) and Ford Foundation Honorable Mention (2015). He teaches courses in capstone design, programming, and sketch recognition, and mentors students across all academic levels through strict eligibility criteria for research collaborations. Education : Ph.D. Computer Science, Texas A&M University (2019) M.S. Computer Science, Texas A&M University (2010) B.S. Computer Science & Mathematics, University of Texas at Austin (2006) Concentration in Mandarin Chinese, National Chengchi University (2007) Research Interests : Taele's work bridges HCI and AI to create accessible educational interfaces. His projects emphasize: Sketch Recognition : Developing algorithms for mid-air gestures, children's developmental assessments, and language learning Accessibility : Haptic systems for visually impaired learners and algebra education Educational Tech : Intelligent tutoring systems for music, math, and East Asian languages Awards & Grants : EAAI-20 Travel Grant (2020) Ford Foundation Dissertation Honorable Mention (2015) NSF East Asia-Pacific Summer Institutes (2013, 2012) Royce E. Wisenbaker Fellowship (2009) Lab & Teams : Director of the Sketch Recognition Lab (SRL) and collaborator with global institutions like Singapore Management University and National Taiwan University. Active in organizing workshops like SketchRec at IUI conferences.

• Sketch Recognition
• Human-Computer Interaction (HCI)
• Artificial Intelligence
• +5 more

Yoel Inbar is an Associate Professor at the University of Toronto, affiliated with the Department of Psychology and the Morality, Affect, and Politics (MAP) Lab. His research explores the intersection of moral intuitions, emotions, and political/social beliefs, with a focus on disgust sensitivity and its implications. He also investigates public acceptance of emerging technologies like genetic engineering. Contact: yoel.inbar@utoronto.ca . PhD, Cornell University BA, University of California at Berkeley His research spans moral psychology, political ideology, and behavioral responses to technological innovation. Recent studies employ natural language processing to analyze morality in real-world contexts, such as political discourse and environmental attitudes. The MAP Lab emphasizes interdisciplinary approaches, integrating psychology, behavioral economics, and computational methods to study moral decision-making and its societal consequences. Alumni from the lab include researchers now at institutions like UC Berkeley, University of the Fraser Valley, and Cornell University, reflecting his mentorship of advanced psychological and behavioral science scholars.

• Social Psychology
• Moral Psychology
• Political Ideology
• +3 more