Bridget Buoniconti serves as Dean of Students, Chief Conduct Officer, and Title IX Deputy Coordinator at Regis College. She joined the institution in 2014 as Assistant Director of Residence Life, later advancing to Director of Residence Life and Associate Dean of Student Affairs before assuming her current leadership roles. A graduate of Boston College with bachelor’s and master’s degrees in English and higher education, she earned her doctorate in Higher Education Leadership from Regis College in 2023. Education: Bachelor’s in English and Secondary Education, Boston College Master’s in English Literature and Higher Education (Student Affairs concentration), Boston College Doctorate in Higher Education Leadership, Regis College (2023) Her work focuses on fostering student development through academic, social, and spiritual support systems. As a member of the First-Year Seminar faculty, she combines teaching and advising to enhance student retention and engagement. She actively develops campus programs, supervises the Department of Residence Life, and champions inclusivity as a Pride Fan. Bridget’s leadership extends to crisis management, including overseeing temporary on-campus housing initiatives for commuter students during exams and participating in institutional updates to public health protocols.
Geoffrey Pleiss is an Assistant Professor in the Department of Statistics at the University of British Columbia's Faculty of Science. He is also a CIFAR AI Chair at the Vector Institute and an inaugural member of CAIDA's AIM-SI (AI Methods for Scientific Impact) cluster. His work bridges statistical theory, machine learning, and computational methods with applications across various scientific domains. Pleiss received his PhD from the Computer Science department at Cornell University in 2020, where he was advised by Kilian Weinberger and worked closely with Andrew Gordon Wilson. Prior to his faculty position at UBC, he was a postdoctoral researcher at Columbia University with John P. Cunningham. His research focuses on the intersection of deep learning and probabilistic modeling, particularly on developing heuristic and approximate notions of uncertainty from machine learning models. His work has significant implications for reliable and optimal decision-making in experimental design and scientific discovery. Major research thrusts include neural network uncertainty quantification, Bayesian optimization, Gaussian processes, and ensemble methods. Pleiss develops theoretical frameworks while maintaining strong connections to practical applications across scientific domains. An analysis of his recent publications reveals a strong focus on uncertainty quantification in deep learning models, with particular attention to the limitations and capabilities of ensemble methods in the era of overparameterized models. His work increasingly addresses practical challenges in Bayesian optimization for scientific discovery, especially in materials science. There's also a growing emphasis on computational efficiency in Gaussian process methods, reflecting his commitment to making advanced statistical techniques accessible for real-world applications. CIFAR AI Chair Pleiss currently advises several graduate students including Donney Fan (PhD, Computer Science), Tim G. Zhou (MSc, Computer Science), Zachary Lau (MSc, Statistics), Nathan Cantafio (BSc, Statistics), and Tristan Cinquin (Research Intern at Vector Institute). His research is supported by multiple funding sources including his CIFAR AI Chair position, which provides significant research resources for advancing machine learning methodologies with scientific impact. Pleiss co-created and maintains GPyTorch, a highly efficient and modular implementation of Gaussian processes in PyTorch designed for speed, modularity, and prototyping. He is also involved with CoLA (Compositional Linear Algebra), a library for structured linear algebra operations in JAX and PyTorch that enables fast linear algebra computations by automatically exploiting matrix structure.
I-Hong Hou is a Professor in the Department of Electrical and Computer Engineering at Texas A&M University, part of the College of Engineering. He holds a B.S. in Electrical Engineering from National Taiwan University (2004), and M.S./Ph.D. in Computer Science from the University of Illinois, Urbana-Champaign (2008/2011). His research focuses on wireless networks, cloud/edge computing, and machine learning with notable contributions to real-time systems and network optimization. Education : B.S., Electrical Engineering, National Taiwan University, 2004 M.S., Computer Science, University of Illinois at Urbana-Champaign, 2008 Ph.D., Computer Science, University of Illinois at Urbana-Champaign, 2011 Research Highlights : Hou’s work emphasizes Age of Information (AoI) , distributed learning, and scheduling algorithms for edge computing. He has pioneered frameworks integrating machine learning with network protocols, such as deep reinforcement learning for restless bandits and second-order optimization for wireless systems. His methods address real-time communication challenges in multi-hop networks and dynamic environments. Awards : Best Paper Awards at ACM MobiHoc (2017, 2020) Best Student Paper, WiOpt 2017 C.W. Gear Outstanding Graduate Student Award, UIUC Advising & Grants : Advised PhD student Siqi Fan (graduated 2024). His research has been supported by grants exploring edge-cloud reconfiguration, real-time video delivery, and neural Whittle index networks. Recent work includes optimizing freshness of information in multi-user systems and developing threshold-optimal policies for complex decision-making. Labs/Teams : Leads the Computer Engineering and Systems Group (CESG) at Texas A&M, collaborating on projects blending networking, machine learning, and distributed systems.
Gyu Tag Lee is a Professor in the International Studies Department at George Mason University Korea, specializing in Cultural Studies with a focus on K-Pop, media criticism, and the globalization of culture. He holds a PhD in Cultural Studies from George Mason University (2013), an MA in Communication from Seoul National University, and a BA in English Language and Literature from the same institution. Having completed three years of military service in the Republic of Korea Air Force, he has been teaching at George Mason University Korea since 2014. His research interests span Cultural Studies, Media Criticism, Popular Music, K-Pop and Hallyu, Globalization of Culture, and Music Industry studies. Professor Lee is particularly recognized for his expertise on K-Pop's global expansion, cultural appropriation issues within the industry, and the relationship between Korean cultural identity and global pop music markets. His extensive publications reflect a consistent focus on K-Pop's evolution, from its historical roots to contemporary challenges and future directions. His work examines the tension between local Korean identity and global appeal, the role of digital platforms in fan engagement, and the cultural politics surrounding K-Pop's international success. Professor Lee's research demonstrates how K-Pop functions as both a cultural product and economic phenomenon with significant implications for understanding transnational cultural flows. As a respected commentator in the field, he serves on the selection committee for the Korean Music Awards and has been featured in numerous international media outlets including Wall Street Journal, South China Morning Post, Netflix's documentary Explained, and major Korean broadcasters such as KBS, MBC, and SBS. His insights on cultural appropriation in K-Pop have been particularly influential in shaping discussions about cultural sensitivity and global cultural exchange. Professor Lee teaches courses including Media Criticism, Globalization and Culture, K-Pop, Hallyu, and Korean Society, and Korean Popular Culture in a Global World, bringing his scholarly expertise directly into the classroom to educate the next generation of cultural critics and analysts.
Loli Kim is a Lecturer on Modern Korea at the Faculty of Asian and Middle Eastern Studies, University of Oxford, with a Leverhulme Postdoctoral Research Fellowship (2022–2025). She specializes in cross-cultural multimodal analysis of Asian communication systems, particularly Korean cinema, folklore, and representation in media. Education: DPhil in Asian and Middle Eastern Studies (2019–2022), University of Oxford Research Focus: Multimodal discourse analysis, foodscaping theory, haenyeo women’s communication Editorial Roles: Assistant Editor of European Journal of Korean Studies; General Editor of 'Foodscaping Asia' series Her work develops the Segmented Film Discourse Representation Structures (SFDRS) methodology for analyzing Korean films' narrative conventions, including violence in revenge cinema and socio-pragmatic dimensions of fashion. She collaborates globally as a visiting lecturer and conference organizer. Kimi’s recent publications examine multimodal translation gaps, cultural representation in children’s literature, and the sociocultural implications of foodscaping. She has delivered keynote talks at institutions including Edinburgh University and SOAS, and co-organizes the Translating Squid Game talks series.
Jean-Claude Besse is a Lecturer in the Department of Physics at ETH Zürich, specializing in superconducting circuits and quantum optics. His research focuses on quantum computing, microwave photonics, and artificial atoms. Research Interests: Besse works on the fabrication of superconducting circuits, modular quantum computing processors, and microwave quantum optics using artificial atoms. His work includes single-photon detection, parity measurements, entanglement stabilization, and quantum networking. He has developed technologies like high-fidelity multiplexed readout and tunable ZZ gates. Key Contributions: Besse led breakthroughs in non-destructive single-photon detection, deterministic remote entanglement, and loophole-free Bell inequality violations. His research enables error-corrected quantum communication protocols and scalable microwave quantum systems. Publications Trends: Recent articles emphasize modular quantum architectures, entanglement stabilization, and microwave photon engineering. Topics include cluster state generation, defect mode mitigation, and reinforcement learning for quantum feedback systems. Labs & Teams: Affiliated with the Laboratorium für Festkörperphysik at ETH Zürich, Besse contributes to advancing superconducting quantum technologies and microwave quantum optics.
Associate Professor Oliver Diessel is a faculty member at the University of New South Wales (UNSW) within the School of Computer Science and Engineering. He has been actively teaching and conducting research at UNSW since at least 2000, with teaching experience spanning various computer architecture and digital systems courses. Dr. Diessel completed his education at the University of Newcastle, Australia, earning a B.E. (Computer, Hons) and B.Math. in 1991, followed by a PhD in 1998. His academic career has focused on reconfigurable computing systems and computer architecture. His primary research interests center around the design, test, and implementation of digital systems in reconfigurable logic devices called Field-Programmable Gate Arrays (FPGAs). Specifically, he focuses on dynamically reconfigurable digital systems where circuits can be modified while the system is operational. His work aims to develop architectures, design methods, and tools that enhance the benefits and reduce the costs of reconfigurable systems. Current research projects include fault-tolerant FPGA-based systems for space applications and fine-grained accelerators for heterogeneous devices. Dr. Diessel has published extensively with 2 books, 1 book chapter, 16 journal articles, 67 conference papers, 1 edited conference proceedings, and 7 conference presentations to his credit. His publications reflect a strong emphasis on reconfigurable technology, computer architecture, and electronic design automation. As a supervisor, Dr. Diessel currently mentors two MPhil students: Tong Wu working on Runtime reconfiguration and Junning Fan working on Fault-tolerance of FPGA-based applications. He has previously supervised six students to completion. His supervision interests include reconfigurable technology and systems, electronic design automation, and computer architecture. Dr. Diessel is an active member of the professional community, serving on the Editorial Board of ACM Transactions on Reconfigurable Technology and Systems and as an IEEE Member. He has taught numerous courses including Configurable Systems (COMP4601), Computer Architecture (COMP3211, COMP4211), Digital Systems (COMP3222), and FPGA Implementation of Digital Systems using Verilog.
Professor Paul Fearnhead is a leading academic in Statistics at Lancaster University 's School of Mathematical Sciences . His research focuses on Bayesian and Computational Statistics , with applications in Anomaly Detection , Continuous-time Markov Processes , and Changepoint Analysis . Department: Mathematics and Statistics Academic Rank: Professor Email: p.fearnhead@lancaster.ac.uk His work bridges theoretical statistics and computational efficiency, notably through pruning techniques for change detection and novel Monte Carlo methods. Current projects include AI Hub initiatives, probabilistic AI foundations, and real-time anomaly detection in streaming data. Research outputs span Bayesian Analysis , Time Series Modeling , and Scalable Statistical Algorithms , with applications in fields like astronomy and epidemiology. Recent publications emphasize simulation-based composite likelihoods and efficient distributed changepoint detection. Scientific contributions include leadership roles in the STOR-i Centre for Doctoral Training and Data Science Institute (DSI) projects such as CoSInES and Statscale. He supervises PhD students including Dylan Bahia, Yuntang Fan, and Ziyang Yang.
Dr. Stephen Reysen serves as Professor in the Department of Psychology and Special Education within the College of Education and Human Services at East Texas A&M University, where he has held progressively senior positions since 2009. His expertise centers on social psychology with specialized focus on fan communities and identity formation across diverse cultural contexts. His educational foundation includes: Ph.D. in Social Psychology from University of Kansas (2009) M.A. in Psychology from California State University, Fresno (2005) B.A. in Psychology from University of California, Santa Cruz (2003) Reysen's research program investigates fanship phenomena through rigorous examination of anime enthusiasts, furries, and bronies (My Little Pony fans), revealing universal psychological mechanisms across seemingly disparate communities. His work on global citizenship explores how transnational identities develop, while his foundational research on collective identity examines its impact on social behavior and attitudes. Methodologically, he employs longitudinal designs and cross-cultural comparisons to uncover deep psychological patterns. Publication analysis shows consistent thematic focus on identity expression within specialized communities, with increasing methodological sophistication from descriptive studies (2016 furry research) to comprehensive theoretical frameworks (2018 global citizenship review) and finally to in-depth community analyses (2019 bronies study). This trajectory demonstrates growing influence in applying social psychology to unconventional cultural domains. His research excellence is recognized through: Chuck Arize Excellence in Research Award (2020) Professor of the Year honor (2017) Dual research awards including Provost Award and Outstanding Researcher (2012) Reysen actively mentors undergraduate researchers through PSY 413 Research Apprenticeship, encouraging early lab involvement. His current longitudinal study on anime fans represents significant grant-funded work through the International Anthropomorphic Research Project, with future expansion planned across multiple fandoms. He teaches core courses including Social Psychology (his specialty), Group Dynamics, and Doctoral Dissertation supervision. He co-directs the International Anthropomorphic Research Project and leads the multi-year anime fan longitudinal study, building collaborative teams that bridge academic research with community engagement in specialized fan cultures.
Dr. Xin Fan is a Teaching Professor in Modern Chinese History at the University of Cambridge's Faculty of Asian and Middle Eastern Studies (AMES). He also serves as a Fellow and Director of Studies at Lucy Cavendish College and Director of Studies at Robinson College. A global historian, Fan specializes in intellectual history, historiography, and worldviews of twentieth-century China. His research explores the intersections between foreign knowledge, nationalism, and knowledge production in non-Western contexts. He co-edits the SAGE Handbook of Interpreting Chinese History and has authored major works like Global History in China (2024) and World History and National Identity in China (2021). His current projects include studies on emotions and nationalism, as well as the global rise of higher education. Fan has taught at universities in Europe and the U.S., focusing on courses about Chinese cultural and historical contexts. His work bridges global and national perspectives, emphasizing how political consciousness shapes historical narratives. Education & Career: Fan has studied and worked in China, the U.S., Germany, and the UK. While formal academic credentials are not detailed, his career trajectory reflects extensive international scholarly engagement. Research Interests: Fan’s expertise spans intellectual history, nationalism, global historiography, and the sociology of knowledge. He examines how cultural and political conditions influence knowledge production in China, particularly regarding world history, emotional politics, and cross-cultural reception of antiquity. His work challenges Eurocentric frameworks and explores non-Western historiographical traditions. Publications: Fan has authored monographs, co-edited volumes, and published widely in journals such as Global Intellectual History and Contributions to the History of Concepts . His book reviews appear in prominent journals like Journal of Asian Studies and Frontiers of History in China . Teaching & Leadership: Fan teaches undergraduate courses on Chinese history and culture at AMES. He directs studies at two Cambridge colleges, fostering academic mentorship in Asian and Middle Eastern Studies.
Alexis Blanchet is a Professor at the Université Sorbonne Nouvelle, holding the rank of Maître de conférences Hors Classe since 2022. He serves as Deputy Director of the Cinéma et Audiovisuel department and directs the university's vidéoludothèque. His research focuses on the economic and cultural history of the video game industry in France, intersections between cinema and digital media, and interactive narrative forms. Key roles: Member of IRCAV research institute, former director of the CAV master's program. Research interests include game studies, transmedia storytelling, and media industries analysis. Published extensively including Une Histoire du Jeu Vidéo en France and Lire les Magazines de Jeux Vidéo . Active in academic governance and public outreach through conferences, media appearances, and collaborative projects.
Xiaoyao Fan is an Assistant Professor of Engineering at Dartmouth College, specializing in image guidance systems for neurosurgery and spine surgery. His work focuses on improving intraoperative imaging accuracy through computational modeling, stereovision, and ultrasound technologies. He collaborates with the Center for Surgical Innovation (CSI) at Dartmouth-Hitchcock Medical Center (DHMC) and has contributed to over 400 surgical cases involving real-time imaging and feedback systems. Education: B.E. in Electrical Engineering, Tsinghua University (2007) Ph.D. in Biomedical Engineering, Dartmouth College (2012) Research Interests: His research emphasizes minimizing surgical errors via real-time brain deformation compensation, spine motion correction, and intraoperative imaging systems. Techniques include stereovision, 3D ultrasound, and machine learning for image registration and navigation. Key applications include open and minimally invasive neurosurgical procedures. Publications: His work spans stereovision systems for spinal surgery, brain shift compensation algorithms, and intraoperative ultrasound registration. Recent contributions address human feasibility and porcine model validation of surgical navigation tools. Grants & Labs: Collaborates with Medtronic on integrating updated imaging into navigation systems. Active in the CSI DHMC lab, focusing on clinical translation of real-time imaging solutions. Teaches ENGS 111: Digital Image Processing. Labs & Teams: Works within Dartmouth’s engineering and medical collaboration networks, advancing surgical precision through interdisciplinary research.
Xiaolei Fan is an Associate Professor in the Department of Chemical Engineering at The University of Manchester. He holds a BEng in Environmental Engineering from Jilin Institute of Chemical Technology (2003), an MRes in Chemical Engineering from East China University of Science and Technology (2006), and a PhD in Continuous Flow Heterogeneous Catalysis from the University of Bath (2010). His research focuses on nonthermal plasma catalysis, CO2 conversion, catalytic biorefinery, and zeolite-based catalysts. He has contributed to over 180 publications, supervised 20+ students, and led projects like the EU-funded SPACING initiative for biofuel production. Research interests include porous materials, reaction engineering, and process intensification through structured reactors/catalysts. He chairs the RSC Heterogeneous Catalysis committee and has organized conferences like the International Conference on Environmental Catalysis. His work aligns with UN Sustainable Development Goals, particularly in clean energy and sustainable chemistry. Education: BEng (Environmental Engineering), Jilin Institute of Chemical Technology, 2003 MRes (Chemical Engineering), East China University of Science and Technology, 2006 PhD (Chemical Engineering), University of Bath, 2010 Awards: Lee Hsun Lecture Award (2018) Zhenxing Scholar Professor Award (2018) Outstanding Achievement Recognition (2018) Grants/Projects: SPACING: Sustainable Production of ACrylic Acid from Renewable Waste Glycerol (2021–2024) Labs/Teams: Catalysis and Porous Materials Group at The University of Manchester
Geoff Pleiss is an Assistant Professor in the Department of Statistics at the University of British Columbia (UBC), affiliated with CAIDA's AIM-SI cluster. He is also a Canada CIFAR AI Chair and faculty member at the Vector Institute. His research bridges deep learning and probabilistic modeling, focusing on uncertainty quantification, Bayesian optimization, Gaussian processes, and ensemble methods. Pleiss earned his PhD in Computer Science from Cornell University (2020), followed by a postdoc at Columbia University. He holds multiple awards, including the AISTATS Top Reviewer and NeurIPS recognitions. His work emphasizes scalable algorithms and open-source contributions, such as the GPyTorch library. Pleiss advises students in Computer Science and Statistics, including Donney Fan (PhD), Tim G. Zhou (MSc), and others. He teaches advanced courses like STAT 547U (Deep Learning Theory) and STAT 520P (Bayesian Optimization). Grants include NSERC Discovery and New Frontiers in Research funding. Pleiss collaborates on interdisciplinary projects, such as astrophysical discovery via machine learning, and actively participates in academic service and outreach. Education: PhD in Computer Science, Cornell University (2020) MSc in Computer Science, Cornell University (2018) BSc in Engineering (Computing with Applied Mathematics), Olin College (2013) Key Research Themes: Uncertainty-aware decision-making with neural networks Scalable Gaussian processes and Bayesian optimization Ensemble methods and their theoretical limitations Recent Grants: NSERC Discovery Grant (2024) New Frontiers in Research Fund (2025, co-PI) His publications span foundational theory to applied machine learning, with over 14,500 citations. He actively mentors students through research internships and advises on open-source software development. Pleiss frequently presents at top conferences and collaborates with industry partners like Microsoft and ASAPP.
Miguel Ángel Bernal Merino serves as a Part-Time Lecturer in the Department of Modern Philology, Translation and Interpretation at the University of Las Palmas de Gran Canaria. Concurrently, he acts as convener of the MA in Translation at the University of Roehampton in London, managing its Specialised Translation, Audiovisual Translation, and Intercultural Communication pathways since 2005. His academic profile bridges theoretical research and industry application in localization disciplines. PhD in The Localisation of Video Games, Imperial College London MSc in The Localisation of Multimedia Interactive Entertainment Software, Imperial College London Certificate in Software Localisation, University of Limerick CELTA, University of Cambridge MPhil in Lip-Synched Dubbing, Universidad de Alicante MA in Hispanic Literature, University of Rhode Island BA in English & Spanish Linguistics, Universidad de Alicante Bernal Merino's research pioneers the expansion of Translation Studies into interactive media domains. His work on video game localization examines interactivity, cultural adaptation, glocalisation, and playability, while his audiovisual translation research investigates creativity in lip-synched dubbing, subtitling, and audiodescription. He extends these frameworks into gaming-based language learning through haptic environments and multisensory reinforcement, exploring physiological aspects of multilingual cognition and polysemiotic neural networks. This multidisciplinary approach fundamentally challenges traditional boundaries in translation theory. His publication trajectory reveals evolving industry-academia integration, shifting from foundational game localization frameworks (2008-2015) toward user-centered research and educational applications (2018-2024). Recent work emphasizes measurable business impacts through quality localization, regional market adaptations, and crowd-sourced methodologies, demonstrating consistent influence on professional standards across gaming and translation sectors. Fellow of the Higher Education Academy Bernal Merino supervises doctoral research on mobile game localization, transmedia fan experiences, and historical game content translation while developing industry-academia pipelines through projects like AHRC's Media Across Borders. His funded initiatives—including Maximising ROI through Quality Game Localisation and Video Games for Language Learning—bridge theoretical innovation with commercial implementation, focusing on glocalisation strategies, interactivity metrics, and playability optimization. These collaborations connect European universities, gaming studios, and localization service providers. As chair of the IGDA Localization SIG and member of GIR Discourse, Communication and Society, he directs international forums for game localization discourse. His work with Routes into Languages promotes audiovisual media in language education, while REF-readiness collaborations enhance research excellence across European institutions through his professional network spanning industry conferences like GDC Summit and Game Global.
