Mina Lee is an Assistant Professor in Computer Science at the University of Chicago, affiliated with the Data Science Institute and Cognitive Science. Her research focuses on 'Writing with AI,' exploring how AI transforms writing processes, content, and identities. She designs AI writing assistants and evaluates human-AI collaboration through user studies and experiments, addressing ethical implications like authorship norms and educational impacts. Education: Ph.D. in Computer Science from Stanford University (2023), advised by Percy Liang. B.S. in Computer Science from Korea University (2016). Postdoctoral research at Microsoft Research's Computational Social Science group (2023–2024). Research interests span Human-Computer Interaction (HCI), NLP, and computational social science. She co-founded workshops on Intelligent Writing Assistants and Human-centered Evaluation of Language Models. Notable awards include MIT Technology Review's Innovators Under 35 Korea (2022) and a Best Paper Award at GPCE 2016. Her work has been published in top venues like CHI, ACL, NeurIPS, and Nature Human Behavior. She advises PhD students on AI-assisted writing, cognitive augmentation, and safe generative models. Current lab projects include designing explainable AI tools and studying AI disclosure norms in writing.
Gail E. Kaiser is a Professor of Computer Science and the Director of the Programming Systems Laboratory (PSL) in the Computer Science Department at Columbia University. She has been with Columbia University since 1985, becoming a full Professor in 1998. Prof. Kaiser's research spans software engineering, program analysis, software testing, and software security, with recent focus on addressing challenges in AI/ML systems testing and security. Prof. Kaiser received her PhD in Computer Science from Carnegie Mellon University in 1985 and her ScB in Computer Science and Engineering from MIT in 1979. Her dissertation at CMU was titled "Semantics for Structure Editing Environments" under advisor Nico Habermann, and at MIT she completed "Automatic Extension of an Augmented Transition Network Grammar for Morse Code Conversations" under advisor Al Vezza. Prof. Kaiser's research interests primarily focus on software engineering following a systems building approach, with recent emphasis on static and dynamic program analysis techniques to improve software reliability and security. Since 2005, she has investigated testing "non-testable" programs, particularly in machine learning, data mining, and scientific computing applications where traditional testing oracles are insufficient. She has developed novel techniques and tools for detecting bugs and verifying repairs in complex systems. Concurrently, she has worked on collaboration environments for computational scientists, creating knowledge sharing and domain-aware environments to support scientific workflows. Prof. Kaiser's recent publications demonstrate a strong focus on the intersection of software engineering and artificial intelligence. Her work addresses critical challenges in testing AI systems, code understanding through deep learning, vulnerability detection, and educational tools for computational thinking. There's a clear evolution from traditional software engineering topics toward AI/ML applications, with particular emphasis on metamorphic testing for non-testable systems, code similarity analysis, and educational applications. Prof. Kaiser has received numerous prestigious awards throughout her career: Distinguished Journal Award (10 Years) from 18th IEEE International Conference on Software Testing, Verification and Validation (ICST), April 2025 Best Research Paper Award at 24th IEEE International Conference on Source Code Analysis & Manipulation (SCAM), October 2024 Distinguished Reviewer Awards for ASE 2024 and FSE 2024 ACM SIGSOFT Distinguished Paper Award for "CONCORD: Clone-aware Contrastive Learning for Source Code", July 2023 Best Student Paper Award at ICCE 2021 Multiple ACM SIGSOFT Distinguished Paper Awards dating back to 2014 Presidential Young Investigator in Software Engineering and Software Systems from NSF (1988-1993) Prof. Kaiser has chaired Columbia's doctoral program since 1997 and served on editorial boards including IEEE Internet Computing and as a founding associate editor of ACM Transactions on Software Engineering and Methodology. Her lab has been continuously funded by major agencies including NSF, NIH, DARPA, ONR, NASA, and numerous companies. Current grants include significant NSF funding for secure containers architecture, learning semantics of code for software assurance, and finding semantic security bugs. As Director of the Programming Systems Laboratory (PSL), Prof. Kaiser leads research in software systems, program analysis, and software testing. The lab has developed numerous tools and techniques for software reliability and security, with recent focus on challenges in AI/ML systems. Her work bridges theoretical foundations with practical applications, often resulting in deployable tools that address real-world software engineering challenges.
Andrew Head is an Assistant Professor at the University of Pennsylvania in the Computer and Information Science department. His research focuses on human-computer interaction, programming, and reading, particularly in developing technology for interactive reading and reasoning. He advises PhD students Alyssa Hwang, Hita Kambhamettu, Litao Yan, Jeffrey Tao, and Jessica Shi, and co-leads the Penn Human-Computer Interaction (Penn HCI) group with Danaé Metaxa. His work is published in top venues like ACM CHI, UIST, and ICSE. Research Interests: Andrew's work bridges interactive systems with programming environments, aiming to enhance how scientists and programmers interact with their tools. Key areas include AI-assisted code understanding, math notation accessibility, and medical note interpretation through interactivity. He employs user studies to identify needs and builds interactive systems to address them. Recent Article Trends: His publications emphasize systems-centric HCI approaches, integrating AI into code and document interfaces. Topics span code explanation (e.g., Ivie), property-based testing (e.g., Tyche), math notation augmentation (e.g., FreeForm), and medical informatics (e.g., Explainable Notes). Recent work also explores notebook environments (e.g., Bolt-on, Tyche) and literate programming (e.g., Colaroid). Scientific Awards: Distinguished Paper Award, ICSE 2024 Best Paper Awards at CHI (2024, 2023, 2022, 2019), UIST (2023, 2018), and others. Nominated for Best Paper at CHI 2023 and VL/HCC 2015. Advising & Grants: Andrew advises multiple PhD students and has secured significant grants, including a $1M NSF award for 'Property-based Testing for the People' (2024). His group collaborates with Penn’s MindCORE center and teams like PLClub and PennNLP. Labs & Teams: He co-leads the Penn HCI group, which works closely with other Penn research teams and labs. The group focuses on creating interactive tools that enhance scientific and programming workflows, supported by grants and cross-institutional partnerships.
Rafał Jończyk is an Assistant Professor at the Department of Pragmatics, Faculty of English, Adam Mickiewicz University in Poznań, Poland, where he conducts research at the intersection of psycholinguistics, affective neuroscience, and bilingualism. His work primarily investigates how emotional processing differs between native and second languages using neurophysiological methods, particularly EEG. With a Ph.D. in English Linguistics from Poznań (2015) and postdoctoral experience at Pennsylvania State University, he has established himself as a leading researcher in bilingual emotional processing. His research interests span Affective Neuroscience , Experimental Pragmatics , Psycholinguistics , Bilingualism and Emotion , and the Neurophysiology of Creativity . His methodology heavily relies on EEG to examine language processing, with particular focus on emotional language comprehension and production in bilingual contexts. His work has demonstrated how bilinguals process emotional content differently in their native versus second languages, revealing reduced sensitivity to negative content in the second language. Jończyk's research program has evolved from early work on hemispheric specialization for emotional words to sophisticated EEG studies of emotional anticipation and metaphor processing in bilinguals. His most recent work explores hyperscanning methodologies to study real-time bilingual communication and the neural correlates of creative thinking in bilingual contexts. His publications show a clear progression from foundational studies of emotional word processing to increasingly complex investigations of emotional communication in naturalistic contexts. Cognitive Neuroscience Society Post-doctoral Fellows Award (2018) START scholarship for most talented young Polish scientists (2018) Scholarship from the Minister of Science and Higher Education (2020) Travel Grant Award for International Symposium on Bilingualism (2013) As Principal Investigator, Jończyk leads two major National Science Center projects examining psychophysiological correlates of affective language processing in bilinguals (2016-2018) and neurophysiological correlates of emotional speech production in bilingualism (2021-2025). He also participates in multiple international collaborations including NSF-funded research on divergent thinking in engineering education. His editorial roles include Topic Editor for Brain Sciences and Associate Editor for Applied Psycholinguistics, reflecting his standing in the field. He teaches courses in Psycholinguistics, Emotions in Social Communication, and Creativity and Language at the university level.
Dr. Nienke Smit is an Assistant Professor in the Department of Education at Utrecht University's Faculty of Social and Behavioural Sciences. Her research focuses on scaffolding processes, adaptive teaching, and classroom observational research from a complex dynamic systems perspective. Specializes in teacher-student interaction Expert in adaptive instruction and observational methods Collaborates with Data Science department Develops tools for classroom observation Research interests include language learning and teaching , judgment and decision-making in education , and professional development of teachers . She leads projects like Eye Get It (joint attention in classrooms) and a replication study on adaptive instruction effectiveness. Her work applies dynamic systems theory to second language development and foreign language pedagogy. Recent publications address translanguaging in multilingual classrooms, replication studies , and process-oriented research . She teaches at Utrecht's Graduate School of Teaching and works on initiatives to reduce teacher shortages through improved training programs.
Enamul Hoque Prince is an Associate Professor and Director of the School of Information Technology at York University. He leads the Intelligent Visualization Lab, funded by the Canada Foundation for Innovation (CFI) and Ontario Research Funds (ORF). He holds a PhD in Computer Science from the University of British Columbia and completed postdoctoral work at Stanford University. His research integrates information visualization, human-computer interaction (HCI), and natural language processing (NLP) to address information overload challenges. Dr. Prince's educational background includes a PhD from UBC, an MSc from Memorial University of Newfoundland, and a BSc from Chittagong University of Engineering & Technology. He has conducted research at institutions like Tableau Software and the Qatar Computing Research Institute and serves on committees for top conferences like ACL and IEEE Vis. His work is supported by grants from NSERC, CFI, and others. Research interests focus on NLP-driven visual analytics, user-adaptive visualization, and accessible interfaces. Notable projects include Evizeon (natural language interfaces for visual analytics), ConVisIT (topic modeling for online conversations), and CIDER (concept-based image search). Publications highlight trends in multimodal systems, chart comprehension, and accessibility. Key awards include the NSERC Discovery Grant (2019) and a Best Paper Honorable Mention at DIS 2021. He supervises graduate and undergraduate students in areas like visualization, NLP, and HCI. Labs and collaborations emphasize interdisciplinary approaches, with the Intelligent Visualization Lab advancing tools for data exploration and user-centered design. Teaching includes courses on design principles and information visualization.
Brendan O'Connor is an Associate Professor in the Manning College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst. His research focuses on computational social science and natural language processing (NLP), particularly exploring how social factors influence language technologies and using text analysis to understand societal trends. His work includes studies on racial bias in NLP, political event analysis, and social media linguistics. He holds a PhD in Machine Learning from Carnegie Mellon University (2014) and dual MS/BS in Symbolic Systems from Stanford University (2006). Education: PhD in Machine Learning, Carnegie Mellon University (2014) MS in Symbolic Systems, Stanford University (2006) BS in Symbolic Systems, Stanford University (2006) Research interests span AI ethics, social media analysis, and computational methods for studying language and society. Notably, he investigates racial disparities in NLP systems, linguistic variation in African American English, and event detection in news and social media. His work has been recognized with NSF CAREER and Google Faculty awards, and his research has been cited thousands of times. His lab, the Statistical Social Language Analysis Lab, develops tools for analyzing large-scale text data. He is affiliated with the Center for Data Science, Center for Intelligent Information Retrieval, and Computational Social Science Institute. Recent projects include analyzing global news coverage of critical events and developing frameworks for zero-shot argument explication. Awards and Honors: NSF CAREER Award Google Faculty Research Award Best Paper Award Advising and Grants: O'Connor has advised projects on social media polling representativeness and demographic analysis. His grants include collaborative research on sociopolitical event extraction and bias mitigation in AI systems. He has also contributed to platforms like Rookie for news archive exploration and ezCoref for coreference resolution. Labs/Teams: Leads the Statistical Social Language Analysis Lab and collaborates with the UMass NLP Group and Harvard Institute for Quantitative Social Science. His work bridges NLP with social science methodologies, emphasizing transparency in algorithms and causal inference using text data.
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.
Roger Luckhurst is Professor of Modern Literature and currently holds the prestigious Geoffrey Tillotson Chair of Nineteenth Century Studies at Birkbeck College, University of London. A leading scholar in Gothic literature, science fiction, and trauma studies, he has been affiliated with Birkbeck for over 25 years, contributing significantly to interdisciplinary literary and cultural studies. Education and Career Trajectory: 2020-present: Geoffrey Tillotson Chair of Nineteenth Century Studies, Birkbeck College 2008-2020: Professor of Modern and Contemporary Literature, Birkbeck College 2004-2008: Senior Lecturer, Birkbeck College 1994-2004: Lecturer, Birkbeck College 1992-1994: Lecturer, University of Hull Research Interests and Scholarly Contributions: Luckhurst's research spans multiple interconnected fields, establishing him as a preeminent voice in literary and cultural studies. His work on late 19th century English literature examines the intersections of Victorian culture with emerging scientific discourses. His expertise in science fiction studies encompasses both literary analysis and cultural theory, exploring how speculative fiction reflects and shapes contemporary anxieties. In Gothic studies , he investigates the persistence of Gothic aesthetics and themes across different media and historical periods. His groundbreaking work in trauma studies has contributed significantly to understanding how literature and culture process collective trauma. Publications and Scholarly Impact: His extensive publication record demonstrates a remarkable breadth of scholarly inquiry. From his early work on J.G. Ballard to his recent comprehensive study of Gothic culture, Luckhurst has consistently produced influential scholarship. His books have been translated into multiple languages including French, Japanese, Turkish, and German, indicating significant international impact. His forthcoming The Gothic: An Illustrated History (2021) promises to be a definitive work in the field. Honors and Awards: 2009: Visiting Research Fellow, University of Birmingham 2009: Visiting Research Fellow, Flemish Academic Centre for Science and the Arts (VLAC), Brussels January-June 2011: AHRC Fellowship, Birkbeck College Spring 2016: Mellon Distinguished Visiting Professor, Department of English, Columbia University, New York Public Engagement and Media Presence: Beyond academia, Luckhurst has demonstrated exceptional commitment to public scholarship. He has served as a broadcaster for BBC radio, bringing literary criticism to wider audiences. His journalism has appeared in leading British newspapers, bridging the gap between academic research and public discourse. This dual role as academic and public intellectual exemplifies Birkbeck's tradition of making scholarship accessible to broader communities. Interdisciplinary Approach and Institutional Contributions: At Birkbeck College, Luckhurst has been instrumental in fostering the institution's renowned culture of interdisciplinary studies. His work seamlessly integrates literary analysis with cultural theory, film studies, architectural history, and scientific discourse. This approach has influenced generations of students and scholars, establishing Birkbeck as a leading center for innovative literary and cultural research.
Raquel Fernández is Full Professor of Computational Linguistics and Dialogue Systems at the University of Amsterdam, where she leads the Dialogue Modelling Group at the Institute for Logic, Language & Computation (ILLC). As Vice-Director for Research at ILLC and a Fellow of the ELLIS Society, she bridges computational linguistics, cognitive science, and artificial intelligence through her research on language use in multimodal and conversational contexts. PhD in Computational Linguistics from King's College London Prior research positions at University of Potsdam and Stanford University's CSLI Her work explores how cognitive constraints, social interaction, and perception shape language use, with a focus on: Visually-grounded language processing Multimodal dialogue modeling Model uncertainty and calibration Language grounding in multimodal data Language learning and semantic change Dialogue reference resolution Recent publications analyze multimodal reasoning limitations, cross-lingual knowledge consistency, and uncertainty modeling in dialogue systems. She has received multiple accolades including an ERC Consolidator Grant , NWO VENI/VIDI/Aspasia fellowships , and EMNLP/GenBench awards . Outstanding Paper Award (EMNLP 2023) Best Data Award (GenBench Workshop 2023) ELLIS Society Fellow ERC Consolidator Grant #819455 recipient NWO VENI/VIDI/Aspasia awardee As a leader in academic service, she serves on the SIGDAT Executive Committee and chairs multiple conference committees. Her lab develops models for multimodal dialogue, visual storytelling, and grounded language understanding.
Prof. Dr.-Ing. Rüdiger Daub serves as Professor and Chair of Production Engineering and Energy Storage Systems at the Technical University of Munich (TUM), operating within the Department of Mechanical Engineering. His leadership encompasses research direction, academic supervision, and strategic development of battery production technologies at TUM's Garching campus (Boltzmannstr. 15), with active industry collaborations driving innovation in sustainable manufacturing. Daub's research program pioneers advanced production methodologies for lithium-ion and solid-state batteries, focusing on electrode manufacturing, electrolyte filling, and cell assembly processes. His work investigates critical parameter interdependencies affecting battery safety and performance, developing inline monitoring systems and digital twin technologies for real-time process optimization. Key contributions include moisture control in electrode production, electrochemo-mechanical characterization of solid-state systems, and robotics solutions for deformable object assembly, all integrated with machine learning for quality assurance in industrial settings. Analysis of his 2023-2025 publications reveals a dominant research trajectory toward solving production bottlenecks in next-generation energy storage. The work demonstrates increasing integration of computational modeling with empirical validation, particularly in solid-state battery manufacturing and high-voltage electrolyte systems. A notable trend is the cross-pollination of robotics, computer vision, and uncertainty quantification techniques to address complex assembly challenges and distribution shifts in quality monitoring, reflecting industry's urgent need for adaptable, data-driven production systems. Leading TUM's specialized laboratories for battery cell production, Daub's team maintains comprehensive facilities for electrode calendering, electrolyte filling, and cell assembly with integrated tracking and tracing capabilities. The research infrastructure supports collaborative projects with automotive OEMs and battery manufacturers to develop scalable production processes, emphasizing environmental sustainability through water-based electrode production and footprint optimization. Current initiatives focus on digital factory modeling and prelithiation technologies for next-generation battery systems.
Larissa Schlegel-Pape serves as a Scientific Associate at the Department for Ornamental and Pedigree Poultry within the Farm Animal Clinic of Freie Universität Berlin's Faculty of Veterinary Medicine. Her work focuses on developing innovative methods for assessing chicken welfare through the creation of the "Stressed Chicken Scale," which aims to systematically identify stress indicators in poultry. Her research interests center on animal welfare science, specifically stress assessment in chickens using both behavioral observation and computer vision technology. She investigates how body posture, movement patterns, and other visual indicators can reliably signal discomfort or stress in poultry, with the goal of creating practical assessment tools for veterinarians and poultry farmers. Her work bridges veterinary medicine, ethology, and technological innovation, contributing to refinement research (one of the 3Rs principles) in animal husbandry. Analysis of her publications reveals a strong focus on developing and validating the Stressed Chicken Scale across multiple contexts. Her work spans methodological development, practical implementation studies, and technological integration with computer vision systems. The research demonstrates progression from conceptual framework to validation studies and practical application, with increasing sophistication in assessment techniques and broader implications for animal welfare standards in poultry farming. Schlegel-Pape actively collaborates with the Federal Institute for Risk Assessment (BfR) and participates in interdisciplinary projects involving artificial intelligence applications in agriculture. She presents her findings regularly at major German veterinary conferences including the DVG (Deutsche Veterinärmedizinische Gesellschaft) events, DACh Epidemiology conferences, and specialized poultry medicine gatherings. Her work contributes significantly to advancing animal welfare assessment methodologies and promoting refinement in poultry husbandry practices.
Elaine J. Francis is a Professor of English and Linguistics at Purdue University, where she also serves as the Associate Head of the Department of English. She holds affiliate appointments in the Department of Linguistics and the Department of Speech, Language, and Hearing Sciences. At Purdue, she directs the Experimental Linguistics Lab and teaches linguistics courses at both graduate and undergraduate levels. Francis completed her B.A. in Linguistics at the College of William and Mary in 1993, followed by her M.A. (1995) and Ph.D. (1999) in Linguistics at the University of Chicago under the direction of Salikoko Mufwene. Her dissertation examined variation among members of the same lexical category in English using Sadock's Autolexical Grammar framework. Prior to joining Purdue in 2003, she served as an Assistant Professor at the University of Hong Kong from 1999 to 2002, where she collaborated with Stephen Matthews on research concerning syntactic categories and relative clauses in Cantonese. Her research focuses on syntax and its interfaces with semantics, discourse information structure, and language processing in production and comprehension. Francis employs experimental methods to investigate syntactic, semantic, discourse-pragmatic, and cognitive factors underlying the grammar and usage of complex sentence structures. Her specific interests include word order alternations, filler-gap dependencies, resumptive pronouns, relative clauses, grammatical categories, and syntactic alternations. She has published extensively in top linguistics journals including Language and Cognition, Glossa Psycholinguistics, Linguistics, Lingua, Cognitive Linguistics, and the Journal of Psycholinguistic Research. Analyzing her recent publications reveals a consistent focus on experimental approaches to syntactic phenomena. Her work demonstrates a strong interest in gradient acceptability, syntactic priming, cross-linguistic comparison (particularly involving English and Cantonese), and the relationship between grammatical theory and language processing. Her 2022 book Gradient Acceptability and Linguistic Theory represents a major contribution that synthesizes experimental findings with theoretical linguistics frameworks. Francis plays an active role in the broader linguistics community. She regularly teaches short courses at the Linguistic Society of America Linguistic Institutes, serves on the LSA Ethics Committee, and is on the editorial board of Glossa Psycholinguistics. She has also edited several books and special journal issues, including Mismatch: Form-Function Incongruity and the Architecture of Grammar (2003) and Polymorphous Linguistics: Jim McCawley's Legacy (2005). As an educator and administrator, Francis has supervised numerous graduate students and currently serves as Associate Head of the Department of English at Purdue. Her Experimental Linguistics Lab provides research opportunities for students interested in the intersection of theoretical syntax and experimental methodology. While she recently announced she will not be accepting new graduate students for the 2025-2026 cycle, her established mentorship record demonstrates her commitment to training the next generation of linguists. The Experimental Linguistics Lab, which she directs, serves as a hub for research combining theoretical linguistics with experimental methods. Her collaborative work extends across disciplines, including collaborations with researchers in speech-language pathology, cognitive science, and computational linguistics, reflecting the interdisciplinary nature of modern linguistic research.
Dr. Aditya Joshi is a Senior Lecturer in the School of Computer Science & Engineering at the University of New South Wales (UNSW). He specializes in Natural Language Processing (NLP), with a focus on sarcasm detection, dialectal NLP, and ethical AI applications in public health and cybersecurity. He joined UNSW in 2023 following industry roles at SEEK, Notiv, and Fractal Analytics, where he developed NLP systems for recommendation engines and meeting analytics. His research has garnered over 3,000 citations (h-index 26) and secured $3.1M in grants, including Defence Trailblazer and Google exploreCSR awards. Education: Joint PhD (2018) from IIT Bombay (India) and Monash University (Australia); MTech in CSE (2011) from IIT Bombay. Research Interests: Making NLP models robust for non-native English speakers and the LGBTI+ community, algorithmic enhancements to transformers, and applications in public health, cybersecurity, and societal issues. His work spans epidemic intelligence (collaborations with EPIWATCH and IFCYBER), cybersecurity tools like AuditNet, and inclusive AI initiatives such as queer-inclusive workshops funded by Google. He designed UNSW's new NLP course (COMP6713) and co-authored a Wiley textbook on NLP. Notable grants include the A$1.4M 'Comprehensive Defence Data Platform' (Lead CI) and A$92K Google exploreCSR grant for benchmarking dialectal sentiment. His awards include the Best PhD Thesis from IITB-Monash and Best Paper accolades at FAccT 2023 and MoMM 2020. He supervises projects on kernel-based attention reformulation, prompt-based sarcasm detection, and multilingual small-scale LLMs. His service roles include Executive Committee Member at ALTA and arXiv moderator for computational linguistics.
Parastoo Abtahi is an Assistant Professor in the Computer Science Department at Princeton University. She leads the Situated Interactions Lab (Ψ Lab) as part of the Princeton HCI Group, focusing on AR/VR and spatial computing. Prior to Princeton, she worked at Meta Reality Labs Research. PhD in Computer Science from Stanford University BSc in Electrical and Computer Engineering from University of Toronto (Engineering Science program) Her research explores wearable interactive technologies that augment human intelligence in physical contexts through: Input on-the-go: Low-effort, privacy-preserving multimodal interfaces Intelligent output: Timely, minimal multisensory systems Situated AI: Personalizable, predictable, safe physical-digital interaction Recent publications analyze: Drone-based haptic illusions for AR/VR Microgestures for mobile AR input Interactivity in explainable AI systems Temporal dynamics in VR haptics Awards include: 2025 Google Research Scholar Award CHI 2019 & 2018 Honorable Mentions She teaches courses like: COS 436: Human-Computer Interaction COS IW: AR Meets AI
