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.
Andrés Cuervo-Rubio is a Part-time Lecturer at Parsons School of Design, The New School. They are an interdisciplinary artist, programmer, and HCI researcher based in Brooklyn. As a co-founder of Folk Computer, a research consultancy focused on tangible computing hardware/software and programming languages, they explore accessible interfaces and paper-based interaction systems. They advise the W3C Immersive Web Working Group (WebAR/VR/XR APIs) and have spoken at global JavaScript conferences since 2017. Education: BA in Computer Science, Oberlin College (2017) BA in Creative Writing, Oberlin College (2017) Research Interests: Focuses on material-based interaction design, bridging physical/digital systems through accessible technologies. Current work emphasizes tangible computing interfaces and inclusive design practices. Active in developing educational frameworks for dynamic content creation in design curricula. Teaching: Recently taught Core 1: Interaction (PUCD 2035) and Core 2: Interaction Studio (PUCD 2125). Upcoming courses include CD Foundations: Interaction (PSAM 1028) in Fall 2025 and CD Studio: Dynamic Content (PSAM 2090) in Spring 2026. Professional Engagement: Serves as technical advisor for immersive web standards and collaborates with industry on accessible XR solutions. Co-leads workshops on physical computing pedagogy.
Ari Holtzman is an Assistant Professor of Computer Science at the University of Chicago. His research spans dialogue systems, text generation, and foundational AI methodologies, including the development of Nucleus Sampling and contributions to the Amazon Alexa Prize. He holds an interdisciplinary degree from NYU in Computer Science and Philosophy of Language, and is nearing completion of his PhD at the University of Washington. Research interests include generative models, alignment challenges in LLMs, evaluation metrics like CLIPScore, and model efficiency techniques such as Qlora finetuning. His work bridges theoretical insights with practical applications, emphasizing both technical innovation and ethical considerations in AI. Key awards include the 2017 Amazon Alexa Prize and Phi Beta Kappa honors at NYU. His recent publications focus on benchmarking frameworks, cache optimization for large models, and understanding model limitations through AbsenceBench. Research contributions extend to multimodal systems, computational creativity, and machine unlearning protocols.
Julian McAuley is a Professor in the Department of Computer Science and Engineering at the University of California, San Diego's Jacobs School of Engineering. His research spans recommender systems, machine learning, natural language processing, music information retrieval, and multimodal learning. He maintains an active research group with numerous PhD students and postdocs working on cutting-edge AI problems. His research interests focus on developing advanced algorithms for personalized recommendation systems, with particular emphasis on sequential recommendation, multimodal learning, and integrating large language models with traditional recommendation approaches. His work bridges the gap between theoretical machine learning and practical applications across multiple domains including e-commerce, music, and healthcare. McAuley has published extensively in top-tier conferences including NeurIPS, ICML, KDD, SIGIR, and ACL, with his most recent work exploring the intersection of large language models and recommendation systems. His publications reveal a strong trend toward multimodal approaches that combine text, vision, and audio for more comprehensive understanding and recommendation. He has received significant research funding from major technology companies including Google, Amazon, Facebook, Adobe, and Samsung, as well as government agencies like the National Science Foundation and Department of Defense. His work has practical applications across multiple industries, with a focus on improving user experience through better personalization. McAuley advises numerous PhD students who have gone on to successful careers at leading technology companies and academic institutions. His former students include Wang-Cheng Kang and Jianmo Ni at Google DeepMind, Chris Donahue and Zachary Lipton as assistant professors at CMU, and Ruining He at Google Deepmind.
Ming Yin is an Associate Professor in the Department of Computer Science at Purdue University. Her research bridges human-computer interaction, applied artificial intelligence, computational social science, and behavioral sciences. She focuses on leveraging human behavior data to design intelligent systems that balance machine efficiency with human understanding, trust, and engagement. Education : PhD in Computer Science (Harvard University, 2017), B.E. in Computer Software (Tsinghua University, 2011) Previous Roles : Postdoctoral researcher at Microsoft Research New York City (2017–2018) Teaching : Courses on AI, Human-AI Interaction, Data Mining, and Human-Centered Computing Research Interests center on social computing, crowdsourcing, human-AI interaction, and ethical AI. She employs experimental and computational methods to study how human behavior can improve AI systems' design, fairness, and user trust. Her work has significant implications for gig economy platforms, decision support systems, and algorithmic accountability. Scientific Contributions include over 15 recent articles in top venues like CHI, IJCAI, and ACL. These works explore topics such as LLM-driven trust calibration, adversarial social influence, and ethical AI design. Her research has been recognized with the NSF CAREER Award Siebel Scholar (Class of 2017) Multiple Best Paper and Honorable Mention Awards at CHI, CSCW, and HCOMP Teaching Expertise spans courses like Introduction to Artificial Intelligence (CS 471), Human-AI Interaction (CS 592-HAI), and Data Mining (CS 573). She emphasizes project-based learning and designing systems for real-world problems, such as "learning in a new era" in her 2025 HCI course.
Matthew Kay is an Associate Professor in the Department of Communication Studies at Northwestern University's School of Communication, with a secondary appointment in Computer Science. He serves as Co-Director of Graduate Studies for the PhD in Technology and Social Behavior program. His research focuses on human-computer interaction and information visualization, specializing in uncertainty communication, usable statistics, and personal informatics. He employs mixed-method approaches including behavioral analysis, interactive system development, and visualization technique evaluation to address real-world data interpretation challenges. Analysis of his recent publications reveals dominant themes in visualization literacy development, uncertainty representation for decision-making, and health informatics applications. His work consistently bridges theoretical frameworks with practical implementations, particularly in educational assessment tools and election forecast visualizations. Professor Kay co-directs the Midwest Uncertainty Collective (MU collective), a research group advancing uncertainty communication methodologies. Previously faculty at the University of Michigan School of Information, he maintains active contributions to visualization tool development including the ggdist R package for uncertainty visualization.
Takako Fujioka is an Associate Professor of Music at Stanford University, affiliated with the Center for Computer Research in Music and Acoustics (CCRMA). Her research focuses on the neural mechanisms underlying auditory perception, auditory-motor coupling, and music-supported therapy for neurorehabilitation. She holds a Ph.D. in Physiology from the Graduate University for Advanced Studies, Japan, and M.Sc./B.Eng. degrees in Electrical Engineering from Waseda University. Her work combines neurophysiological techniques such as MEG and EEG to study brain plasticity in development, aging, and stroke recovery. Notable contributions include investigating how music influences motor and cognitive recovery in stroke patients, as well as exploring the neural basis of musical perception through rhythmic synchronization and pitch discrimination studies. Supported by awards from the Canadian Institutes of Health Research during her postdoctoral work at the Rotman Research Institute, her research bridges clinical neuroscience and music cognition. Dr. Fujioka’s expertise spans auditory neuroscience, neurorehabilitation, and technology-assisted music therapy. She has pioneered studies on tactile mapping for cochlear implant users and networked music performance systems, emphasizing cross-modal perception and human-technology interaction. Her findings contribute to both theoretical understanding of auditory processing and practical applications in medical and educational settings. Awards: Canadian Institutes of Health Research Awards (postdoctoral phase) Labs/Teams: CCRMA, Stanford Music Perception Laboratory, Rotman Research Institute collaborations Key Themes: Neuroplasticity, Music-Mediated Rehabilitation, Auditory-Motor Integration, Multisensory Processing Her recent work examines aging-related changes in binaural hearing and the role of beta/gamma oscillations in rhythmic processing. She advocates for translational research that connects neural mechanisms with real-world therapeutic interventions.
Lorraine (Xiang) Li is an Assistant Professor in the Department of Computer Science at the University of Pittsburgh’s School of Computing and Information (SCI). Her research focuses on the intersection of natural language processing, commonsense reasoning, knowledge representation, and machine learning, particularly in designing probabilistic models and evaluation methods for implicit commonsense knowledge in language. Li holds a PhD from the University of Massachusetts, Amherst, and previously worked as a young investigator with the Mosaic team at AI2. She has an M.S. in Computer Science from the University of Chicago, where she conducted research at TTIC. Her work emphasizes advancing AI’s ability to reason contextually and generate robust, human-like understanding through probabilistic frameworks. Key research themes include bias detection in reasoning models, iterative model editing, domain adaptation with LLMs, and evaluating commonsense through probabilistic measures. Her recent publications explore challenges like confirmation bias in chain-of-thought reasoning and geographical robustness in object recognition. Li actively contributes to the NLP community, serving on program committees for ACL, EMNLP, NAACL, and ARR. Though no formal awards are listed, her prolific publication record reflects her impact in AI research. She currently leads research in procedural knowledge models (e.g., Plasma) and long-tail knowledge generation, advancing foundational AI methodologies.
Kyle Bellucci Johanson serves as a Visiting Critic in Cornell University's College of Architecture, Art, and Planning, Department of Art. Holding an MFA from California Institute of the Arts and a BA in Art and Reconciliation Studies from Bethel University, he merges artistic practice with critical theory through performance architecture and collaborative media. Whitney Independent Study Program (2022–23) Founding fellow at land's edge free school (Los Angeles) Teaching experience at SAIC, UIC, CUNY, and Cooper Union His research investigates: Power structures through spatial interventions Critical theory applications in art practice Post-capitalist imaginaries Hauntology and historical materialism Transdisciplinary approaches to social critique Project trends reveal: Reinterpretation of Soviet design principles Investigation of worker identity in post-industrial contexts Temporal and spatial dislocation in artistic practice Monument critique through performative methods Quantum theory-inspired architectural concepts Reimagining of common spaces as political sites Scientific awards include: Creative Research Grant (2025) Whitney ISP participation (2022–23) Automata Studio Residency (2022) Artists Run Chicago Grant (2021) BOLT Residency (2020–21) Through projects like KLUB WRKR —a nomadic workers' club reimagined for the gig economy—and table (2018–2022), a Chicago-based experimental space for artistic practice, he interrogates institutional frameworks while fostering community through discursive meals and collaborative exhibitions.
Alexey Vladimirovich Vdovin is a Professor and Senior Research Fellow at the National Research University Higher School of Economics (HSE), working within the Faculty of Humanities and School of Philological Sciences. He began his tenure at HSE in 2012 and has accumulated 15 years of scientific and teaching experience. His academic journey includes a Doctor of Philology degree from HSE (2023), a PhD from the University of Tartu (2011), and his initial degree in 'Russian language and literature' from Vyatka State Humanitarian University (2007). He has held significant roles including Deputy Dean for Science at the Faculty of Humanities (2018-2020) and serves on numerous academic councils and committees. Vdovin's educational background demonstrates both depth and international perspective. After completing his undergraduate studies at Vyatka State Humanitarian University in 2007, he pursued doctoral studies at the University of Tartu, where he earned his PhD in 2011 with a dissertation on 'The concept of 'chapter of literature' in Russian criticism of the 1830-1860s.' His academic development has been enriched by numerous international experiences, including visiting researcher positions at Selwyn College, University of Cambridge (2019), Jordan Center at New York University (2017), and multiple research stays at Humboldt University in Berlin through the Aurora Erasmus Mundus program. Professor Vdovin's research focuses on Russian intellectual history, the history of ideas, the Russian Empire, Russian literature of the 19th century, and nationalism studies. His work particularly examines the formation of the Russian literary canon, representations of peasants in literature, and the relationship between literature and society. He has authored approximately 80 articles and 4 monographs on 19th-century Russian literature, culture, and criticism, with works on major figures like Turgenev, Dostoevsky, Tolstoy, Goncharov, Belinsky, Chernyshevsky, Dobrolyubov, and Nekrasov. His recent book 'Monsters at the Threshold: Dracula, Frankenstein, Viy and Other Literary Monsters' (2024) demonstrates his expanding interest in literary archetypes and cultural phenomena. Vdovin has received numerous awards and recognitions for his scholarly work, including the Moscow Government Prize for young scientists (2017), multiple 'Best Teacher' awards (2013-2015, 2017-2024), and recognition as a winner of HSE's competition for best Russian-language scientific works (2022, 2024). He has also received various letters of gratitude from HSE administration, the Faculty of Humanities, and the School of Philology for his contributions to academic life. As an advisor, Vdovin has supervised numerous student research projects, including Smirnova T.V.'s 2014 master's thesis on 'Representation of 'Russianness' and 'Otherness' in Russian essays of the 1840s.' He has also served as a curator for HSE's Personnel Reserve Program at the School of Philological Sciences and has been actively involved in dissertation councils. His research has been supported by significant grants, including a 2024-2025 Russian Science Foundation grant 'The Genre of 'Peasant Life Story' in Russian Literature Before 1861: Poetics, Plots, Socio-Cultural Functions' (No 24-28-00184) and a 2018-2020 RFBR grant on 'State and Literary Institutions: From Peter I's Reforms to the 'Great Reforms.' Professor Vdovin is actively engaged in academic communities beyond HSE, serving as editor-in-chief of the HSE preprint series 'Literary Studies' and participating in the Big Project 'Literature and Society: An Experience of Sociocultural Description.' He is also involved in public scholarship, frequently giving public lectures through platforms like 'Arzamas,' 'Postnauka,' and 'Stradarium,' and appearing on the 'Observer' television program (Culture channel). Since 2015, he has been a mentor at Maya Kucherskaya's Creative Writing School, bridging academic scholarship with creative practice.
Prof. Yan Lianke (born 1958) is a renowned contemporary Chinese writer and academic. He currently holds the IAS Sin Wai Kin Professor of Chinese Culture at Hong Kong University of Science and Technology and serves as Professor at the School of Liberal Arts of Renmin University of China. His work spans novels, short stories, and literary theory, often exploring political, historical, and social themes through a critical lens. Education: BA in Political Education (Henan University, 1985), MA in Literature (PLA Academy of Art, 1991) Awards: Lu Xun Literature Prizes, Franz Kafka Prize, Newman Prize, and international recognition for his humanistic and socially conscious writing Yan’s research and writing focus on the intersection of literature, memory, and truth-telling in authoritarian contexts. His theoretical work, such as the 2020 lecture On Memory , critiques the erasure of personal and collective recollection in modern China. His novels, including Four Books and Dreams of Ding Village , are celebrated for their allegorical depth and spiritual realism. Scientific awards and honors include: 2014 Franz Kafka Prize (first Chinese recipient) 2017 Dream of the Red Chamber Award 2021 Newman Prize for Chinese Literature 2022 Lee Hochul Prize for Peace 2024 Nebula Award for Contribution to Global Chinese Literature Yan’s teaching and creative writing programs at HKUST and Renmin University emphasize the ethical role of literature in documenting human experiences and challenging historical amnesia. His work has been translated into over 30 languages, with more than 150 foreign publications.
Sophie Whitehouse is a Lecturer in Marketing (Education) at King's Business School, King's College London. She holds a PhD in Marketing, an MA in English Language and Linguistics, and a BA in Management with Marketing from the University of Leicester. She is a Fellow of the Higher Education Academy and has been teaching since 2013. PhD in Marketing, University of Leicester MA in English Language and Linguistics, University of Leicester BA in Management with Marketing, University of Leicester Sophie's research centers on marketing in the creative and cultural industries, especially music. She explores consumer culture, authenticity, nostalgia, and the materiality of consumption in a digital age. Her work employs qualitative methodologies and has examined why consumers remain committed to physical formats like vinyl records despite the dominance of digital streaming. Her recent publications reveal a consistent focus on the intersection of marketing, culture, and emotion. She investigates how nostalgia shapes consumption, how record artwork fosters cultural identity, and how pedagogical tools like crib sheets affect student well-being. Her upcoming work extends into collaborative arts research and societal inclusion in higher education. Her scientific contributions have been recognized with the Elsevier Peer Recommendation Prize at the University of Leicester’s Festival of Postgraduate Research. Elsevier Peer Recommendation Prize, University of Leicester’s Festival of Postgraduate Research Sophie has extensive experience supervising undergraduate, Master’s, and MBA dissertations. She is currently open to supervising PhD students whose projects align with her interests in marketing and nostalgia, consumer culture, and the creative industries. While no specific grants are mentioned, her research output and invited talks indicate active scholarly engagement and external collaboration. Sophie is involved in academic events and roundtables such as 'La Pensée Artistique: Artistic Thinking in Consumer Research' and 'The Future of Higher Education,' indicating her integration into research networks and thought leadership in her domain.
Ranjay Krishna is an Assistant Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington, where he co-directs the RAIVN lab and leads the computer vision team at the Allen Institute for AI (Ai2). His research intersects computer vision , natural language processing , robotics , and human-computer interaction . PhD in Computer Science from Stanford University (2021) Bachelor's and Master's degrees from Stanford and Cornell His work has received best paper , outstanding paper , and orals at top conferences like CVPR, ACL, CSCW, NeurIPS, UIST, and ECCV. Media outlets including Science , Forbes , and PBS NOVA have covered his research. He has been supported by grants from Google , Apple , NFS , and others. Ranjay advises a diverse group of 15 PhD and postdoctoral researchers , including Jieyu Zhang, Benlin Liu, and Cheng-Yu Hsieh. His teams have developed benchmarks like MemoryBench and The Colosseum , and his PathFinder framework achieved 74% accuracy in skin melanoma diagnosis—surpassing human experts by 9%. Notable contributions include: Perception Tokens for visual reasoning in MLMs SAM2Act for robotic manipulation with memory Synthetic Visual Genome dataset with 5.6M relationships
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.
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
