جست‌وجوی استاد و پژوهشگر

Jonathan Stokesمشاهده پروفایل

استادیار

• Machine Learning
• Antibiotic Discovery
• Computational Biology
• +۳ مورد دیگر

Jonathan Stokes is an Assistant Professor at McMaster University in the Department of Biochemistry & Biomedical Sciences , where he leads the Stokes Lab and serves as a member of the Michael G. DeGroote Institute for Infectious Disease Research . He also co-founded the AI drug discovery startup Stoked Bio , which commercializes his research breakthroughs. Stoked Bio CEO Jeff Skinner Co-founder Chris Sinclair Research Interests : Stokes specializes in machine learning applications for antibiotic discovery , targeting drug-resistant pathogens like Acinetobacter baumannii . His work combines computational biology , bacterial metabolism , and deep learning to identify novel antimicrobial compounds and synergistic drug combinations. Scientific Contributions : His 15 most recent publications focus on AI-guided antibiotic design , metabolism-driven drug lethality , and explainable deep learning frameworks . Articles highlight trends in generative AI for synthesizable antibiotics, fitness cost exploitation in resistance mechanisms, and multi-omics integration for target identification. Teaching & Mentorship : Stokes teaches graduate courses in Artificial Intelligence in Healthcare and Antibiotic Discovery , while mentoring students like Autumn Arnold , Denise Catacutan , and Gary Liu in both academic and industrial contexts at Stoked Bio.

• Dark Matter
• Stellar Streams
• Galactic Dynamics
• +۳ مورد دیگر

Nathaniel Starkman is a Brinson Prize Fellow and Astrophysics Postdoc at MIT. He is a key maintainer for open-source projects including @astropy , @GalacticDynamics , and @cosmology-api , with over 2,500 GitHub contributions in the last year. His work focuses on dark matter detection, stellar stream dynamics, and computational astrophysics using JAX and differentiable simulations. Current affiliations: MIT, GalacticDynamics, cosmology-api Former affiliations: Astropy Project, Quax, Potamides Research interests span dark matter substructure mapping via stellar streams, Hamiltonian perturbation theory applications, and JAX-based galactic dynamics tools. He develops unit-aware numerical frameworks (unxt, coordinax) and contributes to astronomical data infrastructure standards. Scientific contributions include: Leading differentiable simulations for galactic potentials Creating data-driven stellar stream characterization methods Advancing type annotations in astropy Awards: Brinson Prize Fellowship (MIT) Contact: starkman@mit.edu | ORCiD

Paul De Koninckمشاهده پروفایل

استاد

• Molecular Neurosciences
• Synaptic Plasticity
• Hippocampus
• +۷ مورد دیگر

Paul De Koninck is a Professor in the Department of Biochemistry, Microbiology and Bioinformatics at Université Laval and Deputy Scientific Director of Fundamental Research at the CERVO Brain Research Center. His work bridges molecular neuroscience with advanced neurophotonics technologies to unravel mechanisms of synaptic plasticity and neuronal signaling. Academic Affiliation: Université Laval (Faculty of Science and Engineering) Leadership Role: Deputy Scientific Director, CERVO Brain Research Center Research focuses on synaptic plasticity , neurophotonics , and optical nanoscopy to study how neurons decode signals and remodel circuits for learning and memory . His lab develops cutting-edge tools like STED microscopy and single molecule imaging to track synaptic molecules in real time. Recent publications highlight his dual focus on neurodegenerative disease mechanisms (e.g., Huntington's disease) and microscopy innovation (machine learning-enhanced STED, fluorescence lifetime imaging). Articles span zebrafish neurobiology , mitochondrial transport regulation , and neurovascular framework development . Scientific Awards: 2018 Université Laval "Professeur étoile" Prize for teaching excellence His lab contributes to major collaborative initiatives, including the Canadian Optogenetics and Vectorology Foundry grant (2021: $4.3M from Brain Canada) and the Greenspine Lab for neurophotonics research. The team combines patch clamp electrophysiology , biochemistry , and quantum dot imaging to study synaptic signaling.

Simon Hardyمشاهده پروفایل

دانشیار

• Computational biology
• Neuroscience
• Cell signaling
• +۹ مورد دیگر

Simon Hardy is an Associate Professor at Laval University, affiliated with the Department of Computer Science and Software Engineering and the Department of Biochemistry, Microbiology, and Bioinformatics. He is also an Investigator at the CERVO Brain Research Centre, focusing on interdisciplinary research at the intersection of computational biology, neuroscience, and systems biology. 2017 – Present: Associate Professor, Laval University 2011 – 2017: Assistant Professor, Laval University 2007 – 2011: Postdoctoral Fellow, Systems Biology Center New York (Mount Sinai School of Medicine) 2010: Short-term Postdoctoral Fellow, National Center for Biological Sciences, India Dr. Hardy’s research develops mathematical and computational models to analyze complex biological systems, particularly neural networks and cellular signaling pathways. His work integrates experimental data with computational methods to predict system responses, identify pathological disruptions, and propose interventions. Key methodologies include dynamic graph analysis, Petri net modeling, and formal methods in systems biology. Recent publications highlight his focus on: 2025: Algorithm development for influence graph representation of signaling networks 2024: Structural plasticity in olfactory bulb neurons and Python tools for neuroscience 2023–2020: Computational approaches to cell migration, metabolic robustness, and network motif analysis 2018–2007: Foundational work on Petri net frameworks, molecular activity visualization, and signal propagation dynamics His laboratory, accessible at http://www2.ift.ulaval.ca/~hardy/ , emphasizes collaboration with experimental biologists to generate hypotheses through modeling. He utilizes control theory and computational methods to study cell regulation mechanisms.

Igor Timofeevمشاهده پروفایل

استاد

• Sleep Neuroscience
• Epilepsy
• Synaptic Plasticity
• +۵ مورد دیگر

Dr. Igor Timofeev is a Full Professor in the Department of Psychiatry and Neuroscience at Université Laval's Faculty of Medicine. His research focuses on corticothalamic oscillations during sleep and waking states, synaptic plasticity, and the pathophysiology of epilepsy, with a strong emphasis on memory consolidation and brain injury outcomes. He is affiliated with the Centre de recherche de l’Institut universitaire en santé mentale de Québec (CRIUSMQ). PhD in Physiology from Bogomolets Institute of Physiology (1993, Ukraine) Postdoctoral training at Université Laval (1994-2000) Dr. Timofeev's research explores: Thalamocortical mechanisms in slow-wave sleep and memory Epileptogenesis following brain trauma Thalamic regulation of cortical synchronization His work combines electrophysiology, optogenetics, and computational modeling to address fundamental questions in neuroscience. Scientific awards include: 1996-2000: Savoy Foundation and FRSQ fellowships 2003-2008: CIHR scholar 2006, 2016: Prix Jacques-Leblanc and John Kershman Lecture 2009: NSERC and Georgia Science Foundation certificates Dr. Timofeev supervises PhD and Master's students in thalamocortical research. His lab receives funding from Canadian Institutes of Health Research (CIHR) and Natural Sciences and Engineering Research Council (NSERC), including a 2024 NSERC grant for 'Thalamic Gating During Sleep Oscillations.' Based at the CERVO Brain Research Centre, his team includes research assistants, technicians, postdoctoral fellows, and graduate students, with a focus on in vivo electrophysiology and translational models of neurological disorders.

• Microwave Engineering
• Electromagnetism
• Power Amplifiers
• +۹ مورد دیگر

Professor Ammar B. Kouki is affiliated with the École de Technologie Supérieure in the Department of Electrical Engineering . With a Ph.D. from the University of Illinois and academic roots at Pennsylvania State University, his work bridges microwave engineering, electromagnetism, and wireless systems. Research Axes: Aeronautics/Aerospace, Microwave Circuits, Electromagnetic Modeling Labs: LACIME Laboratory His research interests focus on: RF and microwave circuit design Antenna arrays for 5G and satellite communications Power amplifier efficiency and linearity LTCC (Low-Temperature Co-fired Ceramic) integration MEMS-based reconfigurable systems Thermoelectric energy harvesting Notable article trends include advancements in: LTCC cavity-backed phased arrays for Ka-band 3D microfabrication techniques Harmonic optimization for Class-GF amplifiers Fluidic tuners for microwave adaptability Electromagnetic education via AI Thermal management in GaN HEMTs Academic Leadership : Supervised 20+ graduate theses (PhD and Master’s) Collaborated with industry leaders (Ghannouchi, Gagnon, Landry) Authored 91 peer-reviewed journal articles and 150+ conference reports Holds 8 patents in RF duplexer and amplifier technologies

Kashif Mahmudمشاهده پروفایل

استادیار

• Remote Sensing
• Hydrogeology
• Terrestrial Carbon Cycle
• +۱۲ مورد دیگر

Kashif Mahmud is an Assistant Professor at the Kimbell School of Geosciences, Midwestern State University, and an Adjunct Senior Lecturer at the School of Biological, Earth and Environmental Sciences, University of New South Wales. His research integrates remote sensing, hydrogeology, and carbon cycle dynamics, focusing on karst environments, groundwater recharge, and climate change impacts. Develops innovative methodologies using terrestrial LiDAR and drip loggers for subsurface hydrology studies Specializes in data assimilation for improving terrestrial biosphere model predictions Collaborates on international projects like the ARC-funded 'Caves and their stalagmites: linking climate to groundwater recharge' His lab engages in advanced geospatial projects, including the 'Texas as Art' initiative and NSF-funded GeoTech Center activities. Research areas span from cave hydrology to wildfire smoke impact analysis, with a strong emphasis on computational modeling and environmental sustainability. Recent publications highlight his expertise in: Stochastic modeling of karst aquifers with training image algorithms LiDAR-based biomass estimation for urban forests Climate change feedbacks in terrestrial carbon cycling Wildfire PM2.5 pollution dynamics using satellite data The lab's work has received recognition through student awards (AIPG Shoemaker Award, GSA Karst Division Grant) and collaborative grants like the $3,038,909 ARC project. He supervises graduate students in projects ranging from cave exploration with emerging technologies to spatiotemporal deforestation analysis, maintaining active fieldwork at sites like Natural Bridge Caverns, Texas.

Pablo Lemosمشاهده پروفایل

پژوهشگر ارشد

• Cosmology
• Machine Learning
• Astrophysics
• +۳ مورد دیگر

Pablo Lemos is a postdoctoral Research Fellow at the Montrel Institute for Learning Algorithms (MILA) and the CIELA institute at the University of Montreal, where he is affiliated with the Department of Physics. He co-leads the accelerated forward modelling group at the Simons Collaboration in Learning the Universe and is a member of the Dark Energy Survey (DES) collaboration. Research Focus Lemos specializes in applying machine learning techniques to astrophysics and cosmology problems. His core research areas include: Graph neural networks for cosmological simulations Symbolic regression methods for data analysis Simulation-based inference techniques Bayesian inverse problem solving Large-scale structure analysis Publication Analysis Lemos's recent publications (2024-2025) demonstrate strong interdisciplinary work combining cosmology, astrophysics, and machine learning. Major themes include cosmological constraints from galaxy clustering and weak lensing, advanced Bayesian inference methods using diffusion models, and applications of neural networks to astrophysical data. Approximately 60% of recent publications focus on machine learning applications in cosmology, while 25% address astrophysical inverse problems, and 15% explore cometary science and planetary physics. Collaborations and Groups Co-leader of accelerated forward modelling group at Simons Collaboration in Learning the Universe Active member of Dark Energy Survey (DES) collaboration

Melike Erol Kantarciمشاهده پروفایل

دانشیار

• 5G and 6G Networks
• Artificial Intelligence (AI)
• Tactile Internet
• +۹ مورد دیگر

Dr. Melike Erol-Kantarci is an Associate Professor at the School of Electrical Engineering and Computer Science, University of Ottawa, and a Canada Research Chair in AI-enabled Next-Generation Wireless Networks. She founded the Networked Systems and Communications Research (NETCORE) Laboratory and holds a courtesy appointment as Assistant Professor at Clarkson University's Electrical and Computer Engineering Department. With over 6,000 citations and an h-index of 40, she contributes to IEEE as a Senior Member, chairs the Green Smart Grid Communications special interest group, and serves as Editor for IEEE Communications Letters and IEEE Access . Research Focus: 5G/6G wireless networks AI/ML-driven network optimization Smart grid communications Cyber-physical system security Edge computing and IoT Reconfigurable Intelligent Surfaces (RIS) Scientific Contributions: Her recent publications highlight generative AI integration in 6G, intent-driven network management using hierarchical reinforcement learning, physical layer security for connected vehicles, and explainable AI frameworks in communications. The 15 most recent works (2024-2025) span topics like beamforming optimization, federated learning security, UAV-assisted networks, and semantic communication systems. Leadership: As director of the NETCORE Laboratory, she leads cutting-edge research in networked systems, bridging wireless communication paradigms with energy sustainability and security requirements for next-generation networks.

Harry Hongyu Guoمشاهده پروفایل

استاد مدعو

• Machine Learning
• Deep Learning
• Natural Language Processing
• +۷ مورد دیگر

Harry Hongyu Guo is an Adjunct Professor at the School of Electrical Engineering and Computer Science, University of Ottawa, and a Senior Researcher Officer at the National Research Council Canada (NRC). He holds a BEng and a PhD in Computer Science from Shanghai Jiao Tong University and the University of Ottawa, respectively. Education BEng, Computer Science, Shanghai Jiao Tong University PhD, Computer Science, University of Ottawa His research focuses on advancing machine learning and deep learning for transformative applications in scientific discovery, natural language processing, and computer vision, with a strong emphasis on molecular design for health and climate solutions in collaboration with Yoshua Bengio at Mila. Key areas include protein design, drug discovery, geometric representation learning, and crystalline material modeling. Recent publications highlight work on structure-based drug design using denoising diffusion models (PNAS 2025), protein conformation generation (ICLR 2025), and molecular assembly frameworks (ICLR 2025). His projects also explore AI-driven battery discovery (arXiv 2025) and neural operating system simulations (arXiv 2025). Scientific Awards Excellence in Research Award at NRC-DT (2024) Best Paper Award at Canadian AI (2021) Best Paper Awards at *SEM (2015), MLDM (2012), NRC-IIT (2011) Distinguished Papers Award at ECML-PKDD (2006) Guo serves on program committees for major conferences (ICLR, NeurIPS, ICML) and contributes to interdisciplinary research at the intersection of AI, biology, and materials science.

• Quantum Computing
• Quantum Cryptography
• Classical Cryptography
• +۶ مورد دیگر

Gilles Brassard is a Full Professor in the Department of Computer Science and Operations Research at the Université de Montréal's Faculty of Arts and Sciences. He holds the Canada Research Chair in Quantum Computing and serves as Scientific Director of INTRIQ (Institut transdisciplinaire d'information quantique). His affiliations include membership in the Centre de recherches mathématiques (CRM), Institut Courtois, LITQ (Laboratoire d’informatique théorique et quantique), and talents (Laboratoire d'Intelligence Artificielle pour la Cybersécurité). Brassard's research spans quantum computing, quantum and classical cryptography, foundations of quantum mechanics, and privacy protection. He pioneered quantum teleportation and quantum cryptography, demonstrating how quantum mechanics enables unconditionally secure communication. His work explores quantum advantages in computation, including algorithms that could break classical cryptography while quantum cryptography provides countermeasures. Key concepts he developed include quantum teleportation (inspiring Star Trek-like applications) and quantum pseudo-telepathy games. His recent publications reveal strong focus on quantum key distribution security proofs, relativistic cryptography for secure positioning, and privacy protection against data brokers. Trends show increasing emphasis on practical quantum cryptography implementations, noise resilience in quantum communication, and intersections with machine learning. The 2023-2025 articles particularly address real-world quantum security challenges and foundational quantum information questions. Gerhard-Herzberg Canada Gold Medal for Science and Engineering Killam Prize in Natural Sciences Officer of the Order of Canada Fellow of the Royal Society Brassard has supervised over 40 graduate students across quantum information topics, including quantum algorithms, entanglement simulation, and privacy-preserving systems. His current research is funded by major Canadian grants including NSERC Discovery Program ($20965), FRQNT Strategic Regroupments, and CIFAR. Recent projects include QUORUM (Québec Ontario Consortium on Quantum Protocols) and quantum machine learning initiatives. He leads the theoretical quantum information group within LITQ, focusing on quantum communication complexity and cryptographic applications of quantum phenomena.

• Object Recognition
• Computer Vision
• Artificial Intelligence
• +۷ مورد دیگر

Sven Dickinson is a Professor in the Department of Computer Science at the University of Toronto, with a Faculty Affiliate role at the Vector Institute for Artificial Intelligence since 2018. He earned a B.A.Sc in Systems Design Engineering from the University of Waterloo (1983), followed by an M.S. (1988) and Ph.D. (1991) in Computer Science from the University of Maryland. Education : B.A.Sc, Systems Design Engineering, University of Waterloo, 1983 M.S., Computer Science, University of Maryland, 1988 Ph.D., Computer Science, University of Maryland, 1991 His research focuses on generic object recognition, emphasizing shape representation, image abstraction, and feature matching. Dickinson's work bridges human and computer vision, exploring medial axis transforms, shock graphs, and many-to-many feature correspondence for applications in content-based retrieval, robotics, and biomedical imaging. Recent publications highlight geometric disentanglement, symmetric part detection, and contour analysis via deep learning. Scientific Contributions include advancing skeletal abstraction, deformable models, and saliency maps. Collaborative efforts span the University of Maryland, Rutgers, MIT, and the University of Waterloo. He has authored over 100 papers and edited interdisciplinary works like Shape Perception in Human and Computer Vision (Springer, 2013).

Rachel Horstمشاهده پروفایل

مدرس

• Digital Literacy
• Educational Technology
• Futures Literacies
• +۳ مورد دیگر

Rachel Horst is a Lecturer in the Master of Educational Technology (MET) program at the University of British Columbia (UBC), Faculty of Education, Department of Language and Literacy Education. She holds a PhD in Language and Literacy Education from UBC, informed by a decade of secondary teaching experience. PhD in Language and Literacy Education (UBC) Her research explores digital arts-based methods, futures literacies pedagogy, and critical (post)digital literacies through posthumanist and generative AI frameworks. She focuses on ethical technology design, participatory AI systems, and environmental responsibility in digital tools, aiming to reimagine technology's role in education. Rachel teaches courses ETEC 531, ETEC 565H, ETEC 530, and ETEC 565C. Her work emphasizes values-based experimentation, accessibility, and care in educational technology, inviting educators to prototype alternatives that foreground consent and collaborative knowledge creation. She maintains a personal portfolio website ( www.rachelhorst.ca ) and is active on LinkedIn, engaging in public discourse about AI literacy and futures imaginaries. Her research integrates Donna Haraway's theories to challenge conventional technology narratives.

• Space and Place
• Time
• Qualitative Methods
• +۷ مورد دیگر

Dr. Lisa-Jo K. van den Scott serves as an Associate Professor at Memorial University of Newfoundland, where her innovative work bridges spatial sociology, temporal theory, and symbolic interactionism. Her research uniquely explores how physical environments like walls shape social identity, particularly through her foundational Sociology of Walls framework developed during five years of immersive fieldwork in Nunavut. Her academic journey began with an M.A. in Classics from Memorial University before pursuing doctoral studies at Northwestern University. This classical foundation informed her distinctive approach to contemporary sociological questions, especially regarding space, time, and cultural meaning-making. Van den Scott's research program centers on three interconnected pillars: the sociology of space/place (with walls as critical analytical units), the sociology of time (examining temporal resistance and agency), and symbolic interactionism applied to northern contexts. Her work consistently demonstrates how spatial arrangements and temporal practices constitute identity performance, particularly among Inuit communities where she documented remarkable cultural resilience. This tripartite framework extends to analyses of reality television, political transitions, and research ethics. Her 15 most recent publications reveal a methodological commitment to qualitative approaches while traversing diverse substantive areas—from Inuit shamanism's collective memory to temporal resistance strategies and material culture analysis. Key trends include decolonizing spatial theory through northern epistemologies, innovating temporal agency concepts, and advancing symbolic interactionism's relevance to contemporary social issues. Her scholarly recognition includes: 2019 Helena Lopata Mentor Excellence Award from the Society for the Study of Symbolic Interaction As Editor-in-Chief of Symbolic Interaction , van den Scott shapes the field's discourse while co-founding The Avalon Research Society to advance place-based scholarship. Her mentorship excellence extends to teaching advanced seminars on space/time sociology and qualitative methods, where she emphasizes ethical reflexivity—evident in her public letter to students affirming that 'your ideas are important to our society.' She actively cultivates scholarly communities through the Anglo-Nordic Network of Social Research and as co-organizer of the Annual Qualitative Analysis Conference since 2014, creating vital spaces for methodological innovation and interdisciplinary collaboration in qualitative research.

Tianxi Yangمشاهده پروفایل

استادیار

• Food Science
• Analytical Chemistry
• Material Science
• +۵ مورد دیگر

Tianxi Yang is an Assistant Professor of Food Science in the Faculty of Land and Food Systems at the University of British Columbia (UBC) in Vancouver, Canada. Dr. Yang leads the Yang Research Group, which focuses on developing innovative analytical technologies and advanced materials to improve food safety, sustainability, and resilience of agricultural and food systems. Dr. Yang received her PhD in Food Science from the University of Massachusetts Amherst in 2018, followed by a Postdoctoral Research Associate position at BASF's North American Center for Research on Advanced Materials at the same institution in 2019. In 2021, she served as a Research Chemist/ORISE Research Fellow at the U.S. Food and Drug Administration's Center for Food Safety and Applied Nutrition. Dr. Yang's research spans interdisciplinary approaches from Food Science, Analytical Chemistry, Material Science, and Nanotechnology. Her work primarily focuses on three major themes: (1) Nanosensors in food, developing Point-of-Care tools for rapid, on-site food safety testing; (2) Nano-enabled agriculture, creating smart nanomaterials for sustainable farming practices; and (3) Sustainable food packaging, designing biodegradable and intelligent packaging solutions. Her recent publications demonstrate growing expertise in nanoplastic detection, intelligent food packaging, and machine learning applications in food safety monitoring. Applied Sciences 2022 Early Career Investigator Award (2023) U.S. Oak Ridge Institute for Science and Education (ORISE) Fellowship (2019) Institute of Food Technologists (IFT) Tanner Award for most-cited paper (2019) Multiple scholarships including Phi Tau Sigma Student Achievement Scholarship (2018) and North America BASF Science Competition Award (2018) Dr. Yang teaches courses including FNH 200: Exploring Our Food, FNH 302: Food Analysis, and FOOD 520: Advances in Food Analysis. She actively mentors graduate students in her research group and serves in various professional capacities, including as Chair of the Food Bioengineering Subdivision of the American Chemical Society Division of Agricultural and Food Chemistry (2022-2023). Her research is supported by multiple grants focusing on developing innovative solutions for food safety challenges, with recent work on portable devices for microplastic detection gaining international attention through coverage in over 100 news outlets. The Yang Research Group at UBC operates state-of-the-art laboratories equipped for nanomaterial synthesis, food analysis, and sensor development. The team consists of graduate students, postdoctoral fellows, and research associates working collaboratively on interdisciplinary projects at the intersection of food science and nanotechnology.