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Jeff CluneView profile

Professor

• Artificial Intelligence
• Machine Learning
• Neuroevolution
• +5 more

Jeff Clune is a Professor in the Department of Computer Science at the University of British Columbia (UBC), Canada, and a Canada CIFAR AI Chair at the Vector Institute. He also serves as a Senior Research Advisor at DeepMind. His work focuses on advancing artificial intelligence through evolutionary computation, neuroevolution, and open-ended systems. Clune's research explores topics such as continual learning, generative models (e.g., Genie), and automated scientific discovery. He is known for developing algorithms like Go-Explore and pioneering methods in neuroevolution to create robust and adaptable AI systems. His academic affiliations include the UBC Faculty of Science and collaborations with industry leaders like DeepMind. Clune teaches courses on machine learning and data mining, emphasizing practical applications and theoretical foundations. His awards include the SIGEVO Impact Award and recognition for outstanding publications in AI research. Notable projects include the development of the Go-Explore algorithm and contributions to AI safety and ethical frameworks. Clune's work bridges biological inspiration with machine learning, aiming to create systems that evolve and learn like natural organisms. Research interests span AI safety, generative AI, robotics, and scalable learning algorithms. He has published extensively on topics like neural network dynamics, open-endedness, and automated experimentation. Current projects include enhancing AI's ability to self-improve and exploring ethical implications of advanced AI systems.

• Computational Linguistics
• Natural Language Processing (NLP)
• Theoretical Linguistics
• +9 more

Stergios Chatzikyriakidis is a Professor of Computational Linguistics at the University of Crete and an Associate Researcher at the Centre for Linguistic Theory and Studies in Probability (CLASP). He holds a BA in Greek Philology (specializing in Linguistics) from Aristotle University of Thessaloniki, an MSc and PhD in Computational Linguistics and Formal Grammar from King’s College London. His career includes roles at Royal Holloway (University of London), CNRS, the Open University of Cyprus, and the University of Gothenburg. From 2016–2021, he served as Associate Director of CLASP. His research spans the intersection of NLP and Theoretical Linguistics, focusing on Natural Language Inference, Dialogue Modelling, Semantic Parsing, and the integration of symbolic logic with Machine Learning. He also develops NLP resources for under-resourced languages and explores constructive type-theoretical semantics. Additionally, he is an accomplished novelist with four Greek-language novels and two short story collections (one in English). His work emphasizes interdisciplinary methods, combining formal grammatical frameworks with probabilistic and computational techniques. Key themes include metaphor detection, sentiment analysis, and the implementation of formal semantics in AI systems.

• Planetary Science
• Physics
• Asteroid Impact Dynamics
• +4 more

Elizabeth A. Silber is a Senior R&D Scientist at Sandia National Labs and an Adjunct Professor in the Department of Earth Sciences at Western University. Her research focuses on planetary science, physics, and extraterrestrial phenomena, with a particular emphasis on infrasound analysis for bolide detection, planetary defense strategies, and atmospheric interactions. She collaborates on high-profile missions like OSIRIS-REx and investigates phenomena such as asteroid entry dynamics, Venus resurfacing, and space debris monitoring. Her work combines geophysical observation techniques with advanced data analysis methods to address critical questions in planetary science and space safety. Education & Affiliations: Western University: Adjunct Professor, Department of Earth Sciences Sandia National Labs: Senior R&D Scientist Research Interests: Silber’s research spans multiple disciplines including: Infrasound-based bolide tracking and energy estimation Planetary defense mechanisms for asteroid mitigation Impact crater formation on icy bodies like Europa and Titan Venus atmospheric studies and resurfacing processes Acoustic signatures of spacecraft reentries and rocket explosions Grants & Collaborations: Her projects involve multi-institutional collaborations, including observational campaigns for OSIRIS-REx re-entry studies and analysis of historical bolide datasets. She actively contributes to global infrasound sensor networks and balloon-borne acoustic detection systems. Labs & Teams: Associated with Sandia National Labs’ planetary defense initiatives and Western University’s Earth Sciences research groups.

Robert LeBlancView profile

Associate Professor

• Secondary English Language Arts education
• Literature instruction
• Narratology and narrative theory
• +9 more

Dr. Robert LeBlanc serves as Associate Professor of ELA/Literacy and Board of Governors Research Chair (Tier II) in Literacy Studies at the University of Lethbridge's Faculty of Education. Currently on academic leave, he maintains active research leadership while specializing in secondary English education and literature instruction methodologies. His educational foundation includes: Ph.D. in Reading/Writing/Literacy from the University of Pennsylvania (Defended with Distinction) M.A. in Education and Society from McGill University (Dean's Honour) B.Ed. in Secondary Education from the University of Saskatchewan (With Great Distinction) LeBlanc's research examines classroom discourse through interactional sociolinguistics, narrative theory, and Bourdieu's frameworks, with particular focus on digital literacies in platform societies. His work bridges traditional literary interpretation with emerging digital ecologies, analyzing how students navigate voice stylization, intertextuality, and ethical dimensions of narrative form within contemporary educational contexts. Recent publications demonstrate consistent exploration of digital platform impacts on ELA instruction, narrative pedagogy innovations, and sociocultural dynamics in literacy development. His scholarship reveals evolving emphasis on pandemic-responsive teaching, algorithmic literacy, and critical media ecologies while maintaining core commitments to qualitative ethnographic methodologies. Notable recognition includes: 2024 Alberta Teachers' Association Educational Research Award AERA Outstanding Dissertation Award (2017) University of Pennsylvania Faculty Award for Outstanding Leadership and Teaching Coyle Fellowship at Notre Dame's Center for Literacy Education As Research Chair, LeBlanc leads institutional initiatives in literacy studies while mentoring graduate researchers. His policy briefs for the National Council of Teachers of English demonstrate active engagement with educational practitioners, though specific grant funding details remain unspecified in source materials.

Brandon HelfieldView profile

Assistant Professor

• Biomedical Ultrasound Imaging
• Focused Ultrasound Therapy
• Molecular Biophysics
• +5 more

Brandon Helfield is an Assistant Professor at Concordia University with cross-appointments in Physics and Biology. He holds the Tier II Canada Research Chair in Molecular Biophysics in Human Health and serves as a Junior Scientist at the Physical Sciences Platform of Sunnybrook Research Institute. His research bridges biomedical ultrasound, microbubble dynamics, and therapeutic applications. Education : PhD in Medical Biophysics (University of Toronto), BSc in Physics (McGill University), Postdoctoral Fellowship in Cardiology (University of Pittsburgh) Research Interests : Dr. Helfield focuses on biomedical ultrasound imaging and therapy, particularly microbubble-based technologies for targeted drug/gene delivery to treat cardiovascular diseases. His recent work explores CRISPR-Cas9 delivery to stem cells, immunomodulation via focused ultrasound, and super-resolution imaging algorithms. Publication Trends : His research spans ultrasound physics, microbubble dynamics, and clinical translation. Key areas include cavitation mechanics, vascular delivery optimization, and machine learning applications for imaging analysis. Awards : Burroughs Wellcome Fund Career at the Scientific Interface Award, Arthur E. Weyman Young Investigator Award, European Symposium on Ultrasound Young Investigator Award

Gregor KosView profile

Senior Lecturer

• Atmospheric Chemistry
• Environmental Chemistry
• Analytical Chemistry
• +3 more

Gregor Kos is a Senior Lecturer at the Department of Chemistry and Biochemistry , Concordia University, Montreal, Canada. His work focuses on environmental analytical chemistry, long-term urban pollutant monitoring, and Arctic studies. PhD in Analytical Chemistry, Vienna University of Technology Postdoctoral research at McGill University Visiting scientist at University of Idaho His research interests include developing field-deployable sensors for urban air pollution, statistical analysis of atmospheric data, and studying mercury cycles and mycotoxin contamination. He employs Python and R for multivariate data analysis. His recent publications cover topics like Arctic snow chemistry, mycotoxin detection, and mercury emissions from industrial activities. These works emphasize environmental modeling, spectroscopy, and community-science collaborations such as the Decolonizing Light project. At Concordia, he teaches courses including CHEM 217 , CHEM 218 , and CHEM 610 , integrating data analysis and environmental monitoring into the curriculum.

Vladimir MakarenkovView profile

Professor

• Bioinformatics
• Artificial Intelligence
• Machine Learning
• +6 more

Roles and Affiliations: Full Professor of Computer Science at Université du Québec à Montréal (UQAM), Director of the DESS in Bioinformatics program. Regular member of LaCIM and affiliate member of Mila (Quebec AI Institute). Served as Assistant Professor (2001–2006) and Associate Professor (2006–2011) before becoming Full Professor in 2011. Education: B.Sc./M.Sc. in Applied Mathematics and Computer Science, Moscow State University (1987–1992) DEA in Computer Science, University Paris V (1993–1994) Ph.D. in Computer Science and Mathematics, École des Hautes Études en Sciences Sociales (EHESS), Paris (1994–1997) Research Interests: Focuses on machine learning applications in bioinformatics, including clustering algorithms, phylogenetic analysis, and genomics. Specializes in CRISPR/Cas9 off-target prediction, SARS-CoV-2 origin analysis, and high-throughput screening (HTS) data correction. Develops tools like T-REX web server for phylogenetic analysis and DUNEScan for skin cancer uncertainty estimation. Integrates deep learning and reinforcement learning for clustering and medical diagnostics. Publications and Grants: Over 100 peer-reviewed articles spanning bioinformatics, AI, and computational biology. Key grants include projects on HTS data correction, phylogenetic networks, and machine learning for biomedical applications. Collaborates with institutions like Mila and Université de Montréal. Labs and Teams: Leads research teams at UQAM’s Department of Computer Science, focusing on interdisciplinary projects combining AI and life sciences. Maintains collaborations with international groups in computational biology and data science.

Olivia DasView profile

Associate Professor

• Distributed Systems
• Cloud Computing
• Mobile Cloud Computing
• +5 more

Olivia Das is an Associate Professor in the Department of Electrical, Computer, and Biomedical Engineering at Toronto Metropolitan University. She holds a PhD, MSc, and BSc in Computer Engineering and Applied Mathematics, and is a licensed Professional Engineer (PEng). Her research focuses on performance and dependability evaluation of distributed systems, including cloud computing, mobile cloud, and IoT. Education: PhD, MSc, and BSc from Carleton University and the University of Calcutta. Das employs techniques like measurements, analytical models, simulation, and machine learning to study resource management in distributed software systems. Her work aims to eliminate loading errors and lags in cloud-based systems through proper backend server provisioning. She teaches courses such as Introduction to Software, Object-Oriented Engineering Analysis and Design, and Computer Systems Modelling. Scientific Awards: Teaching Excellence Award, Electrical and Computer Engineering, Toronto Metropolitan University (2011) Visiting Faculty, Indian Institute of Technology-Kanpur (2012) Visiting Faculty, International Institute of Information Technology-Hyderabad (2012) She leads the Dependable Adaptive Systems Group (DAS) and is a member of Professional Engineers Ontario (PEO) and IEEE. Das emphasizes interactive learning in her classroom and is available to supervise students.

Eugene SyrianiView profile

Professor

• Software Engineering
• Model-Driven Engineering
• Digital Twins
• +5 more

Dr. Eugene Syriani is a Professor at the Department of Computer Science and Operations Research , Faculty of Arts and Sciences , University of Montreal . He leads the GEODES research group and teaches software engineering at undergraduate, Master's, and PhD levels. His work combines Model-Driven Engineering (MDE) and Simulation to improve software engineer productivity and cross-disciplinary system design. Research interests span two axes: (1) Software Engineering focusing on Domain-Specific Languages (DSLs) , Model Transformations , Code Generation , Collaborative Modeling , and Customizable Modeling Environments ; (2) Simulation addressing Digital Twins , Discrete-Event Simulation , and Co-Simulation for applications in agriculture, automotive, and smart systems. His recent work explores AI-assisted modeling and prompt engineering . Key projects include Digital Twins for Vertical Farming (funded by NSERC, MITACS, and industry partners) and Domain-Specific Environments (NSERC Discovery Grant). He has received multiple best paper awards at international MDE and modeling conferences. Scientific contributions include: Best Paper, ACM/IEEE International Conference on Model Driven Engineering Languages & Systems (2023, 2018) NSERC Discovery Grant (2020-2027) Visiting Professor Fellowships (University of L'Aquila, TU Wien, University Cote d'Azur) Guest Editor for Software & Systems Modeling and JOT He supervises 13 graduate students and postdocs, with expertise in DSL development , collaborative modeling , digital twin frameworks , and model consistency . His tools include Gentleman (projectional editor), ReLiS (systematic review tool), and AToMPM (cloud-based modeling environment).

Cheng-Zhi Anna HuangView profile

Associate Professor

• Artificial Intelligence
• Deep Learning
• Generative AI
• +4 more

Dr. Cheng-Zhi Anna Huang is currently a faculty member at the Massachusetts Institute of Technology (MIT) with a joint appointment between the Department of Electrical Engineering and Computer Science (EECS) and the Department of Music and Theater Arts (MTA), spanning both the College of Computing and School of Humanities, Arts, and Social Sciences. She simultaneously holds an adjunct associate professor position at the Université de Montréal's Department of Computer Science and Operations Research. Her academic background includes a PhD from Harvard University, a master's from the MIT Media Lab, and dual bachelor's degrees in music composition and computer science from the University of Southern California. Dr. Huang's research focuses on human-AI co-creation in music, with particular emphasis on: Generative AI models for music composition and performance Neural network interpretability for musical applications Interactive systems for real-time human-AI collaboration Reinforcement learning frameworks for creative expression Cross-cultural music modeling and computational musicology She pioneers novel approaches to musical interaction through machine learning, aiming to develop systems that extend how humans understand, learn, and create music. Her publication portfolio shows strong emphasis on generative models for music, particularly transformer architectures, with consistent output in top AI/ML venues since 2014. Recent work focuses on controllable music synthesis, human-AI co-creation frameworks, and performance modeling. The 14 most recent publications demonstrate progression from fundamental music representation research toward sophisticated interactive systems and evaluation frameworks. Awards and Honors: Canada CIFAR AI Chair (Mila) Outstanding Paper Award at NeurIPS Workshop CtrlGen (2021) First Prize in San Francisco Choral Artists New Voices Project (composition) Dr. Huang actively supervises graduate students, with recent master's advisees including Nithya Shikarpur (2024) working on human-AI co-creation for Hindustani music, and Yusong Wu (2023) researching controllable performance synthesis. She is currently recruiting postdoctoral researchers and PhD students for her MIT Music Technology laboratory, focusing on multi-agent reinforcement learning and human-AI interaction in musical contexts.

Marc G. BellemareView profile

Adjunct Professor

• Reinforcement Learning
• Deep Reinforcement Learning
• Generative Modeling
• +5 more

Marc G. Bellemare is a Canada CIFAR AI Chair at Mila, an Adjunct Professor at the School of Computer Science at McGill University and Université de Montréal, and the Chief Scientific Officer at Reliant AI, a Montréal-Berlin startup. His research focuses on reinforcement learning and generative modeling, with significant contributions to distributional reinforcement learning, exploration in high-dimensional spaces, and the development of the Arcade Learning Environment (ALE). He has held previous roles at the Google Brain team and DeepMind. Marc’s work includes both theoretical and applied advancements, such as distributional reinforcement learning theory, exploration strategies, and the commercial application of RL for Loon’s stratospheric balloons. His publications span journals like Nature and top conferences including NeurIPS, ICML, and AAAI. He has received multiple best paper awards, including at NeurIPS 2021 and ICML 2019 Workshop. Current Students: Adrien Ali Taiga, Jacob Buckman, Harley Wiltzer, Pierluca D'Oro, Nathan U. Rahn, Jesse Farebrother Graduated Students: Rishabh Agarwal, Charline Le Lan, Max Schwarzer, Johan Obando Céron, Philip Amortila, Vishal Jain His recent articles emphasize distributional RL, exploration strategies, and large-scale applications. Scientific awards include best papers at NeurIPS, ICML, and RLDM. He is also a co-founder of Reliant AI and developed the ALE benchmark, which underpins deep RL research.

Paul SheridanView profile

Assistant Professor

• Text Analysis
• Ontologies
• Computational Literary Studies
• +6 more

Paul Sheridan is an Assistant Professor at the School of Mathematical and Computational Sciences, University of Prince Edward Island, specializing in text analysis and ontologies for computational literary studies. He develops novel term weighting schemes through statistical significance testing to improve document retrieval, classification, and summarization methods. His Literary Theme Ontology (LTO) provides the first controlled vocabulary of literary themes for media annotation and information retrieval. Research Grants: AI/machine learning for engine maintenance (2024), keyword extraction efficacy analysis (2023–2024), GPT-2 unnatural language generation (2022–2025) Academic Leadership: Statistics and Analytics Program Lead (2024–present), ACENET Research Directorate member His recent publications focus on lexical diversity analysis, term dispersion quantification, and statistical foundations of TF-IDF. He supervises students in projects spanning energy-efficient NLP, causal inference in finance, and low-resource language embeddings. Paul actively contributes to open-source projects like stoRy and PAFit packages.

Sandrine MeretteView profile

Assistant Clinical Professor

• Mass Spectrometry
• Toxicology
• Data Mining
• +4 more

Sandrine Merette is a clinical assistant professor in the Department of Pathology & Laboratory Medicine at the University of British Columbia (UBC) and a mass spectrometry scientist at the Provincial Toxicology Centre within the British Columbia Centre for Disease Control (BCCDC) . Her work bridges forensic toxicology, public health, and data science. B.Sc. in Applied Chemistry , University of Hertfordshire, UK Ph.D. in Medicinal Chemistry , University of Hertfordshire, UK Dr. Merette's research focuses on mass spectrometry and data mining for identifying novel psychoactive substances (NPS) in postmortem and clinical toxicology, illicit drug supplies, and wastewater. She also investigates NPS metabolism and its implications. Her recent publications analyze NPS trends through population-scale mass spectrometry datasets , postmortem drug concentration studies , and metabolomics using language models . Key domains include forensic toxicology, computational chemistry, and public health surveillance. She is affiliated with the Provincial Toxicology Centre and UBC Faculty of Medicine , contributing to clinical toxicology, illicit drug research, and bioanalytical chemistry.

Hind SbihiView profile

Adjunct Assistant Professor

• Environmental Health
• Public Health
• Epidemiology
• +7 more

Hind Sbihi is an Adjunct Assistant Professor at the University of British Columbia (UBC) School of Population and Public Health and Director of Data Science & Innovation for Data & Analytic Services at the British Columbia Centre for Disease Control (BCCDC). Her research focuses on the intersection of the built environment (air pollution, green spaces, microbiome) and human health, particularly among vulnerable populations like children and pregnant women. Education: PhD and MSc in Occupational and Environmental Health (UBC), BEng in Industrial Engineering (École Polytechnique Montreal) Research Interests: Dr. Sbihi investigates how environmental exposures (e.g., air pollution, green spaces) shape health outcomes, with a focus on intervention strategies and surveillance systems for emerging pathogens. Her work bridges precision health, microbiome research, and policy development. Article Trends: Recent publications highlight her expertise in Long COVID epidemiology, RSV immunization cost-effectiveness, microbiome-environment interactions , and health inequities linked to environmental factors. Scientific Awards: Postdoctoral Fellowships: BC Children's Research Institute, CIHR, Michael Smith Foundation Doctoral Awards: CIHR Banting and Best, UBC Four-Year Fellowship, Killam Pre-Doctoral Fellowship David Bates Scholarship (2011) Advising and Grants: Her research has been supported by major grants from CIHR, Michael Smith Foundation, and provincial health agencies. She collaborates with interdisciplinary teams, including Dr. Stuart Turvey's lab at BC Children's Hospital Research Institute. Labs and Teams: Dr. Sbihi has worked with the BC Children's Hospital Research Institute and contributes to BCCDC's surveillance programs, including the British Columbia COVID-19 Cohort (BCC19C).

Japan TrivediView profile

Professor

• Petroleum Engineering
• Enhanced Oil Recovery (EOR)
• Unconventional Reservoirs
• +6 more

Japan Trivedi, PhD, P.Eng is a Professor in the Civil and Environmental Engineering Department at the University of Alberta . His research focuses on Enhanced Oil Recovery (EOR) , CO2 Sequestration , Unconventional Reservoirs , and integration of Machine Learning in reservoir simulation. His lab operates at the Natural Resources Engineering Facility (NREF) under the School of Mining and Petroleum Engineering . Research Areas: Chemical EOR (polymers, surfactants, nanofluids) CO2 utilization for EOR and storage Reinforcement Learning for SAGD optimization Extensional rheology of complex fluids Techniques: Reservoir simulation Machine learning integration Micromodel experiments Field-scale modeling Key Projects: Include CO2 EOR/sequestration, Tight Oil EOR, ASP polymer characterization, and real-time SAGD optimization. His group collaborates on underground coal gasification and fracture reservoir characterization . Teaching: Offers courses like PET E 377 - Modelling in Petroleum Engineering and PET E 649 - Advanced Reservoir Simulation , emphasizing numerical methods, EOR processes, and simulation tools.