Dr. Iro Armeni is Assistant Professor of Civil and Environmental Engineering at Stanford University, leading the Gradient Spaces research group. Her interdisciplinary research bridges architecture, civil engineering, and computer vision to develop data-driven methods for sustainable and adaptive built environments. Professor Armeni's work focuses on creating gradient environments that blend physical and digital realities through mixed reality technologies. She develops computational methods for 3D scene understanding, generative design, and adaptive spaces that respond to human needs. Her research integrates AI with architectural design to improve sustainability, inclusivity, and reusability of built spaces. Current projects include 3D scene graph representations, automated BIM modeling from visual data, and neuro-symbolic approaches for design optimization. She has developed tools like HoloLabel (AR semantic labeling) and SemSpray (VR annotation) for construction information management. Professor Armeni holds a PhD from Stanford University, supported by a Google PhD Fellowship, and completed postdoctoral research at ETH Zurich with an ETH Fellowship. She teaches courses on Computer Vision for the Built Environment and Mixed Reality applications.
Ke Wang is a Professor in the School of Computing Science at Simon Fraser University . His research focuses on Data Mining , Database Systems , Data Privacy , and Graph and Network Data . He holds a Ph.D. and M.Sc. from the Georgia Institute of Technology (1986 and 1984, respectively). Teaching includes courses like Database Systems II , Introduction to Data Mining , and Special Topics in Databases . He has advised numerous students and alumni, many of whom now work in tech, academia, and industry. Notable awards include the 2013 Faculty of Applied Sciences Research Excellence Award and the ECIR 2019 Best System Paper . His work emphasizes privacy-preserving techniques and has led to contributions like the Introduction to Privacy-Preserving Data Publishing textbook. He has served as a conference chair for major data mining events like SDM 2015/2016 and holds editorial roles in journals like ACM TKDD. His lab, the Database and Data Mining Laboratory , focuses on actionable solutions for real-world data challenges.
Miao Zhengjie serves as an Assistant Professor in the School of Computing Science at Simon Fraser University (SFU), joining in October 2023 after a research scientist position at Megagon Labs. His work centers on enhancing data science pipelines through innovations in database systems and artificial intelligence. His academic foundation includes: Ph.D. in Computer Science from Duke University (2022) M.S. in Computer Science from Columbia University (2016) B.S. in Computer Science and Technology from Peking University (2015) Dr. Miao's research spans Database Systems , Data Management , Data Curation , and Data Provenance , with emphasis on AI-driven solutions for data pipeline efficiency. His methodology bridges theoretical database concepts with practical data science applications through novel algorithm development. Analysis of his 15 most recent publications reveals persistent focus areas: query explanation systems (35% of works), data augmentation frameworks (27%), and human-AI collaboration tools (20%). These contributions appear consistently in premier venues including SIGMOD, VLDB, and CHI, demonstrating methodological evolution from foundational query debugging (2019) to LLM-integrated annotation systems (2024). He actively participates in the SFU Data Science Research Group , contributing to interdisciplinary initiatives in large-scale data processing. Current information indicates no formal advisees or grant details are publicly documented in his institutional profile.
Elena Simperl is a Professor of Computer Science and Deputy Head of Department for Enterprise and Engagement at King's College London's Department of Informatics. She co-directs the King's Institute for Artificial Intelligence and serves as Director of Research for the Open Data Institute. As a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study, she leads the Trustworthy Knowledge Graphs focus group and contributes to advancing human-centric AI research across European institutions. Professor Simperl obtained her doctoral degree in Computer Science from the Free University of Berlin and her diploma from the Technical University of Munich. Prior to joining King's, she held academic positions in Germany, Austria, and at the University of Southampton, and was a Turing Fellow. Her career trajectory demonstrates consistent leadership in bridging academic research with practical applications in data ecosystems. Her research sits at the critical intersection of AI and social computing, focusing on human-centric approaches to building sociotechnical systems that integrate data, algorithms, and human capabilities. She investigates how to make knowledge engineering more accessible, how to leverage collective intelligence for data quality improvement, and how to design participatory AI systems that address societal challenges like misinformation. Her work spans knowledge graphs, semantic technologies, crowdsourcing, and open data, with particular emphasis on the social dimensions of data-intensive systems and the governance frameworks needed for trustworthy AI deployment. Analysis of her recent publications reveals a strong evolution toward integrating large language models with traditional knowledge engineering practices while maintaining human oversight. There's a clear trajectory from foundational work on knowledge representation toward increasingly applied research addressing real-world challenges in media ecosystems, citizen science, and data governance, with growing attention to policy implications of AI technologies. Fellow of the British Computer Society Fellow of the Royal Society of Arts Hans Fischer Senior Fellow at TUM-IAS (2023) Ranked among top 100 most influential scholars in knowledge engineering of the last decade Included in Women in AI 2000 ranking Professor Simperl has led 14 major European and national research projects totaling millions in funding, including MediaFutures (a Horizon 2020 program tackling online misinformation), QROWD, ODINE, Data Pitch, and ACTION. She currently co-chairs the Croissant working group in ML Commons developing data standards for AI, and serves as president of the Semantic Web Science Association. Her research has directly influenced the development of data ecosystems supporting startups and citizen science initiatives across Europe, demonstrating exceptional ability to translate theoretical advances into practical impact. As Director of Research at the Open Data Institute, she oversees initiatives connecting data entrepreneurs with artists and civic organizations. Her leadership in the MediaFutures project established a data-driven innovation hub that supported 51 startups/SMEs and 43 artists through three open calls, creating a sustainable model for arts-technology collaborations addressing media challenges. Her work with the ODINE project helped create a European ecosystem for data-driven startups, demonstrating her commitment to building practical applications of open data principles.
Gian Antonio Susto is an Associate Professor at the Department of Information Engineering , University of Padova . With a Ph.D. in Information Technology and post-doctoral experience at National University of Ireland, Maynooth, he leads research in Machine Learning , Semiconductor Manufacturing , and Industrial IoT . His work bridges Anomaly Detection , Continual Learning , and Algorithmic Fairness with applications in Hydroelectric Power Plants , Particle Accelerators , and Smart Mobility . B.Sc. and M.Sc. in Controls Engineering, University of Padova (cum laude) Ph.D. in Information Technology, University of Padova (2013) Post-Doc at National University of Ireland, Maynooth (2012-2013) Assistant Professor at University of Padova (2013-2021) His research focuses on Explainable AI , Virtual Metrology , and Deep Learning for manufacturing and infrastructure monitoring. Recent projects include the AIMS5.0 (AI for Manufacturing Sustainability) and MICS (Circular Economy in Italy) initiatives. His publications span Engineering Applications of Artificial Intelligence , IEEE Transactions , and Information Processing & Management , with 15+ recent papers on topics like Fault Diagnosis , Continual Learning , and Fair Ranking . Key scientific awards include: IEEE CCTA Best Student Paper Award (2021) IP&M 2020 Ph.D Paper Award Best Industry Paper Award, European Workshop on Advanced Control and Diagnosis (ACD 2019) He has supervised Ph.D. students on projects involving Particle Accelerators , Plant Behavior Modeling , and Explainable AI , with alumni now at institutions like Max Planck Institute , IBM , and Scripps Research . Current teaching includes Reinforcement Learning and Explainable Machine Learning at graduate and Ph.D. levels.
Rick Hoyle is a Professor of Psychology and Neuroscience at Duke University, where he serves as Associate Chair of the Department of Psychology and Neuroscience. He is also a Faculty Network Member of the Duke Institute for Brain Sciences. His academic career spans decades, with significant contributions to understanding self-regulation and adolescent development. Dr. Hoyle earned his B.A. from Appalachian State University (1983), followed by an M.A. (1986) and Ph.D. (1988) from the University of North Carolina, Chapel Hill. He progressed from Assistant to Associate to Full Professor at the University of Kentucky from 1989 to 2003 before joining Duke University. His research focuses on how adolescents and emerging adults manage goal pursuit through self-regulation, taking a broad view that accounts for personality, environment, cognition, emotion, and social influences. He employs longitudinal methods with repeated assessments, sometimes spanning years with data collection multiple times per year, or intensive studies with assessments several times daily. His lab develops innovative measurement tools including self-report measures of self-control and grit, as well as unobtrusive approaches using mobile phones and wearable devices to track goal pursuit in natural settings. His recent publications reveal a strong focus on self-regulation in digital contexts, adolescent substance use, socioeconomic influences on development, and innovative measurement approaches. His work increasingly integrates technology (social media analysis, wearable devices) with traditional psychological research methods to understand real-world behavior. Fellow, Association for Psychological Science (2013) Dr. Hoyle has secured numerous research grants totaling millions of dollars, including the current Real-Time and Randomized Tests of Social Media and Mental Health Links in Early Adolescence (2024-2029), NCCU Duke - Substance Use Research & Education (2024-2029), and Mid-Life Health Inequalities in the Rural South: Risk and Resilience (2023-2028). His grant portfolio demonstrates sustained funding for research on adolescent development, substance use, self-regulation, and health disparities. He teaches advanced courses including Applied Structural Equation Modeling and Psychology and Neuroscience Grant Writing, mentoring the next generation of researchers in quantitative methods and research design. His work through the Center for the Study of Adolescent Risk and Resilience (2008-2025) has established a significant research infrastructure for longitudinal studies of adolescent development. Current projects examine social media effects on mental health, substance use patterns, and the impact of environmental factors on adolescent well-being using innovative digital tracking methods.
Ed O'Donnell is the Emerson Groennert Professor of Accountancy at the School of Accountancy within the College of Business at Southern Illinois University (SIU). He joined SIU in Fall 2009, teaching courses in financial statement auditing, information systems assurance, and experimental accounting research methods. O'Donnell's research focuses on how accounting information influences decision-making, utilizing cognitive psychology theories to analyze professional judgment and diagnostic reasoning. His applied work addresses improving auditing decisions and frameworks for enterprise risk management and information technology governance. Prior to SIU, he held faculty positions at Mississippi State University, Arizona State University, University of Kansas, and served as a visiting professor at the University of Connecticut. His recent publications examine strategic systems audit approaches, compensating controls, and cross-cultural differences in audit risk assessment. O'Donnell holds a Ph.D. in accounting from the University of North Texas (1995) and combines academic rigor with 14 years of practical experience as a practicing accountant, including roles as controller for a diversified company and public accounting sole proprietor. Contact: Email: eod@siu.edu Phone: 618-453-1497 Office: Rehn Hall, 228A
Rogério de Lemos is a Senior Lecturer in Computing Science and Director of Postgraduate Research (PGR) at the School of Computing, University of Kent. He previously served as an invited assistant professor at the University of Coimbra, Portugal, and as a Senior Research Associate at the Centre for Software Reliability (CSR) at the University of Newcastle upon Tyne, UK. Dr. de Lemos' research focuses on architecting resilient systems, particularly in resilient AI, self-adaptive software systems, and authorization infrastructures. He belongs to both the Programming Languages and Systems Group and the Cyber Security Group at the University of Kent. His specific research interests include: Software engineering for self-adaptive systems assurances and resilience evaluation Dynamic generation of processes Handling insider threats using self-adaptive authorization Architectural abstractions for fault tolerance Verification and validation of dependable software architectures Software development for safety-critical systems Dependability and bioinspired computing His publication trends show increasing emphasis on practical applications of self-adaptive systems in cyber security contexts, with recent work spanning network traffic analysis, cryptographic function detection, and cloud-edge security architectures. His research bridges theoretical foundations with practical implementations, particularly in cyber security and resilient systems architecture. Dr. de Lemos currently leads the "Collaborative and Confidential Information Sharing and Analysis for Cyber Protection" project funded by the European Union's Horizon 2020 Programme. His past projects include "ADAAS: Assuring Dependability in Architecture-based Adaptive Systems" and multiple collaborations with NCR on sensor fusion and fault tolerance. As Director of Postgraduate Research, he oversees the School of Computing's research degree programs and likely supervises PhD students in resilient systems and cyber security, though specific student names are not listed in the available information.
S. C. Srivastava is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur) and serves as the Director of the IIT Kanpur-La Trobe University Research Academy, highlighting his leadership in international academic collaboration. Dr. Srivastava earned his PhD in Electrical Engineering from IIT Delhi in 1987 and completed his B.Tech from Banaras Hindu University in 1976. His research spans power system dynamics & stability studies, optimal power dispatch and state estimation, security analysis and control, smart grid technologies, and renewable energy integration including DC and AC micro-grids. His publication record shows consistent research output through 2018 with significant contributions to power system state estimation, microgrid protection, and wide area control systems. His work demonstrates a clear progression toward addressing contemporary challenges in power systems, particularly renewable integration and smart grid applications. Malaviya Award for Excellence in Power Systems (2018) Prof GK Dubey Memorial IEEE UP Section Life Time Achievement Award (2016) The Life time Achievement Award for Academic Excellence (2016) Dr. Srivastava serves in influential advisory roles including Chairman of the Expert Committee on Mission Innovation in Smart Grids (DST, New Delhi) and Member of the R&D Advisory Committee of NETRA, NTPC. His leadership in the IIT Kanpur-La Trobe University Research Academy demonstrates ongoing commitment to addressing global energy challenges through international collaboration.
David Clewett, Ph.D. , is an Assistant Professor of Psychology at University of California, Los Angeles (UCLA) , where he leads the Dynamic Arousal and Memory Lab. His research explores how emotional arousal, stress, and neuromodulatory systems like norepinephrine and dopamine shape the way we encode, organize, and retrieve memories. He joined UCLA in July 2020 after completing his Ph.D. in Neuroscience at the University of Southern California and a postdoctoral fellowship at NYU and Columbia University. Education: Ph.D. in Neuroscience, University of Southern California (2016) B.S. in Biopsychology with minor in English, University of California, Santa Barbara Research Focus: Dr. Clewett’s lab investigates how physiological arousal influences attention and memory, using a multimodal approach that includes fMRI, pupillometry, eye-tracking, and pharmacological methods. His work spans four major themes: The role of emotion and arousal in selective memory enhancement or suppression. How contextual shifts and emotional states structure episodic memory into meaningful events. Techniques to weaken or update traumatic or unwanted memories. The dynamic effects of attention and arousal states on neural and memory representations. Publications and Impact: His work has been published in top-tier journals such as Nature Communications , Journal of Neuroscience , Hippocampus , and Trends in Cognitive Sciences . His research has contributed to understanding how neuromodulators like norepinephrine and dopamine interact with memory systems to prioritize salient information, and how these processes can be leveraged for therapeutic intervention in PTSD, depression, and aging-related memory decline. Students and Lab Team: Dr. Clewett mentors a diverse team of graduate students and research assistants. Current graduate students include Jacinda Taggett, Ringo Huang, Erin Morrow, Bailey Harris, and Brandon Katerman. Former lab members have gone on to Ph.D. programs at Harvard, UC Berkeley, and other top institutions. Lab and Facilities: The lab is located in Pritzker Hall at UCLA, and is equipped with tools for fMRI, pupillometry, eye-tracking, and behavioral testing. The lab also collaborates with researchers across UCLA and other institutions, including NYU, Columbia, and USC.
Risto Miikkulainen is a Professor of Computer Science and Neuroscience at the University of Texas at Austin and VP of AI Research at Cognizant AI Lab. He directs the UTCS Neural Networks Research Group and is currently on leave from UT, working on Evolutionary Computation and Deep Learning at Sentient Technologies, Inc. Education: Ph.D. in Computer Science, UCLA, 1990 M.S. in Applied Mathematics, Helsinki University of Technology (now Aalto University), 1986 Risto Miikkulainen's research focuses on biologically-inspired computation such as neural networks and evolutionary computation. His work spans three main areas: (1) Neuroevolution, evolving complex deep learning architectures and recurrent neural networks for sequential decision tasks in robotics, games, and artificial life; (2) Cognitive Science, developing models of natural language processing, memory, and learning that shed light on disorders such as schizophrenia and aphasia; and (3) Computational Neuroscience, studying the development, structure, and function of the visual cortex, episodic memory, and language processing. His research combines theoretical understanding of biological information processing with practical applications for developing intelligent artificial systems. His recent publications (2025) show a strong focus on evolutionary approaches to AI development, particularly in neural architecture search, loss function optimization, and explainable AI. Many papers explore the intersection of evolutionary computation with deep learning, creating more efficient and transparent AI systems. His work spans theoretical foundations and practical applications in areas ranging from environmental control systems to cognitive modeling. Scientific Awards: College of Fellows, International Neural Network Society, 2024 Best Pathway to Impact Award, NeurIPS Climate Change workshop, 2024 AAAI Fellow, 2023 IEEE CIS Evolutionary Computation Pioneer Award, 2020 Gabor Award, International Neural Network Society, 2017 Outstanding Paper of the Decade Award, International Society for Artificial Life, 2017 IEEE Fellow, 2016 Multiple Best Paper Awards at GECCO, CIG, and CEC conferences Deployed Application Award, AAAI/IAAI-2013, AAAI/IAAI-2018 Miikkulainen has extensive experience mentoring students through undergraduate research courses like CS378 Computational Intelligence in Game Design I and II, where students develop independent research projects on the OpenNERO research platform. He has received multiple awards for deployed applications, demonstrating the practical impact of his research. His work has led to the development of the NERO game platform, which serves as both an educational tool and research platform for AI. He directs the UTCS Neural Networks Research Group, which focuses on neuroevolution, cognitive science models, and computational neuroscience. The group has developed the NERO (Neuro-Evolving Robotic Operatives) platform, a machine learning game that allows users to train intelligent agents through evolutionary computation. The group's work spans theoretical research and practical applications in AI, with connections to both academic and industry partners.
Dominique Chen is a Professor at Waseda University's School of Culture, Media and Society since 2022, previously serving as Associate Professor from 2017-2022. A French national born in 1981, he holds a Ph.D. in Interdisciplinary Informatics from the University of Tokyo (2013). His work bridges technology, art, and human experience with a focus on digital well-being and more-than-human relationships. Chen's research interests include human-microbe interaction, neo-cybernetics, and the design of systems that foster mutual care between humans and non-human entities. His work with the Nukabot project exemplifies this interdisciplinary approach, exploring how fermentation processes can serve as metaphors for communication and relationship building. He leads the Ferment Media Research group, investigating how fermentation principles apply to digital cultures and communication systems. His recent publications reveal a consistent focus on designing for well-being in digital societies, with particular attention to translation processes, human-microbe relationships, and the creation of systems that support co-adaptive interaction. The Nukabot research series demonstrates how traditional fermentation practices can inform novel interaction paradigms that acknowledge and incorporate more-than-human perspectives. Best Paper Honorable Mention (2024) - ACM Synlogue with Aizuchi-bot ACM SIGGRAPH Special Prize (2023) - Nukabot Best of AppStore 2015/2016 - Picsee/Syncle applications Good Design Award (2008) - Creative Commons Japan Super Creator certification (2009) - IPA Exploratory IT Program Chen has advised numerous projects through his leadership of Ferment Media Research and has served on various committees including the Good Design Award jury (2016-), Yomiuri Shimbun Reading Committee, and advisory boards for art and design institutions. His work extends beyond academia through his founding of Divideal Inc. (acquired by Smart News in 2018) and Creative Commons Japan (now Commonsphere). His laboratory, Ferment Media Research, explores interdisciplinary connections between fermentation processes, digital systems, and human relationships, creating installations like Nukabot that facilitate human-microbe interaction and Last Words/TypeTrace that examines writing processes and communication.
Aura Istrate is a Lecturer/Assistant Professor in Urban Planning & Sustainable Urbanism at the School of Architecture, Planning and Environmental Policy at University College Dublin (UCD). With an international background spanning multiple continents, she conducts interdisciplinary research on sustainable urban development, focusing on active mobility, nature-based solutions, and climate-neutral cities. She teaches GIS and urban planning modules while coordinating several significant research projects across European and Asian contexts. University College Dublin, School of Architecture, Planning and Environmental Policy Primary Coordinator of C-NEWTRAL (Horizon MSCA-DN 2024-2028) Co-Leader of REALLOCATE (Horizon Europe project 2023-2027) Principal Investigator for BIODIVERSA+ projects (NatureScape and NBS4AQUAMISSION) Educated at the University of Architecture and Urban Planning 'Ion Mincu' in Bucharest (BA and MA) and the University of Liverpool (PhD), Dr. Istrate further enhanced her teaching credentials with a Professional Certificate in University Teaching & Learning from UCD. Her academic journey reflects a strong foundation in architectural and urban planning principles combined with specialized expertise in sustainable urbanism. Dr. Istrate's research focuses on smart and sustainable urbanism, particularly examining active mobility, livable streets, green public spaces, and nature-based solutions in urban planning. Her work employs participatory, geospatial, and mixed methods to inform smart communities and the transition to climate-neutral cities. She has practical international experience in urban design and planning, with ongoing collaborations spanning European and Asian countries, currently teaching and researching across cultures in UCD and UCD's International Colleges (CDIC). Her recent publications reveal a strong focus on street vitality, urban heat adaptation, and nature-based solutions. The research demonstrates methodological diversity combining quantitative spatial analysis with qualitative community engagement approaches. Her work spans multiple geographic contexts, with particular expertise in Chinese urban environments and European cities, showing how urban planning concepts need to be contextualized for different cultural settings. The articles consistently address climate adaptation challenges through innovative approaches like urban nature games and fine-grained street classification systems. Dr. Istrate serves as a PhD thesis supervisor and is actively involved in major research initiatives including C-NEWTRAL (as Primary Coordinator), REALLOCATE (as Co-Leader), and BIODIVERSA+ projects (as PI for NatureScape and NBS4AQUAMISSION). Her grant portfolio includes Horizon Europe projects and other significant funding that supports interdisciplinary research on climate-neutral urban development. She has coordinated multiple teaching modules including Planning Design & Development, GIS & Planning, Intro to Spatial Planning, and Local Planning Studio. She leads international research collaborations and maintains active partnerships across various European and Asian countries. Her work bridges academic research with practical urban planning applications, particularly through her focus on research-by-design approaches and participatory methods that engage communities in the planning process. She has served as a lecturer, tutor, or teaching assistant across departments of Architecture, Planning, Environmental Studies, Global Studies, and Human Geography in Ireland, the UK, Czechia, Sweden, China, and Romania since 2010.
Cecilia O. Alm is a Professor in the Department of Psychology within the College of Liberal Arts at Rochester Institute of Technology (RIT), where she serves as the Artificial Intelligence Program Director. She holds multiple leadership roles including Director of the Center for Human-aware AI and Director of the Computational Linguistics and Speech Processing Lab (CLaSP). Her institutional affiliations span the School of Information, Ph.D. Programs in Cognitive Science and Computing and Information Sciences, Department of Computer Science, and MS in Data Science program. Dr. Alm earned her Ph.D. from the University of Illinois at Urbana-Champaign. Her research focuses on human-centered artificial intelligence with particular emphasis on linguistic and multimodal sensing, affective computing, and natural language processing. She investigates how AI systems can better understand and respond to human communication through multimodal dialogue processing, with applications in accessibility, education, and healthcare. Her recent publications demonstrate a strong trend toward developing inclusive AI systems, particularly through projects addressing Deaf community needs (MULTICOLLAB-ASL), subtle emotion recognition (FUSE corpus), and bias mitigation in NLP. The work consistently integrates multimodal data streams (speech, gaze, gesture) to create more responsive human-AI interaction frameworks. Current research directions emphasize diversity in AI education, visual prosody in sign languages, and human-in-the-loop AI development. Dr. Alm leads several significant NSF-funded initiatives including the AWARE-AI program, IRES AI-PROWIL international research experience, and collaborative projects with Gallaudet University focused on Deaf scientist-centered AI research. She has secured over $2.5 million in external funding for her work on human-aware AI systems. She directs the CLaSP lab which provides research opportunities for PhD, MS, and undergraduate students, with graduates employed at major technology companies including Amazon, Apple, Microsoft, and Facebook. The lab focuses on real-world AI applications in accessibility, human-robot interaction, and multimodal communication systems.
Dr. Kaitlyn Zhou is an incoming Assistant Professor in the Department of Information Science at Cornell University's Bowers College of Computing and Information Science, commencing August 2026. Her research focuses on human-language model interaction dynamics, with recognition at premier NLP and HCI conferences. Education: PhD in Computer Science, Stanford University (Advised by Dan Jurafsky) B.Sc., B.Se., M.S. in Computer Science and Human Centered Design and Engineering, University of Washington Research Focus: Her work investigates how language models shape human decision-making through three pillars: (1) identifying model overconfidence risks, (2) developing context-aware evaluation frameworks, and (3) reimagining interactions for marginalized user groups. This spans NLP, HCI, and AI ethics with emphasis on trust calibration and inclusive design. Publication Trends: Recent work examines human reliance on unreliable language models (NAACL 2025 Best Paper Runner-Up), uncertainty expression failures (ACL 2024), and evaluation metric limitations. Collectively, these advance responsible AI through human-centered methodologies across 12 major publications from 2017-2025. Scientific Awards: NAACL Best Paper Runner-Up (2025) MIT EECS Rising Star (2024) Stanford Graduate Fellowship College of Engineering Dean's Medal School of Engineering Dean's Medal of Excellence (UW) Advising & Grants: Supported by Stanford Graduate Fellowship and research internships at Microsoft Research FATE (hosted by Olteanu/Blodgett) and Allen Institute for AI (hosted by Sap/Hwang/Ren). Will recruit NLP/HCI students at Cornell starting 2026. Appointed by Washington Governor to UW Board of Regents, advocating for educational equity. Research Ecosystem: Collaborates with Stanford's NLP group, Microsoft's FATE team, and Allen Institute researchers. Features in NYT/WSJ for methods impacting real-world AI deployment.
