Alan Ritter is an Associate Professor at the School of Interactive Computing , Georgia Institute of Technology, with additional affiliation to the Machine Learning Center . His research focuses on Natural Language Processing , particularly robust models across domains/languages with fewer labels and efficient resource use, plus data-driven dialogue agents for open-topic conversations. Research Interests : Robust NLP models, cross-lingual transfer, resource-efficient learning, dialogue systems, cultural bias measurement, and privacy-aware language models Students : Mentors Ph.D. students in Georgia Tech's ML and CS programs, including Junmo Kang, Yang Chen, and Duong Minh Le. Alumni include Fan Bai (Ph.D. 2023), Yang Chen (Ph.D. 2024), and Andrew Li (M.S. 2024). Awards : NSF CAREER Award, Amazon Research Award, ACL 2024 Best Social Impact Paper, IUI 2009 Best Student Paper. Recent Work : Studies training budget allocation between supervised and preference-based finetuning, cross-lingual information extraction, cultural bias in LLMs, and privacy risk mitigation in social media disclosures. Service : Served as Program Chair for NAACL 2025, Area Chair for multiple top-tier conferences (COLM, EMNLP, ACL, EACL, AAAI). Email : alan.ritter@cc.gatech.edu
Sheila McIlraith is a Professor in the Department of Computer Science at the University of Toronto, holding the Canada CIFAR AI Chair at the Vector Institute and serving as Associate Director and Research Lead at the Schwartz Reisman Institute for Technology and Society. Her research spans AI safety, ethics, reinforcement learning, and knowledge representation, with a focus on human-compatible AI and long-term societal impacts. Her career includes six years as a Research Scientist at Stanford University and a year at Xerox PARC. McIlraith’s work has been recognized through ACM and AAAI fellowships, as well as prestigious awards like the SWSA 10-Year Award (2011) and the CAIAC Lifetime Achievement Award (2024). Research Interests: AI Safety and Alignment Human-Compatible AI Reinforcement Learning with Ethical Constraints Semantic Web Services Cognitive Robotics and Diagnostic Systems Probabilistic and Logical Reasoning Recent Contributions: Her work emphasizes ethical AI integration, such as the Embedded Ethics Education Initiative (E3I), and addresses challenges in long-term AI risks, multi-agent systems, and interpretable decision-making frameworks. Awards and Honors: ACM Fellow AAAI Fellow 2023 IJCAI-JAIR Best Paper Prize 2024 CAIAC Lifetime Achievement Award Labs and Teams: McIlraith leads initiatives at the Schwartz Reisman Institute and contributes to the Vector Institute, focusing on societal and ethical dimensions of AI technology.
Dr. Muhammad Abdul-Mageed is an Associate Professor in the School of Information at The University of British Columbia, with joint appointments in Linguistics and an associate membership in Computer Science. He holds the Canada Research Chair in Natural Language Processing and Machine Learning. His research focuses on deep learning, socio-pragmatics, and speech/language technologies, particularly for Arabic and African languages. He leads the UBC Deep Learning & NLP Group and co-directs SSHRC-funded grants like I Trust AI and Ensuring Full Literacy. He is a founding member of the Center for Artificial Intelligence Decision making and Action and a member of the Institute for Computing, Information, and Cognitive Systems. His work spans automatic speech recognition, machine translation, computational socio-pragmatics, and low-resource language technologies. Notable projects include developing Arabic speech recognition systems, multidialectal Arabic benchmarks, and tools for African language processing. He has authored over 100 peer-reviewed papers and leads initiatives like the NADI Arabic Dialect Identification shared task and the NileChat project for culturally-aware LLMs. His research aims to create equitable, socially-aware AI systems for health, social media, and information management.
Ryuko Kubota is a Professor in the Department of Language and Literacy Education at the University of British Columbia (UBC), Faculty of Education, since 2009. Her research spans critical applied linguistics , race and language education , and decolonial pedagogies . She has contributed extensively to understanding language ideologies , multicultural education , and critical literacies . Education: BA in English Linguistics, Rikkyo University (1980) MAT in TESOL, School for International Training (1987) PhD in Education, OISE/University of Toronto (1992) Her research interests focus on the intersection of race, language policies, and critical pedagogies. She examines neoliberal paradoxes in language learning, translingual practices , and antiracist engagement in global contexts. Her work addresses systemic inequities in English language education and immersion programs . Recent publications highlight critical approaches to World Englishes , AI-assisted writing , and raciolinguistic hegemony . These studies span interdisciplinary sub-fields including critical race theory , decolonial education , and language teacher identity . Scientific awards include the DSSA Award 2020 . She supervises graduate students like Charu Gupta (PhD) and collaborates with institutions such as the Language Sciences Institute at UBC. Her teaching includes courses on critical multicultural education and language politics .
Qingguo Li is a Professor and Associate Head at the Department of Mechanical and Materials Engineering , Queen's University , and a member of the Ingenuity Labs Research Institute . He specializes in biomechanical system design, energy harvesting, wearable sensors, gait analysis, and load carriage systems. His research integrates robotics, biomedical engineering, and sensor technology to develop human-centric devices and mobility aids. Current Roles : Professor, Associate Head, Queen's University Research Institute : Ingenuity Labs Research Institute Lab : Bio-Mechatronics and Robotics Laboratory His work focuses on biomechanical energy harvesting , IMU-based motion analysis , and assistive device development . Key applications include stroke rehabilitation, gait monitoring, and wearable power generation systems. Articles span cable-driven robots , smart walkers , and 3D printing mechanisms , emphasizing human-robot interaction and dynamic modeling . The lab explores sensor calibration , adaptive control algorithms , and human movement optimization . Areas of impact include rehabilitation engineering , load carriage stability , wearable sensor accuracy , and assistive robotics . His team develops solutions for gait asymmetry detection , post-stroke mobility , and low-cost energy systems , leveraging machine learning and kinetic modeling .
Florian Shkurti is an Assistant Professor in the Department of Computer Science at the University of Toronto Mississauga (UTM), affiliated with the UofT Robotics Institute, Vector Institute, and Acceleration Consortium. His research focuses on robotics, machine learning, and computer vision, emphasizing safe and effective autonomous systems in dynamic environments. He directs the Robot Vision and Learning (RVL) lab, exploring areas like environmental monitoring, autonomous navigation, and mobile manipulation. Research Interests: His work spans robotics, machine learning, and computer vision. Key areas include robot perception, planning under uncertainty, safe exploration, imitation learning, and applications in field robotics, autonomous vehicles, and chemistry lab automation. He develops methods enabling robots to perceive, reason, and act safely in collaboration with humans. Publications: Recent work includes advancements in safe multitask learning, interactive crowd navigation, and diffusion models for trajectory planning. His research bridges theoretical foundations with real-world applications in environmental science and autonomous systems. Affiliations: Faculty Member, UofT Robotics Institute; Faculty Affiliate, Vector Institute; Faculty Member, Acceleration Consortium. He also holds positions at UTM's Mathematical & Computational Sciences department. Teaching: Courses include Imitation Learning for Robotics, Neural Networks, and Mobile Robotics. He emphasizes hands-on experience with autonomous systems through projects involving RC cars and simulation tools. Labs & Teams: Leads the RVL lab, collaborating on projects like RoboCulture (automated biological experimentation) and SICNav (safe crowd navigation systems). The lab focuses on cross-disciplinary robotics solutions for real-world 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.
About Marin Litoiu is a Professor at York University, holding dual affiliations in the Department of Electrical Engineering and Computer Science at the Lassonde School of Engineering and the School of Information Technology in the Faculty of Liberal Arts and Professional Studies. He is a Fellow of the Canadian Academy of Engineering and a recipient of the 2020 IBM Faculty of the Year Award. His research focuses on cloud computing, self-adaptive systems, DevOps, IoT, and machine learning-driven performance engineering. Research & Awards Litoiu leads the Dependable Internet-of-Things Applications (DITA) program, funded by NSERC, and co-founded Bitnobi Inc., acquired by Myant. His notable awards include the CASCON 2019 Most Influential Paper Award and Best Paper Awards at multiple conferences. His work emphasizes practical applications of adaptive systems, cybersecurity, and smart infrastructure integration. Grants & Projects NSERC CREATE Program: $1.65M for the DITA program (2018) York Innovation, TIAP, NSERC, and OCI-funded Bitnobi incubation Leadership in multiple CASCON workshops on cloud computing and AIOps Labs & Teams Litoiu’s lab has produced impactful startups like Bitnobi and pioneered research in self-driving systems, edge computing, and AI-driven operations. His team collaborates with industry partners like IBM and explores cutting-edge topics such as LLMs in performance optimization and fault detection.
Karyn Moffatt is an Associate Professor in the School of Information Studies at McGill University and holds the Canada Research Chair in Inclusive Social Computing. As Graduate Program Director for the PhD program, she leads the Accessible Computing Technologies Research Group (ACT Lab), focusing on designing inclusive computing applications that support social engagement across diverse lifespans and abilities. Her work bridges human-computer interaction, accessibility research, and real-world community impact. Educational background: PhD in Computer Science, University of British Columbia MSc in Computer Science, University of British Columbia BASc in Computer Engineering, University of British Columbia Research Interests: Dr. Moffatt's work centers on inclusive social computing with emphases on aging populations , disability access , and intergenerational communication . She investigates how technology can overcome barriers to social participation through co-design methodologies, particularly for older adults and individuals with cognitive or physical disabilities. Current projects explore AI-enhanced aging support, dementia-friendly social platforms, accessible financial technology, and respite care coordination systems. Her approach integrates participatory design with rigorous usability testing to create solutions that address real-world challenges in healthcare, finance, and community engagement. Publication Trends: Analysis of her 15 most recent publications reveals consistent focus on aging and accessibility (60% of works), with growing emphasis on AI ethics (2025), dementia support systems (30% of 2023-2024 works), and accessible financial technology (2024). Methodologically, 75% employ co-design or participatory approaches, while 40% involve longitudinal field studies. Key venues include CHI (33%), ASSETS (20%), and ACM Transactions on Accessible Computing (27%), demonstrating leadership in top-tier HCI and accessibility forums. Scientific Awards: Multiple Best Paper Awards from ASSETS, CHI, and CSCW conferences Canada Research Chair in Inclusive Social Computing Advising and Grants: Dr. Moffatt currently supervises PhD candidates Chong Hu and Muhe Yang, having graduated four students since 2022 including Maurício Fontana De Vargas (2023) and Carrie Dai (2023). Her active grants include: NSERC Discovery Grant (2024-2029) as PI: Ethical AI for active aging Canada Research Chair renewal (2022-2027) as PI McGill Nursing Collaborative grant (2023-2025) as Co-I: iRespite mHealth app for palliative care Labs and Teams: She directs the ACT Lab, which partners with healthcare providers, public libraries, and community organizations to develop and deploy inclusive technologies. Current initiatives include the QuickPic AAC system for speech therapy, dementia-focused social programs with Montreal libraries, and Quebec-wide respite care coordination tools, all developed through interdisciplinary collaboration with clinicians, caregivers, and end-users.
M. Tamer Özsu is a University Professor of Computer Science at the David R. Cheriton School of Computer Science, University of Waterloo, where he holds a Cheriton Faculty Fellowship. He also serves as a Distinguished Visiting Professor at Tsinghua University and is the Founding Director of Waterloo-Huawei Joint Innovation Laboratory since 2018. His extensive contributions to computing have earned him numerous prestigious awards including the 2024 ACM Presidential Award for long-standing and significant contributions to the computing field. Professor Özsu's research focuses on data engineering aspects of data science, particularly addressing data management issues with two main foci: management of non-traditional data and large-scale distributed data management. He is renowned for his seminal book "Principles of Distributed Database Systems" (co-authored with Patrick Valduriez), now in its fourth edition, and the "Encyclopedia of Database Systems" (co-edited with Ling Liu), in its second edition. His work bridges theoretical foundations with practical system implementations, targeting grand societal challenges through computational approaches. His recent publications reveal a strong trend toward graph analytics, streaming data processing, and the integration of large language models with vector data management. The research shows increasing focus on GPU-accelerated graph processing, RDF query optimization, and multimodal data analysis, reflecting the evolution of data management challenges in the era of big data and AI. His work continues to address fundamental challenges in distributed data systems while adapting to emerging technologies and application domains. Scientific Awards and Fellowships ACM Presidential Award (2024) IEEE TCDE Education Award (2024) IEEE Innovation in Societal Infrastructure Award (2022) CS Can | Info Can Lifetime Achievement Award (2018/2019) ACM SIGMOD Test-of-Time Award (2015) ACM SIGMOD Contributions Award (2006) The Ohio State University College of Engineering Distinguished Alumnus Award (2008) Fellow of the Royal Society of Canada Fellow of the American Association for the Advancement of Science (AAAS) Life Fellow of the Association for Computing Machinery (ACM) Life Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA) Elected member of the Science Academy, Türkiye Professor Özsu has been deeply involved in academic leadership and community building. As Founding Editor-in-Chief of ACM Books (2013-2019), he launched a series that by 2019 had published 28 major books with another 30 under contract. His service to ACM, particularly through SIGMOD, has been exemplary and widely recognized. He directs the Waterloo-Huawei Joint Innovation Laboratory, which focuses on cutting-edge research in data management and distributed systems, fostering strong industry-academia collaboration.
Verónica Loureiro-Rodríguez is an Associate Professor in the Department of Linguistics at the University of Manitoba's Faculty of Arts. Her research focuses on sociolinguistics, language identity, and code-switching, with special attention to global hip hop and multilingual communities. She holds a PhD from the University of California, Davis, an MA from the University of Colorado at Boulder, and a BA from the Universidade de Santiago de Compostela. Dr. Loureiro-Rodríguez's work examines language attitudes across diverse contexts, including French-English dynamics in Manitoba, Spanish-Valencian bilingual processing, and code-switching in music. She has also explored language use in robotics and cultural hybridity among Puerto Rican and Mexican communities. Her teaching excellence was recognized with the 2021 Faculty of Arts Teaching Excellence Award. Education: PhD (UC Davis), MA (CU Boulder), BA (USC) Awards: 2021 Teaching Excellence Award (Established Faculty) Research Focus: Language policy, digital sociolinguistics, and cultural identity She currently supervises graduate students in Master's and PhD programs, focusing on sociolinguistic methodologies like the matched-guise technique. Her research often intersects with music studies, robotics, and diaspora linguistics.
Dr. Eunice Eunhee Jang is a Professor in the Department of Applied Psychology and Human Development at the Ontario Institute for Studies in Education (OISE), University of Toronto. Her research focuses on synergistic learner modeling, dynamic assessment systems, and the intersection of language testing with educational measurement. PhD with specializations in language testing, educational measurement, and program evaluation Develops interactive digital assessment interfaces for struggling readers Author of "Focus on Assessment" (2014) and co-author of OECD Reviews on Evaluation and Assessment in Education Research Interests Dr. Jang's work explores prismatic assessment analytics to understand learner potential and predict learning pathways. She integrates natural language processing and machine learning to create diagnostic feedback systems that support cognitive, metacognitive, and affective growth in technology-rich classrooms. Scientific Awards Jacqueline Ross TOEFL Dissertation Award Caroline Clapham IELTS Master’s Award Tatsuoka Measurement Award Professional Contributions She has served on major advisory boards including EQAO provincial assessments and TOEFL Committees of Examiners. Currently, she is an elected board member for the International Language Testing Association and contributes to the Broader Measures of Success Advisory Committee for People for Education.
Kevin Leyton-Brown is a Professor of Computer Science at the University of British Columbia (UBC), holding a Canada CIFAR AI Chair at the Alberta Machine Intelligence Institute (Amii). He is also an Associate Member of the Vancouver School of Economics and a Fellow of the Royal Society of Canada, ACM, and AAAI. His research focuses on AI, machine learning, computational economics, and game theory, with notable contributions to algorithmic market design, heuristic algorithms, and large language models. He co-authored influential textbooks on multiagent systems and game theory, and his work has been recognized with prestigious awards including the INFORMS Franz Edelman Award and the Killam Teaching Prize. Education: PhD (Computer Science), Stanford University; MSc (Computer Science), Stanford University; BSc (Computer Science), McMaster University. Research Interests: Artificial Intelligence, Machine Learning, Game Theory, Computational Economics, Algorithmic Game Theory, Market Design, and Large Language Models. He has developed impactful tools like SATzilla, AutoWEKA, and Mechanical TA, and contributed to high-stakes projects such as spectrum auction design and Ugandan agricultural market platforms. Awards & Recognition: Royal Society of Canada Fellow (2023), ACM SIG-KDD Research Track Test of Time Award (2023), INFORMS Franz Edelman Award (2018), ACM Fellow (2020), AAAI Fellow (2018), Killam Teaching Prize (UBC), and numerous paper awards from top conferences like AAAI, ICML, and ACM-EC. Leadership & Affiliations: Director of UBC’s CAIDA and AIM-SI research clusters, former Chair of ACM SIG-Ecom, and advisor to companies like AI21 Labs and Auctionomics. He has held visiting roles at institutions including MIT, Harvard, and the Simons Institute.
Istvan David is an Assistant Professor in the Department of Computing and Software at McMaster University , with research expertise spanning Digital Twins , Model-Driven Engineering , and Sustainability . His work bridges theoretical and applied domains, focusing on smart ecosystems , collaborative modeling , and AI-driven simulation . Key contributions include frameworks for digital twin evolution and interoperability in sustainable systems. Education : BSc, MSc, and PhD in Computer Engineering and Computer Science from Budapest University of Technology and Economics, and University of Antwerp. Research Areas : Digital Twins, Model-Driven Engineering, Reinforcement Learning, Smart Ecosystems, Sustainability, Collaborative Modeling, Cyber-Biophysical Systems, and Software Architecture. Recent Article Trends emphasize AI integration with digital twins, collaborative modeling in industrial contexts, and sustainable systems engineering . His work often combines machine learning with formal modeling to address challenges in technical sustainability and smart agriculture .
Yang Wang is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University, holding an adjunct position since 2022. Previously, he served as an Associate Professor at the University of Manitoba (2012–2022) and worked as Chief Scientist in Computer Vision at Huawei Canada (2020–2022). He holds a PhD from Simon Fraser University, MSc from the University of Alberta, and BEng from Harbin Institute of Technology. His research focuses on computer vision, machine learning, and deep learning, particularly in meta-learning, test-time training, and continual learning. Key areas include crowd counting, anomaly detection, video highlight detection, and gaze estimation. His work has been recognized with awards such as the Falconer Emerging Researcher Rh Award (2017) and a Faculty of Science Research Chair (2019–2022). Recent research emphasizes AI models that are personalized and adaptable, leveraging techniques like meta-learning and few-shot learning. He has published extensively in top venues (CVPR, ICCV, ECCV) and holds patents in related fields. His group collaborates with industry partners like Huawei and Sightline Innovation.
