Dr. Hoontaek Seo serves as Associate Professor of Finance and Chair of the Department of Accounting, Economics, and Finance at Niagara University's Holzschuh College of Business Administration, where he has been faculty since fall 2010. His office is located in Bisgrove Hall Room 354F with office hours Tuesdays and Thursdays 10 a.m.-12 p.m. and Wednesdays 1:30-3:30 p.m. He holds a Ph.D. in Finance from Michigan State University (2009), forming the foundation of his academic expertise. Research focuses on empirical corporate finance mechanisms, particularly security offerings dynamics, corporate governance structures, control systems, and divestiture strategies. His work examines how these elements influence corporate financial decision-making and market valuation processes within empirical frameworks.
Mark Liberman is a Trustee Professor at the University of Pennsylvania , holding appointments in the Department of Linguistics and Department of Computer and Information Science . He serves as Director of the Linguistic Data Consortium and Faculty Director of Ware College House . His career spans linguistics, speech technology, and computational methods. Education: Harvard University (1965-1969), MIT (M.S. 1972, Ph.D. 1975) Professional Experience: AT&T Bell Laboratories (1975-1990), University of Pennsylvania (1990-present) His research interests include: Corpus-based Phonetics : Analyzing speech patterns via large-scale datasets. Clinical Applications : Developing speech biomarkers for neurodegenerative diseases. Tonal Phonology : Studying lexical tone and intonation in languages like Yoruba and Mandarin. Formal Annotation Models : Creating frameworks for linguistic data standardization. Recent publications highlight automated speech analysis, cross-linguistic prosody, and digital biomarkers for conditions like ALS-FTD and Alzheimer’s. His collaborations span computational linguistics , neurology , and cognitive science . Scientific awards include the IEEE James L. Flanagan Award (2017), Antonio Zampolli Prize (2010), and fellowships from the AAAS and Linguistic Society of America . He advises PhD students May Chan and Jonathan Him Nok Lee and contributes to editorial boards for journals like Cognition and Annual Review of Linguistics . His work bridges speech science , language technology , and neurocognitive research .
Ryan Heuser is an Assistant Professor in Digital Humanities at the University of Cambridge, specializing in computational approaches to literary and intellectual history, prosody, and artificial intelligence's impact on language. His work bridges data science, machine learning, and literary studies through digital methodologies. Doctoral training in Eighteenth-Century British Literature, Stanford University (2019) Founding member & Associate Research Director, Stanford Literary Lab Junior Research Fellow, King’s College Cambridge (2019-2022) Research interests span computational modeling of semantic revolutions, large-scale literary field analysis, and the intersection of digital methods with historical and intellectual studies. His book Explorations in the Digital History of Ideas (2023) co-edited with Peter de Bolla exemplifies this approach. Recent publications focus on historical semantics, metrical analysis, and digital mapping of emotions in literature, reflecting his interdisciplinary expertise in natural language processing, network theory, and literary data visualization. Currently leads teaching initiatives at Cambridge Digital Humanities and contributes to computational projects exploring textual rhythms and large language models.
Nicholas Evans is a Distinguished Professor in the Department of Linguistics at the School of Culture, History & Language, Australian National University. He is an ARC Laureate Fellow and serves as Director of the ARC Centre of Excellence for the Dynamics of Language (CoEDL), reflecting his leadership in integrating typology, descriptive linguistics, and cognitive science. His work spans linguistic diversity, endangered languages, and the interplay between language and culture. His research focuses on Australian and Papuan languages, with extensive fieldwork in remote communities. Key interests include linguistic typology, historical and contact linguistics, semantics, and the cognitive underpinnings of grammar. He has published foundational grammars and dictionaries of Kayardild, Bininj Gun-wok, and Dalabon, contributing significantly to the documentation of endangered languages. His recent publications reveal a strong trend in cross-linguistic studies of social cognition (SCOPIC), syntactic typology, and phylogenetic modeling of the Yam languages. These works integrate linguistic, cognitive, and genetic data, highlighting interdisciplinary approaches to understanding language evolution and human diversity. ARC Laureate Fellow Fellow of the Australian Academy of the Humanities (FAHA) Fellow of the Academy of the Social Sciences in Australia (FASSA) Fellow of the British Academy (FBA) Evans supervises research students and leads major projects such as 'The Wellsprings of Linguistic Diversity' and CoEDL, which involve extensive collaboration across institutions and disciplines. His grants include modeling Pacific creoles and phonemic analysis of Tok Pisin. He is also involved in digital archiving initiatives like PARADISEC and the Language Data Commons of Australia, ensuring long-term preservation of linguistic data. He leads and contributes to research teams focused on Southern New Guinea languages, paradigm syncretisms (PARABANK), and cultural heritage preservation. His work emphasizes reciprocal engagement with speech communities and training the next generation of language documenters.
Mari Ostendorf serves as an Adjunct Professor in the Department of Computer Science and Engineering within the College of Engineering at the University of Washington, where she conducts research at the intersection of speech technology and computational linguistics with emphasis on spontaneous speech phenomena. Her educational foundation includes: PhD in an unspecified field, Stanford University (1985) Her research program systematically investigates: Speech Processing: Specializing in spontaneous speech characteristics and prosodic modeling Natural Language Processing: Focusing on conversational speech parsing and stance analysis Computational Linguistics: Integrating linguistic theory with machine learning approaches Prosody: Analyzing idiosyncratic speech patterns for language processing applications Stance Recognition: Developing computational methods for identifying speaker attitude and commitment Her work manifests in significant projects including the LiCORICE Project (2009-2011) as Principal Investigator and the ATAROS Project as Co-Principal Investigator, both advancing automatic spoken language processing through detailed modeling of speech prosody and stance phenomena. Analysis of her publication record reveals a consistent trajectory toward interdisciplinary integration of linguistic theory and machine learning for spoken language understanding, with particular emphasis on non-lexical cues and discourse markers in conversational contexts that bridge computational and cognitive approaches to language processing. No scientific awards were mentioned in the provided documentation. Her advising record includes PhD candidates Jeremy Kahn (2010 dissertation on conversational speech parsing) and Esther Le Grézause (2017 dissertation on stance expression). Her grant portfolio features the LiCORICE Project (2009-2011, PI with Emily M. Bender and Mark Zachry) and the ATAROS Project (Co-PI with Richard Wright and Gina Levow), demonstrating sustained research funding in speech technology. Her research operates within an interdisciplinary framework connecting computer science and linguistics, evidenced by collaborations spanning departments and contributions to dissertation defenses in the Linguistics program at the University of Washington.
Felicity Meakins is a Professor of Linguistics at the University of Queensland, affiliated with the School of Languages and Cultures. She specializes in documenting First Nations languages in northern Australia, focusing on language contact processes, revitalization, and the impact of English on Indigenous languages. Her work bridges academic research and community engagement, including consulting on Native Title claims and language revitalization programs. Education: She studied at the University of Queensland between 1995–2001, completing her PhD in 2008. Prior to her academic career, she worked as a community linguist with Diwurruwurru-jaru Aboriginal Corporation (2001–2004) and as a PhD researcher with the Aboriginal Child Language Project (2004–2008). Research Interests: Meakins explores language contact, mixed languages, and Indigenous knowledge systems. Her projects include the 'Dingo Lingo' study tracing canine terminology across Australia and co-authored works like Tamarra: A Story of Termites on Gurindji Country (2023) and Understanding Linguistic Fieldwork (2018). She has compiled dictionaries and grammars for languages such as Gurindji, Bilinarra, and Mudburra. Grants & Recognition: Recipient of the Eureka Award (2021), LSA’s Hale Award (2021), and a Fellow of FASSA/FAHA. She led the UQ node of the ARC Centre of Excellence for the Dynamics of Language (2022). Labs/Teams: Collaborates with the Language Data Commons of Australia (LDaCA) and Indigenous communities in Northern Territory projects like the Wave Hill Walk-Off documentation.
Ching Kwan Lee is a Professor of Sociology at the University of California, Los Angeles (UCLA). Her work focuses on global and comparative issues, including labor politics, political sociology, decolonization, and the dynamics of Chinese capitalism. She is renowned for her trilogy on Chinese labor and global expansion, including Gender and the South China Miracle , Against the Law , and The Specter of Global China . Lee has also authored groundbreaking studies on Hong Kong’s decolonization struggles and African-China relations. Education: PhD in Sociology from the University of California, Berkeley. Research Interests : Globalization and its social impacts Comparative labor movements and protest dynamics Decolonization and postcolonial state formations Sino-African economic and labor relations Hong Kong’s political trajectory and transnational activism Her recent work explores resistance to 'global China,' including mass mobilizations in Hong Kong documented in Forever Hong Kong: A Global City’s Decolonization Struggle (2025). She co-edits the Cambridge Elements in Global China and leads the Global Hong Kong Studies @UC initiative. Awards & Recognition : 2024 Distinguished Career in Political Sociology Award Multiple book prizes for The Specter of Global China Fellowships at Stanford’s Center for Advanced Study and Princeton’s Institute for Advanced Study Grants & Initiatives : Lead researcher on NSF grants studying platform capitalism and labor in China Initiated comparative projects on Brazil, India, China, and South Africa ( Southern Interregnum ) Co-editor of volumes on Hong Kong’s Umbrella Movement and global labor studies
Matthew Louis Mauriello is an Assistant Professor in the Department of Computer and Information Sciences at the University of Delaware , where he directs the Sensify Lab . He holds a PhD in Computer Science from the University of Maryland (2018) and completed postdoctoral work at Stanford University (School of Medicine, 2020; School of Public Policy & Environmental Engineering Department, 2019). Research interests span Human-Computer Interaction (HCI), Ubiquitous Computing, and User-Centered Design with applications in: Sustainability Human-Building Interaction Wearable Technology Personal Informatics Educational Game Design Mental Health Interventions Recent publications highlight trends in stress monitoring (skin-like biosensors, workplace wellbeing), energy auditing (thermography systems), and educational technology (block-based programming tools for teachers). His work appears in ACM CHI, ACM Human-Computer Interaction, and Building and Environment. Scientific awards include: Best Paper Honorable Mention, CHI 2016 Best Paper Honorable Mention, CHI 2015 Best of WebSci'18 Teaching at University of Delaware encompasses courses like Educational Game Design Operating Systems Advanced Web Technologies Computing for Social Good with a focus on project-based learning and systems thinking.
Andrea Arpaci-Dusseau is the Susan Beth Horwitz WARF Professor of Computer Sciences and Catherine A. Erickson Professor in the School of Computer, Data & Information Sciences at the University of Wisconsin-Madison. She has been a professor at UW-Madison since January 2000 and currently serves as Graduate Advising Chair for the Computer Sciences Department. Her research focuses on computer systems with primary emphasis on file and storage systems, but also making significant contributions in distributed systems, virtualization, and scheduling. According to csrankings.org, she has published the fourth-most papers in premier systems conferences (SOSP and OSDI) and the most at the top file and storage conference (FAST). Professor Arpaci-Dusseau's recent publications demonstrate continued leadership in storage systems research, with increasing focus on cloud architectures, persistent memory technologies, and system reliability. Her work bridges theoretical foundations with practical implementations, consistently addressing real-world challenges in modern computing environments. ACM SIGOPS Mark Weiser Award 2018 (highest honor in systems field) UW-Madison Van Hise Outreach Teaching Award 2017 Multiple Best Paper awards at FAST, SOSP, OSDI, and EuroSys conferences Carolyn Rosner Award for Excellence in Teaching (2010, 2017) Co-chaired major conferences including USENIX ATC '04, FAST '07, OSDI'18, and SOSP'24 Professor Arpaci-Dusseau has co-advised 28 Ph.D. students and is deeply committed to educational outreach through the CaTaPuLT project, which connects UW-Madison students with K-12 schools to teach computational thinking using Scratch. This initiative has reached hundreds of students across Madison and earned her significant recognition for teaching excellence. She leads the Arpaci-Dusseau Systems Lab (ADSL) and is involved with the Wisconsin Institute on Software-defined Datacenters in Madison (WISDoM), where her research group continues to advance state-of-the-art solutions in computer systems.
Sunita Sarawagi is a Professor at Computer Science and Engineering , IIT Bombay, and a member of AI Labs@CSE . She is also associated with the Center for Machine Intelligence and Data Science (CMInDS), which she founded in 2020. Education: PhD in Computer Science from UC Berkeley (Thesis: Query Processing in Tertiary Memory Databases), BTech in Computer Science from IIT Kharagpur Research Interests span machine learning , data analytics , graphical models , and structured learning , with applications in text segmentation, sequence modeling, domain adaptation, and human-in-the-loop systems. Her publications reveal a strong focus on integrating data mining with database systems , temporal data analysis , and information extraction using probabilistic methods. Professional Activities include serving on the IEEE John Von Neumann Medal committee (2017-), VLDB 2011 Research Track Co-chair , and multiple program committee roles at top conferences like ICML, KDD, and SIGMOD. Labs & Teams : Leads the SS Lab , a research group focused on probabilistic graphical models, sequence modeling, and data integration techniques.
Elizabeth McCracken is a Professor in the College of Liberal Arts at the University of Texas at Austin, where she teaches creative writing courses including Advanced Fiction Workshop (CRW 355F), Literature for Writers (E 380F), and Fiction Writing (CRW 325F). She also teaches in the low residency MFA program at Bennington College. McCracken received her M.F.A. from the University of Iowa in 1990. Her academic career has been distinguished by numerous grants and fellowships from prestigious organizations including the Guggenheim Foundation, the National Endowment for the Arts, and the Radcliffe Institute for Advanced Study. Her creative interests focus on Creative Writing , particularly Fiction , Short Stories , and Autobiographical Writing . McCracken's work explores complex human relationships, grief, memory, and the transformative power of storytelling. Her writing is characterized by its emotional depth, wit, keen observation of human nature, and ability to blend the comic with the heartbreaking. McCracken's publications have established her as a significant voice in contemporary American literature. Her work has been widely recognized for its originality and emotional resonance, appearing in prestigious collections such as The Best American Short Stories, The Pushcart Prize, and The O. Henry Prize Stories. Winner of The Story Prize for Thunderstruck & Other Stories (2015) Finalist for the National Book Award for The Giant's House (1996) Named one of the 20 Best Young American Novelists by Granta Recipient of grants from the Guggenheim Foundation, NEA, American Academy in Berlin, and other prestigious organizations As an educator, McCracken has mentored numerous writing students through her positions at the University of Texas and Bennington College. Her teaching emphasizes both technical craft and emotional authenticity, encouraging students to find their unique voices while developing strong writing techniques. Her 2023 novel The Hero of This Book has been named a Top Ten Best Book of the Year by Time and People magazines, further cementing her reputation as one of America's finest contemporary writers.
Gierad Laput is a Senior Engineering Manager at Apple, leading the Perception and Interaction Engineering organization under Machine Intelligence Neural Design (MIND) at Apple AI/ML (AIML). He is also an Adjunct Professor at Carnegie Mellon University's School of Computer Science and Human-Computer Interaction Institute. His research sits at the intersection of sensing systems, interactive technologies, and machine learning, with applications in ambient intelligence, wearables, and AI-driven interactive experiences. Ph.D. in Computer Science from Carnegie Mellon University Founding member of CMU's Future Interfaces Group Former Google Ph.D. Fellow, Disney Imagineer, and recipient of 10 Best Paper Awards/Nominations His research agenda at Apple leverages cutting-edge hardware to develop multimodal ML systems for vision, audio, and motion sensors, enabling features like head gesture detection for AirPods, Apple Intelligence integrations, and health monitoring tools. Recent collaborative projects include Vision Pro hand interaction systems and WatchOS updates for cycling/fall detection. Key research areas include human-computer interaction , machine learning for sensor fusion , and smart environment sensing . Over 35 publications cover transformative technologies like ViBand (bio-acoustic sensing), EM-Sense (touch recognition), SkinTrack (arm as touchpad), and ElectroDermis (stretchable electronics). Scientific honors include: Fast Company Innovation by Design Award (2017) Google PhD Fellowship (2018) Swartz Entrepreneurial Fellowship (2018) Best Paper Awards at ACM UIST (2016) and ACM CHI (2015) As an educator, he has taught courses at CMU and the University of Michigan on on-device machine learning , signal processing , and human-centered design . His lab has mentored numerous researchers now pursuing PhDs at MIT, UW, CMU, and Northwestern.
Mark Y. Liberman is the Christopher H. Browne Distinguished Professor of Linguistics and Trustee Professor at the University of Pennsylvania. He holds a joint appointment in the Department of Linguistics and the Department of Computer and Information Science. His roles include Director of the Linguistic Data Consortium (LDC), Faculty Director of Ware College House, and former Director of the Institute for Research in Cognitive Science. Education: A.B. in Linguistics and Applied Mathematics from Harvard University (1965–1969), M.S. (1972) and Ph.D. (1975) in Linguistics from MIT. Research focuses on corpus-based phonetics, clinical linguistics applications, tonal phonology, formal models for linguistic annotation, and computational linguistics. He explores speech production, prosody, and interdisciplinary topics like language evolution and neurobiology of speech. Recent articles highlight advancements in speech biomarkers for neurodegenerative diseases, autism analysis, and computational linguistics. Awards include Fellowships from the AAAS and Linguistic Society of America. He advises graduate students and leads large-scale language resource initiatives like LDC, contributing to open-access linguistic datasets. Labs/Teams: Linguistic Data Consortium (LDC), Institute for Research in Cognitive Science (IRCS), and collaborations in computational linguistics and neuroscience.
Yarin Gal is an Associate Professor of Machine Learning at the University of Oxford's Department of Computer Science and a Tutorial Fellow at Christ Church College. He is also a Turing AI Fellow at the Alan Turing Institute and Director of Research at the UK Government’s AI Safety Institute. He leads the Oxford Applied and Theoretical Machine Learning (OATML) Research Group, focusing on Bayesian deep learning, AI safety, and uncertainty quantification. Education PhD in Uncertainty in Deep Learning (2016) Research Interests His research integrates Bayesian methods with deep learning to address challenges in AI safety , uncertainty quantification , and robustness . Key areas include: Bayesian neural networks and approximate inference Uncertainty estimation in deep learning AI safety and interpretability Applications in autonomous driving, medical imaging, and NLP Publications & Trends His recent work spans Bayesian optimization , adversarial robustness , and continual learning . Notable contributions include Targeted Dropout for model pruning, Uncertainty in Autonomous Driving , and theoretical studies on adversarial examples in Bayesian networks. Awards & Honors Turing AI Fellow Teaching & Supervision He has taught Advanced Machine Learning , Uncertainty in Deep Learning , and contributed to NASA's Frontier Development Lab. His current students include Kelsey Doerksen, Gunshi Gupta, and Shreshth Malik. Labs & Teams He leads the OATML Group , a multidisciplinary team advancing theoretical and applied machine learning, with a focus on safety and interpretability in AI systems.
Dawn Song is a Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley, affiliated with multiple research centers including the Berkeley Artificial Intelligence Research Lab (BAIR) and the Berkeley Center for Responsible, Decentralized Intelligence (RDI). She holds leadership roles in AI safety, cybersecurity, and blockchain research. Her work bridges machine learning, security, and distributed systems, with notable contributions to formal verification, privacy-preserving technologies, and AI governance. Education: Ph.D. (2002) and M.S. (1999) in Computer Science from UC Berkeley and Carnegie Mellon University, respectively. She previously served as an Assistant Professor at Carnegie Mellon University before joining UC Berkeley in 2007. Research Interests: Dawn's work focuses on AI safety, cybersecurity, and the ethical implications of frontier AI. She explores topics such as large language model vulnerabilities, zero-knowledge proofs, blockchain security, and policy frameworks for AI governance. Her research combines theoretical rigor with practical applications, addressing challenges in secure systems, adversarial machine learning, and privacy-preserving computation. Publications: Her recent work includes groundbreaking studies on LLM memorization, smart contract decompilation, and AI agent cybersecurity evaluation. She also leads initiatives like the Singapore Consensus and California Report on AI safety priorities, emphasizing global collaboration in risk mitigation. Notable Awards: MacArthur Fellowship (2010), ACM Fellow (2019), IEEE Fellow (2019) Advising & Grants: She advises projects on AI policy and cybersecurity, securing grants from NSF, DARPA, and industry collaborations. Her lab develops tools like CyberGym for evaluating AI agents and zkPyTorch for secure machine learning. Labs & Teams: Her research groups at UC Berkeley focus on cutting-edge projects in AI safety, blockchain, and cybersecurity, collaborating with industry leaders and policymakers to advance both technical and ethical standards.
