Jennifer Neville is a Senior Principal Researcher at Microsoft Research Redmond and holds the Samuel Conte Chair Professor of Computer Science and Statistics at Purdue University. With over 100 publications and 10K citations, her research spans data mining, machine learning, and AI algorithms for relational and networked domains including social networks, epidemiology, and web analytics. Education: BS in Computer Science, University of Massachusetts Amherst (2000) MS in Computer Science, University of Massachusetts Amherst (2004) PhD in Computer Science, University of Massachusetts Amherst (2006) Her work focuses on relational learning techniques that exploit connections between entities to enhance pattern discovery. Recent research explores large language models (LLMs), emphasizing alignment with user intent through interaction at scale, while addressing statistical biases from graph structures. Selected scientific awards include the NSF Career Award (2012), ICDM Best Paper (2009), and IEEE’s 10 to Watch in AI (2008). She served on the AAAI Executive Council (2015-2018) and chaired multiple conferences including SIAM Data Mining (2019) and ACM Web Search (2016). Contact: neville@cs.purdue.edu jenneville@microsoft.com
Prof. Ryan Keith Shosted is a full-time tenured Professor at the University of Illinois at Urbana-Champaign , affiliated with the Department of Linguistics , Spanish and Portuguese , American Indian Studies Program , Beckman Institute , Lemann Center for Brazilian Studies , Center for Latin American and Caribbean Studies , and Center for African Studies . He serves as Director of the Program in Translation and Interpreting Studies and leads the Chin-Woo Kim Phonetics Laboratory . Education: Ph.D. , Linguistics, University of California, Berkeley (2006) M.A. , Linguistics, University of California, Berkeley (2003) B.A. , Linguistics, Brigham Young University (2000) Shosted's research focuses on the intersection of phonetics , phonology , and historical linguistics . He pioneered the application of ultrafast dynamic MRI to study the vocal tract's physiological-acoustic mapping in diverse languages, including Hittite cuneiform , Deseret Alphabet , and endangered languages like Q'anjob'al. His work spans speech production modeling , nasalization mechanisms , and cross-linguistic articulatory analysis . The 15 most recent publications demonstrate his leadership in dynamic speech imaging , phonetic-aerodynamic modeling , and historical sound change analysis . Key trends include advanced MRI techniques for speech study, phonetic universals , and historical writing systems as tools for linguistic reconstruction. Scientific Awards: Campus Award for Excellence in Undergraduate Teaching (2021) Dean's Award for Excellence in Undergraduate Teaching (2021) Arnold O. Beckman Award (2009, 2010) Jacob K. Javits Fellowship (2001-2005) Shosted's grant portfolio includes NSF funding for nasalization research (BCS-1651197, BCS-1121780) and NIH collaboration (1R01DE027989-01A1) on cleft palate speech. He has directed 12 graduate students and taught courses ranging from Hittite language to quantitative phonetic methods . The Chin-Woo Kim Phonetics Laboratory , under his directorship since 2007, expanded in 2010 to include articulatory phonetics facilities with EPG, ultrasound, and MRI analysis capabilities. He continues to lead Beckman Institute collaborations in speech imaging technology.
Univ.-Prof. Dr. Michaela Sambanis is a Professor of English Didactics at the Institute of English Philology within the Department of Philosophy and Humanities at Freie Universität Berlin. She has held this position since 2011 and previously served as the managing director of the Institute from Winter semester 2017/2018 to October 2019. Her academic journey includes research work at the Transfer Center for Neuroscience and Learning at the University of Ulm (2008-2011), completion of her habilitation in 2006, and her promotion in 2001. Professor Sambanis's research centers on the innovative intersection of educational neuroscience and language teaching methodology. Her work pioneers the field of Positive Foreign Language Didactics, connecting positive psychology with language education. She investigates embodied cognition approaches, particularly movement-based learning, and explores theater methods and arts integration in language instruction. Her research also addresses teacher well-being and health, multilingualism in educational settings, and the application of neuroscience findings to practical classroom situations. The k2teach project represents her current focus on teaching-learning labs in English teacher education. Her scholarly output demonstrates a consistent trajectory toward integrating neuroscience with language pedagogy, with recent publications increasingly addressing mental health, digital transformation in education, and positive psychology applications. The evolution of her work shows a progression from practical teaching methods to increasingly sophisticated neurodidactic frameworks that bridge scientific evidence with classroom practice. Professor Sambanis serves on multiple scientific advisory boards including the Goethe Institut in Munich, the Transfer Center for Neuroscience and Learning at the University of Ulm, and the Schlözer Program for Teacher Education. She is also the founding chair of the cross-state E&M Berlin-Brandenburg section and a member of the German Society for Foreign Language Research (DGFF). Her editorial work includes the SELT book series on English Language Teaching. Her teaching responsibilities include supervising master's theses in English teaching, and she has developed numerous teaching-learning laboratories that connect theoretical knowledge with practical application in teacher education. Her work demonstrates a strong commitment to evidence-based foreign language didactics that incorporates insights from neuroscience, psychology, and educational research.
Pavel Panchekha is an Assistant Professor in the School of Computing at the University of Utah, where he holds the Warnock Chair for Junior Faculty. His research spans programming languages, web browsers, and numerical analysis, with a focus on developing programming language techniques to address challenges across computer science. Dr. Panchekha received his educational training at prestigious institutions: PhD in Computer Science from the Paul G. Allen School for Computer Science and Engineering at the University of Washington, advised by Michael D. Ernst and Zachary Tatlock BS in Mathematics from MIT Panchekha's research program has two major thrusts. First, he works on web browser internals , with projects including fuzzing layout invalidation, multi-tenant garbage collection, and optimizing 2D graphics. He is also authoring a textbook on web browsers that informs much of this research. Second, he focuses on automatic numerical analysis , with projects such as automatic accuracy improvement, synthesis via term rewriting, scalable static accuracy analysis, and math library implementation. He leads the FPBench and Herbie projects, which are major deployments of his research. His scholarly output demonstrates consistent contributions across programming languages, verification, and numerical methods. Recent work shows a growing emphasis on bidirectional typing systems, layout invalidation in browsers, and robust floating-point error analysis. His publications reveal a trajectory from foundational work on floating-point accuracy (notably the Herbie tool that won a Distinguished Paper Award at PLDI 2015) toward more comprehensive systems for program synthesis, verification, and browser optimization. Panchekha has received significant recognition for his research contributions: NSF Fellowship ARCS Foundation Fellowship Adobe Research Fellowship Wissner-Slivka Foundation Fellowship 2015 PLDI Distinguished Paper Award for work on the Herbie numerical analysis and repair tool As an advisor, Panchekha mentors a substantial group of students across multiple levels. He currently advises six students: Marisa Kirisame (PhD), Bhargav Kulkarni (PhD), Yumeng He (PhD), Artem Yadrov (MS), Jesus Ponce (BS), and Jonas Regehr (BS). Previously, he has advised over twenty students including PhD candidates like Ian Briggs and numerous MS and BS students. His advising spans theoretical topics in programming languages and practical applications in web browsers and numerical computing. Panchekha leads research groups focused on programming languages applications to web browsers and numerical analysis. His work on the Herbie tool for floating-point accuracy improvement has become influential in the programming languages community, and his more recent work on browser internals is shaping how researchers understand and optimize modern web rendering engines. He is currently developing a textbook on web browsers that aims to synthesize knowledge about browser architecture and implementation.
Dr. Yu Huang is an Assistant Professor in the Department of Computer Science at Vanderbilt University's School of Engineering, with a secondary appointment in the Department of Teaching and Learning at the Peabody School of Education. She is affiliated with the Institute for Software Integrated Systems, the Frist Center for Autism and Innovation, the Vanderbilt Lab for Immersive AI Translation (VALIANT), and the Vanderbilt LIVE Learning Innovation Incubator. Her academic journey began with a BS in Aerospace Engineering from Harbin Institute of Technology in China (2011), followed by an MS in Computer Engineering from the University of Virginia (2015), and culminated with a PhD in Computer Science and Engineering from the University of Michigan in 2021 under Professor Westley Weimer. Dr. Huang's research bridges human cognition and machine intelligence to enhance software development. Her work spans software, hardware, AI, medical imaging (fMRI/fNIRS), eye tracking, and mobile sensing through collaborations with Security, Education, Psychology, and Neuroscience researchers. She leads the MIND Lab (Mixed INtelligence Development for programming lab), investigating programming expertise formation, code comprehension processes, cognitive error patterns, and diversity in programming communities. Her innovative approach combines empirical human studies with AI model development to create more effective programming tools. Her recent publications reveal a growing emphasis on leveraging human attention data to improve code language models, analyzing cognitive biases in security contexts, and examining social factors in technical communication. The research shows strong interdisciplinary connections between neuroscience, psychology, and software engineering, with increasing applications of LLMs in developer tooling. Dr. Huang's work consistently demonstrates how understanding human cognition can inform better AI systems for programming tasks. Dr. Huang has received numerous prestigious recognitions including the 2025 ICPC Vaclav Rajlich Early Career Achievement Award and three ACM SIGSOFT Distinguished Paper Awards (ICSE 2019, FSE 2023, ICSE 2024). Her lab has earned the Best Presentation Award at GI2024, while her students have received the Richard Bennett/Dorothy Danforth Compton Prize scholarship and the C. F. Chen Best Paper award. She actively mentors a diverse team of graduate students (Yifan Zhang, Zach Karas, Zihan Fang, Yueke Zhang, Jiahao Zhang) and undergraduate researchers, with many former students advancing to top institutions (Stanford, Harvard, Duke, UC Berkeley) and organizations (NASA JPL). Her research is supported by a 4-year NSF grant, GitHub Tech for Social Good funding, and the Provost's Faculty Immersion Vanderbilt Grant, enabling comprehensive studies of human-AI collaboration in software engineering. The MIND Lab maintains a strong collaborative culture, frequently working with Professor Kevin Leach's research group and organizing retreats to locations like Radnor State Park and the Great Smoky Mountains. This environment fosters innovation at the intersection of human cognition and software engineering while supporting the professional development of emerging researchers in the field.
Magnus Westerlund is a Senior Lecturer in Information Technology and Director of the Laboratory for Trustworthy AI at Arcada University of Applied Sciences in Helsinki, Finland. His industry background spans telecom and information management, and he holds a doctoral degree in Information Systems from Åbo Akademi University. He actively contributes to the Z-Inspection® network, focusing on ethical AI implementation and governance. Westerlund’s research emphasizes trustworthy AI, cybersecurity, and distributed systems. Key areas include AI regulatory compliance (e.g., EU AI Act), healthcare AI applications, blockchain security, and IoT edge solutions. His work bridges academia and industry, such as the Valohai-CSC collaboration for machine learning infrastructure in Finnish academia. His publications highlight practical AI assessment methods, ethical AI integration, and decentralized technologies. Notable contributions include frameworks for sustainable AI development, privacy-preserving autonomous systems, and smart contract-based IoT security protocols. Westerlund also explores educational innovations, such as integrating large language models (LLMs) into coding education. His research consistently addresses real-world challenges like pandemic-era healthcare AI, edge computing for IoT, and cybersecurity in autonomous systems.
Cuiyun Gao is a Full Professor and PhD Supervisor at the School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen. She has established herself as a prominent researcher in the intersection of artificial intelligence and software engineering. Her educational background includes a PhD from the Chinese University of Hong Kong (completed in 2018), followed by postdoctoral work at CUHK and a Research Fellowship at Nanyang Technological University. She also had a visiting period at University College London supervised by Prof. Mark Harman and Prof. Federica Sarro. Dr. Gao's research primarily focuses on Software Repository Mining, Natural Language Processing, Code Analysis, Large Language Models, Source Code Understanding, User Review Analysis, Vulnerability Detection, and Mobile Advertising Analysis . Her work bridges the gap between traditional software engineering practices and modern AI techniques, particularly in the context of code intelligence and software maintenance. Her recent publications (2024-2025) demonstrate a strong emphasis on Large Language Models for code-related tasks, including code generation, optimization, vulnerability detection, and software engineering applications. Her research shows a clear trend toward addressing practical challenges in integrating LLMs into the software development lifecycle while maintaining code quality and security. Scientific Awards: Distinguished Paper Award at ASE 2023 Best Paper Award of the Track at ICSE 2024 Distinguished Paper Award at ICSE 2024 Dr. Gao actively supervises multiple PhD and Master's students, contributing to the next generation of software engineering researchers. She has served on numerous conference committees including FSE, ISSTA, ICSE, ASE, and SANER. Her research has received significant attention in the software engineering community, with multiple papers published in top-tier venues like FSE, ICSE, ASE, and TSE. Her lab appears to be actively engaged in both theoretical research and practical applications, particularly in the context of WeChat and other industry collaborations, demonstrating strong industry-academia connections.
Chang Xu is a Professor and Ph.D. supervisor at Nanjing University, affiliated with the State Key Laboratory for Novel Software Technology, School of Computer Science, and Institute of Computer Software (ICS). He has been a full-time faculty member since 2010, when he joined as an associate professor and was later promoted to full professor in 2015. Education: Ph.D. from The Hong Kong University of Science and Technology (HKUST) in 2008 (advisor: Prof. S.C. Cheung) M.Eng. from Institute of Software, Chinese Academy of Sciences (ISCAS) in 2003 B.Eng. from University of Science and Technology of China (USTC) in 2000 Research Interests: Professor Xu's research focuses on big data software engineering, intelligent software testing and analysis, and adaptive and autonomous software systems. His recent work centers on constructing and providing runtime support for intelligent software in open environments, with emphasis on inconsistency detection and resolution for environments, and quality assurance for adaptive, concurrent, learning-based, smartphone-based, and spreadsheet-based applications. His work bridges theoretical foundations with practical applications in software engineering, particularly in program analysis, software testing, and self-adaptive systems. Scientific Awards: ACM SIGSOFT Distinguished Paper Award from ICSE 2025 Best Student Paper Award from EUROSYS 2025 ACM Distinguished Member in 2024 Best Paper Award from SOSP 2023 Best Paper Candidate from ISSRE 2022 Yangtze River Scholar by the Ministry of Education in 2021 Multiple ACM SIGSOFT Distinguished Paper Awards from conferences including ASE, ICSE National Science and Technology Progress Award (Second Class) in 2011 Academic Service and Advising: Professor Xu has served on numerous program committees for top software engineering conferences including ICSE, ASE, ESEC/FSE, and ISSTA. He is an editorial board member for several journals including Journal of Computer Science and Technology and Frontiers of Computer Science. He has supervised numerous Ph.D. and MSc students, with research topics spanning program analysis, software testing, self-adaptive systems, and more. His students have gone on to successful careers in both academia and industry. Research Groups: Professor Xu is associated with the SPAR research group at Nanjing University and the CASTLE research group at HKUST, focusing on software analysis, reliability, and testing.
Dr. Brandon A. Boyd serves as Associate Professor and Director of Choral Activities at the University of Missouri's College of Music, holding the Marie M. and Harry L. Smith Endowed Chair. He directs the MU University Singers, Sankofa Chorale, and Choral Union Symphonic Chorus while teaching graduate courses in choral conducting, literature, and arranging. His research focuses on community-building through choral singing, with specific interests in organizing choirs for homeless populations, studying the social and physical effects of choral singing on senior citizens, and creating authentic field experiences for music therapy and choral education students. His work extends internationally through partnerships with Bolivian universities and domestic community initiatives including prison choirs and senior citizen ensembles. As a composer and arranger, Dr. Boyd's works appear in publications by Hinshaw Music, Gentry Publications, GIA, and Kjos Music Press. He curates the 'Brandon A. Boyd Choral Series' with Hinshaw Music and serves as Executive Choral Editor for Gentry Publications. His compositions primarily focus on African-American spirituals and traditional arrangements, often incorporating gospel elements and contemporary rhythmic signatures. Notable performances include collaborations with the London Symphony Orchestra, NDR Elbphilharmonie Orchestra, Nashville Symphony, Missouri Symphony, and St. Louis Symphony, with multiple appearances at Carnegie Hall as conductor, composer, and collaborative pianist. Marie M. and Harry L. Smith Endowed Chair National ACDA Composition Initiative committee member Executive Choral Editor of Gentry Publications Dr. Boyd maintains active community engagement through initiatives like the Santa Fe Desert Chorale's 'Giving Voice to the Voiceless' program, where he served as Composer-in-Residence and created the Interfaith Community Shelter Street Choir for homeless populations. His international work includes conducting workshops at Universidad Católica Boliviana and Universidad Evangelica in Bolivia through Partners of the Americas. He directs significant choral community partnerships including the Tallahassee Senior Choir, RAA Middle School Partnership Choir, and MTC Women's Prison Glee Club, demonstrating his commitment to music's social impact beyond traditional academic settings.
Yoshiko Matsumoto is the Yamato Ichihashi Professor in Japanese History and Civilization and Professor of East Asian Languages and Cultures at Stanford University, with a courtesy appointment in Linguistics. She has been a faculty member at Stanford since 1992, progressing from Assistant Professor to her current distinguished position. Matsumoto also serves as coordinator of the Japanese Language Program and has held significant administrative roles including Chair of the Department of Asian Languages (2003-2005) and Interim Chair of the Department of East Asian Languages and Cultures (2016). Matsumoto earned her Ph.D. in Linguistics from the University of California, Berkeley (1989), following M.A. degrees in Linguistics from UC Berkeley and General and Applied Linguistics from the University of Tsukuba, an M.I.A. in American Studies from the University of Tsukuba, and a B.A. in English Language & Literature from Japan Women's University. Professor Matsumoto's research focuses on linguistic pragmatics from cross-linguistic perspectives, with particular expertise in Japanese language. Her work spans structural and sociocultural aspects of language in use, including noun-modifying clause constructions, honorifics, discourse markers, and the intersection of language with gender and aging. She has pioneered research on conversational narratives of older adults, examining how ordinary framing strategies help individuals navigate difficult experiences. Her current projects explore intergenerational communication through haiku, communicative abilities of people with dementia, and noun-modifying constructions across Eurasian languages. Matsumoto's scholarship consistently bridges theoretical linguistics with practical applications for understanding human communication in diverse social contexts. Matsumoto's recent publications reveal a growing focus on practical applications of linguistic research for social benefit, particularly in intergenerational communication and dementia care. Her work increasingly integrates arts-based approaches, especially haiku poetry, to bridge generational divides and enhance communication with elderly populations. The research shows a consistent trajectory from theoretical linguistic frameworks toward applied, human-centered language studies that address real-world challenges in aging societies, with particular attention to how ordinary language practices help individuals navigate life transitions and difficult experiences. Dean's Award for Distinguished Teaching, School of Humanities and Sciences, Stanford University (2000) Richard E. Guggenhime Faculty Scholar, Stanford University (2000-2003) Violet Andrews Whittier Fellow, Stanford Humanities Center (2019-2020) Faculty Research Fellow, Michelle R. Clayman Institute for Gender Research (2014-2015) Research Fellow, Japan Foundation (2002) Internal Fellow, Stanford Humanities Center (2005-2006) Presidential Fund for Innovation in the Humanities, Stanford University (2009-2011) Professor Matsumoto has mentored numerous students through her teaching in Japanese language and linguistics courses, including specialized offerings on language and aging, points in Japanese grammar, and haiku-based communication. Her research has been supported by prestigious grants from the National Endowment for the Humanities, the Japan Foundation, and Stanford's Presidential Fund for Innovation in the Humanities. She has served on multiple editorial boards including the Journal of Pragmatics since 1992, demonstrating long-standing leadership in her field. Matsumoto has also advised students through individual studies and thesis projects in East Asian Languages and Cultures. Matsumoto leads several collaborative research initiatives including the 'Sharing Conversations' project which examines intergenerational communication through haiku, and research on communicative abilities of people with dementia. Her work often involves interdisciplinary teams spanning linguistics, gerontology, and creative arts, with fieldwork conducted in both Japan and the United States. The 'Noun-Modifying Constructions in Languages of Eurasia' project represents a major international collaboration examining linguistic structures across cultural boundaries. She also directs the 'Language, Old Age and Gender in Japan' project supported by the Stanford University/Japan Foundation, and the 'Difficult Conversations Continue: Memories of the 3.11 Disaster and Bereavement Narratives' project focused on post-disaster communication.
Nalini Iyer is a Professor of English at Seattle University, affiliated with the Department of English and the African and African American Studies Program. She holds the Wismer Professorship and the Theiline Pigott-McCone Endowed Chair in the Humanities. Her research focuses on Global Anglophone Literature, Postcolonial Studies, South Asian and Postcolonial African Literature, and Transnational Feminism. Dr. Iyer earned her Ph.D. in English from Purdue University. She teaches courses such as Literature of India, African Literature, and Asian American Literatures, emphasizing postcolonial perspectives and diasporic narratives. She serves as Editor of the South Asian Review and has held leadership roles in the Modern Language Association and the South Asian Literary Association. Her research explores themes like the hegemony of Anglophone writing, diaspora studies, and Partition Studies. Recent publications include Teaching Anglophone South Asian Diasporic Literature (2024) and articles on Muslim representation in American literature and trauma narratives in South Asian texts. Her work bridges literary analysis with feminist, race, and caste critiques. Awardees of her endowed chairs reflect her scholarly impact. She has authored/co-authored books on South Asian diasporas in the Pacific Northwest, language debates in Indian literature, and postcolonial canons. Her academic contributions span pedagogy, critical biographies, and interdisciplinary collaborations. Dr. Iyer’s advising and grants focus on fostering inclusive literary education and amplifying marginalized voices. She collaborates with institutions globally, contributing to transnational scholarly networks.
Long Nguyen is a Professor of Statistics at the University of Michigan, Ann Arbor, with a courtesy appointment in Electrical Engineering and Computer Science. He is affiliated with the Michigan Institute for Data Science (MIDAS) and the Vietnam Institute for Advanced Study in Mathematics (VIASM). His research focuses on Bayesian nonparametrics, optimal transport, machine learning, and spatiotemporal data analysis. Nguyen holds a PhD in Computer Science from UC Berkeley and has held postdoctoral positions at Duke University and the Statistical and Applied Mathematical Institute. Education: B.Sc. in Computer Science from Pohang University of Science and Technology; M.Sc. in Mathematics from Arizona State University; Ph.D. in Computer Science from UC Berkeley (2007). Research Interests: Bayesian nonparametric methods, optimal transport theory, statistical inference for complex models, and applications in spatiotemporal data, functional data analysis, and hierarchical modeling. He emphasizes developing scalable algorithms and geometric approaches for statistical learning. Editorial Roles : Annals of Statistics Journal of Machine Learning Research SIAM Journal on Mathematics of Data Science Bayesian Analysis Awards : IMS Fellow, ASA Fellow NSF CAREER Award IEEE Signal Processing Young Author Award L. J. Savage Dissertation Award (via student Aritra Guha) Advising & Collaborations : Guided over 20 PhD students and postdocs, many now in academia and industry. Collaborates on projects in AI ethics, music theory, and environmental data science. Active in organizing summer schools in Vietnam on Bayesian statistics and machine learning. Labs & Teams : Co-leads the Statistical Machine Learning reading group at U-M and collaborates with the VIASM on advanced mathematical research in Hanoi.
Trevor E. Carlson is an Assistant Professor at the School of Computing, National University of Singapore (NUS), focusing on high-efficiency microarchitectures, hardware/software co-design, and secure chip design for IoT and server applications. He earned his Ph.D. in Computer Science from Ghent University (2014) and B.Sc./M.Sc. in Electrical & Computer Engineering from Carnegie Mellon University (2002/2003). Research Interests include energy-efficient processors, secure computing platforms, neuromorphic accelerators, and fast simulation methodologies. He co-developed the Sniper Multi-Core Simulator used globally for performance/power evaluation. Scientific Awards : Best Paper Award, International Conference on Embedded Computer Systems (2016) Best Paper Award, International Symposium on Performance Analysis of Systems and Software (2013) Heidelberg Laureate Forum participation (2015) HiPEAC Technology Transfer Award for Sniper Simulator (2013) Current Research involves secure Systems-on-Chip (SOCure project), hardware security for IoT, and simulation methodologies. He leads a lab with researchers working on topics like Capstone for trustless secure memory access and LABS for laser fault injection benchmarks.
Michael Qizhe Shieh is an Assistant Professor in the Department of Computer Science at the National University of Singapore (NUS), affiliated with the Tree and Rock AI Lab (TRAIL). He holds a PhD and Master's from Carnegie Mellon University (Machine Learning and Language Technologies) and a Bachelor's from Shanghai Jiao Tong University's ACM Class. His research focuses on Large Language Models, Deep Learning, and Natural Language Processing, with notable contributions to semi-supervised learning techniques like Noisy Student and UDA, and the RACE benchmark for reading comprehension. Education: PhD in Machine Learning, Carnegie Mellon University (2020) Master's in Language Technologies, Carnegie Mellon University (2018) Bachelor's in Computer Science, Shanghai Jiao Tong University (2016) His research explores robustness, safety, and scalability of AI systems. He has served as Area Chair for top conferences like NeurIPS, ICML, and ICLR. Current research directions include adversarial robustness, LLM self-evaluation, and alignment mechanisms. His lab, TRAIL, emphasizes foundational AI research. Selected contributions include: Developing UDA and Noisy Student techniques for semi-supervised learning Creating the RACE benchmark for exam-based reading comprehension Advancing methods for LLM safety and adversarial defense Prospective students are encouraged to apply to NUS's PhD program for collaborative research opportunities.
Dr. David Wright is a Professor in the Department of English and Technical Communication at Missouri University of Science and Technology (Missouri S&T). He joined the faculty in 2007 after prior roles at NASA’s Education Project, Oklahoma state government, and the software industry. He holds a Ph.D. in Technical Communication (Oklahoma State University, 2007), an M.S. in Higher Education Administration (1996), and a B.S. in Organizational Psychology (1993), all from Oklahoma State University. His research focuses on smart home technology and artificial intelligence, particularly examining human-AI interaction through usability and user experience (UX) testing. He also explores technology diffusion, technical communication practices in emerging technologies, and educational methodologies for technical fields. His work integrates interdisciplinary approaches, blending engineering, sociology, and computer science. Recent publications highlight his contributions to IoT usability, smart home adoption challenges, and the intersection of AI ethics with virtual assistants. He has also authored studies on knowledge graph design, technical documentation in software development, and educational initiatives in computer science and healthcare. Dr. Wright teaches courses in technical writing, usability studies, and web-based communication. His academic service includes curriculum development and advising on technical communication pedagogy. While no specific awards are listed, his extensive publication record reflects sustained scholarly impact in his fields.
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