جستجوی استاد راهنمای دانشگاهی

Sihang Liuمشاهده پروفایل

استادیار

• Computer Architecture
• Computer Systems
• Persistent Memory Systems
• +۳ مورد دیگر

Dr. Sihang Liu is an Assistant Professor in the School of Computer Science at the University of Waterloo. Prior to this role, he served as a visiting faculty member at SystemsResearch@Google. He holds a PhD from the University of Virginia, where his research was supported by the Google Fellowship Award. His academic career has been marked by contributions to computer architecture, systems, and persistent memory technologies. Dr. Liu's research interests span computer architecture, systems, and cybersecurity, with a focus on persistent memory systems, energy-efficient computing, and data center optimization. His work bridges hardware-software co-design and explores challenges in scalable computing, fault tolerance, and sustainable AI systems. His recent publications highlight advancements in adaptive memory tiering (HybridTier), carbon intensity forecasting (EnsembleCI), and securing persistent memory (Side-Channel Attacks on Optane). These contributions underscore his commitment to addressing critical issues in modern computing systems' performance, security, and environmental impact. Awards: Google Fellowship Award (PhD), NVMW Memorable Paper Award Finalist (2019), 2019 MICRO Top Picks Honorable Mention Professional Service: Program committees for ISCA, MICRO, ASPLOS; Artifact evaluation roles in leading conferences As an advisor, Dr. Liu mentors a diverse group of students, including current PhD candidates Henry Tian and Desen Sun, and numerous undergraduates. His lab focuses on innovation in sustainable computing and resilient systems design.

Mohamed Hibat-Allahمشاهده پروفایل

استادیار

• Quantum Computing
• Natural Language Processing
• Machine Learning
• +۲ مورد دیگر

Mohamed Hibat-Allah is an Assistant Professor in the Department of Applied Mathematics at the University of Waterloo, where he researches the intersection of natural language processing and quantum many-body physics. His work focuses on using language models to describe quantum systems and developing machine learning solutions for combinatorial optimization problems applicable to scientific and industrial challenges. His research integrates techniques from natural language processing, quantum physics, and statistical mechanics to advance computational methods for simulating quantum materials and solving complex optimization problems. This interdisciplinary approach bridges theoretical physics with cutting-edge AI methodologies. Analysis of his recent publications reveals a strong thematic focus on quantum machine learning, neural network applications in physics, and variational methods. Key trends include the development of quantum-inspired algorithms, benchmarking of quantum models against classical counterparts, and novel approaches to simulating quantum systems using recurrent neural architectures.

Pengfei Liمشاهده پروفایل

استاد

• Finite Mixture Models
• Empirical Likelihood
• Experimental Design
• +۵ مورد دیگر

Roles & Affiliations Professor at Department of Statistics and Actuarial Science , University of Waterloo since 2012. Serves as Associate Editor for Canadian Journal of Statistics and Metrika . Previously held roles at University of Alberta (2008-2011) and University of British Columbia (2008 postdoc). Education PhD in Statistics (2007) - University of Waterloo MA in Statistics (2004) - Nankai University BSc in Statistics (2001) - Nankai University Research Focus Specializes in statistical methodologies including finite mixture models, empirical likelihood, experimental design, biased sampling problems, capture-recapture data, and density ratio models. Current interests include statistical inference under constraints and analysis of non-probability survey samples. Awards CRM-SSC Prize in Statistics (2022) Institute of Mathematical Statistics Fellow (2022) Multiple awards for teaching and research excellence from University of Waterloo Students & Grants Advised over 10 PhD/Master’s students. Active grants include NSERC funding since 2009 and startup grants from University of Waterloo. Supervises postdocs in statistical methodology development.

Changbao Wuمشاهده پروفایل

استاد

• Survey Methodology
• Complex Surveys
• Empirical Likelihood Methods
• +۶ مورد دیگر

Changbao Wu is a Professor and Chair of the Department of Statistics and Actuarial Science at the University of Waterloo, within the Faculty of Mathematics. His research focuses on complex survey design and analysis, with expertise in empirical likelihood methods, resampling techniques, and missing data problems. He has developed R packages to implement these methods and is a Fellow of the American Statistical Association and Elected Member of the International Statistical Institute, receiving the 2012 CRM-SSC Prize in Statistics. Education: PhD in Statistics (1999) from Simon Fraser University under Prof. Randy Sitter. He has been at Waterloo since 1999. Research Interests: Design and analysis of complex surveys Semiparametric/nonparametric methods Empirical likelihood methods Resampling (jackknife/bootstrap) Missing data and measurement error Survey sampling methodology Professional Roles: Associate Editor: Survey Methodology (2006–), Biometrika (2008–), Journal of Nonparametric Statistics (2011–) Member: Statistics Canada’s Advisory Committee on Statistical Methods Recent Publications Trends: Focus on non-probability survey samples, causal inference, and pseudo-empirical likelihood methods. Recent work addresses challenges in combining non-probability and probability samples, doubly robust estimation, and calibration techniques. Awards: Fellow of ASA (since 2020) Elected ISI Member (since 2012) CRM-SSC Prize (2012) Grants and Advising: Extensive grants related to survey methodology and statistical inference. Advises on the International Tobacco Control (ITC) China Survey and collaborates on large-scale studies like the Canadian Longitudinal Study on Aging (CLSA). Labs/Teams: Leads research in survey statistics and statistical methodology at the University of Waterloo, contributing to interdisciplinary projects involving health, economics, and social sciences.

Bahman Gharesifardمشاهده پروفایل

استاد

• Systems and Control
• Distributed Control and Optimization
• Geometric Control Theory
• +۹ مورد دیگر

Bahman Gharesifard is a Professor in the Department of Mathematics and Statistics at Queen's University, Canada. He holds a Ph.D. from Queen's University (2009) and advanced degrees from Shiraz University (B.Sc., 2002; M.Sc., 2005). His research focuses on systems and control theory, with emphasis on distributed control, optimization, geometric control, and their intersections with network sciences, machine learning, and game theory. He has been recognized with the First Year Instructor Teaching Award in Engineering & Applied Science (2014 & 2016). His academic journey includes postdoctoral research at the University of California, San Diego (2009–2012) and the University of Illinois, Urbana-Champaign (2012–2013). His work bridges theoretical foundations of control systems with practical applications in distributed optimization, neural networks, and contagion models on networks. Recent research trends include advancing Lyapunov-based methods for reinforcement learning, analyzing structural controllability in sparse systems, and developing models for network dynamics using Pólya urn frameworks. His articles explore topics like averaged controllability, flexible-step MPC, and stability in distributed algorithms. Education: Ph.D., Queen's University (2009) M.Sc., Shiraz University (2005) B.Sc., Shiraz University (2002) Awards: Engineering & Applied Science First Year Instructor Teaching Award (2014) Engineering & Applied Science First Year Instructor Teaching Award (2016) He collaborates on projects involving secure distributed optimization, epidemic modeling via Pólya contagion networks, and neural network approximation guarantees. His lab contributes to theoretical control advancements with practical implications in robotics, energy systems, and AI.

Ian Churchمشاهده پروفایل

دانشیار

• Ocean Mapping
• Hydrodynamic Modeling
• Marine Habitat Mapping
• +۲ مورد دیگر

Dr. Ian Church is an Associate Professor in the Department of Geodesy and Geomatics Engineering within the Faculty of Engineering at the University of New Brunswick. He specializes in ocean mapping using acoustics, with primary research interests in integrating hydrodynamic numerical modeling with ocean mapping, marine habitat mapping, acoustic water column interpretation, and evaluating autonomous mapping platforms. His research aims to better understand the marine environment using acoustics and minimize uncertainty in ocean mapping products. Dr. Church received all his degrees (B.Sc.Eng, M.Sc.Eng, Ph.D.) from UNB while working with the Ocean Mapping Group. His professional experience includes operating and managing multibeam sonar systems onboard the coast guard ship Amundsen in the Canadian Arctic (2005-2013), and positions at the University of Southern Mississippi before returning to UNB in 2016. His publications demonstrate consistent focus on hydrographic surveying, ocean mapping technologies, and marine data processing. Recent trends show increased emphasis on AI applications in seabed mapping, advanced sensor technologies, collaborative training programs, and hydrodynamic modeling for coastal management. Dr. Church also contributes to educational initiatives like the COMREN International School on Hydrographic Surveying.

Argyri Paneziمشاهده پروفایل

استادیار

• Digital Information Law
• AI Liability
• Cybersecurity Governance
• +۲ مورد دیگر

Dr. Argyri Panezi is Canada Research Chair in Digital Information Law and Policy at the University of New Brunswick. Her work addresses legal challenges in digital infrastructures, AI governance, and e-justice systems. Education: Ph.D., European University Institute LL.M., Harvard Law School LL.B., University of Athens Panezi's research examines privacy in emerging technologies, copyright reforms for digital libraries, and participatory justice platforms. She directs the Legal Innovation Laboratory, developing solutions for rural access to justice. Publications analyze data property concepts, liability frameworks for AI, and pandemic-era judicial reforms. Recent work emphasizes community-centered technology design. Awards include a Canada Research Chair appointment and Stanford Digital Civil Society fellowship. She leads bilingual access-to-justice initiatives in Atlantic Canada.

Jinjun Shanمشاهده پروفایل

استاد

• Dynamics
• Control Systems
• Navigation
• +۱۱ مورد دیگر

Professor Jinjun Shan is a Full Professor of Space Engineering and former Department Chair (2018-2023) in the Department of Earth and Space Science and Engineering at York University's Lassonde School of Engineering. An internationally recognized expert in dynamics, control and navigation, he joined York University as an Assistant Professor in 2006, was promoted to Associate Professor in 2011, and became a Full Professor in 2016. Dr. Shan received his B.Eng., M.Eng., and Ph.D. degrees from Harbin Institute of Technology, China, in 1997, 1999, and 2002, respectively. Before joining York, he was a Post-Doctoral Fellow at the University of Toronto Institute for Aerospace Studies (2003-2006) and a Research Assistant at City University of Hong Kong (2002-2003). His research focuses on dynamics, control and navigation, autonomous systems, multi-agent systems, smart materials and structures, space instrumentation, active vibration control, and orbit dynamics. Dr. Shan has made significant contributions to national and international space missions including NEOSSat and has attracted over $5 million in research funding from governmental agencies and industry partners. His laboratory, the Spacecraft Dynamics Control and Navigation Laboratory (SDCNLab), which he founded in 2006, conducts cutting-edge research in space engineering. Dr. Shan's extensive publication record includes over 200 peer-reviewed journal and conference papers, with his most recent work focusing on multi-agent formation control, autonomous vehicle decision-making, quadrotor control systems, and smart material applications. His research shows a clear progression from fundamental dynamics and control theory toward increasingly complex multi-agent systems and real-world applications in autonomous vehicles and space engineering. Fellow of Canadian Academy of Engineering (CAE) Fellow of Engineering Institute of Canada (EIC) Fellow of American Astronautical Society (AAS) Associate Fellow of AIAA Alexander von Humboldt Research Fellowship JSPS Fellowship Lassonde Educator of the Year Award (2022) Named in Stanford's list of world's top 2% researchers Dr. Shan has successfully mentored numerous graduate students and post-doctoral fellows, with current advisees working on cutting-edge projects in multi-agent systems, UAV control, and smart materials. His research is supported by substantial funding from NSERC, CSA, and industry partners. As the founding director of SDCNLab, he has built a comprehensive research facility for spacecraft dynamics, control, and navigation, recently expanding to include autonomous unmanned vehicle research through a CFI JELF award. His laboratory continues to make significant contributions to both theoretical advancements and practical applications in space engineering and autonomous systems.

Luigi Benedicentiمشاهده پروفایل

استاد

• Software Agents
• Software Process Improvement
• New Media Technology
• +۳ مورد دیگر

Dr. Luigi Benedicenti is a Professor and Dean of the Faculty of Computer Science at the University of New Brunswick. He holds a Laurea in Electrical Engineering and a Ph.D. in Electrical and Computer Engineering from the University of Genoa, Italy. A licensed Professional Engineer in Saskatchewan and an Italian-licensed Engineer, he collaborates extensively with TRLabs and IEEE, engaging in global research partnerships across Europe, Southeast Asia, and North America. His research focuses on three core areas: Software Agents, Software Process Improvement, and New Media Technology. Current work emphasizes unifying distributed digital service platforms, optimizing delivery across devices and locations. Benedicenti's recent studies explore emotional contagion in open-source collaborations, agile methodologies in mission-critical systems, and decision-support frameworks for software development. Publications highlight themes like emotional dynamics in agile teams, optimization in manufacturing processes, and adaptive frameworks for defense software. His work bridges theoretical models with practical applications in security-critical systems and ubiquitous computing environments. Professional contributions include leadership roles in advancing software engineering practices and fostering interdisciplinary collaboration. His research integrates technical innovation with human-centric design principles to address complex challenges in modern software ecosystems.

Nicholas Touikanمشاهده پروفایل

دانشیار

• Geometric Group Theory
• Algorithmic Group Theory
• Low-dimensional Topology
• +۲ مورد دیگر

Nicholas Touikan is Associate Professor in Mathematics and Statistics at the University of New Brunswick, specializing in geometric group theory. His research examines groups as geometric objects, focusing on computational problems in infinite discrete groups exhibiting large-scale curvature properties. Primary investigations develop algorithms for group-theoretic problems using geometric insights from hyperbolic and negatively curved groups. Complementary research applies low-dimensional topology techniques to analyze group structures and actions. Current projects include solving conjugacy problems for automorphism groups and developing efficient folding algorithms for virtually free groups.

Oliver Terna Iorhemenمشاهده پروفایل

استادیار

• Biological Wastewater Treatment
• Wastewater Reclamation and Reuse
• Nutrients Removal
• +۴ مورد دیگر

Dr. Oliver Terna Iorhemen is an Assistant Professor of Environmental Engineering at the University of Northern British Columbia (UNBC), joining in August 2021. He holds a Ph.D. in Civil Engineering (Environmental Engineering) from the University of Calgary, an MSc from the University of Leeds, and a B.Eng. from Ahmadu Bello University, Nigeria. His research focuses on biological wastewater treatment, resource recovery from wastewater, and rural water supply solutions. He has participated in collaborative projects with municipalities, industries, and universities. Education Ph.D. in Civil Engineering (Environmental Engineering), University of Calgary (2019) MSc(Eng) in Environmental Engineering & Project Management, University of Leeds (2011) B.Eng. in Water Resources & Environmental Engineering, Ahmadu Bello University (2008) Research Interests Dr. Iorhemen’s work emphasizes aerobic granular sludge (AGS) technology for wastewater treatment and resource recovery, including phosphorus removal, contaminants of emerging concern (CEC), and biofilm processes. His current projects explore AGS applications in brewery wastewater treatment, biofilter systems for rural communities, and constructed wetlands in cold climates. He integrates machine learning and data-driven models to optimize bioreactor performance. Scientific Awards Recipient of prestigious awards such as the NSERC Postdoctoral Fellowship , Teaching Achievement Award (UCalgary), and multiple scholarships including the Eyes High International Doctoral Scholarship . Advising & Collaborations Supervises Master’s students in areas like curdlan recovery, xanthan gum extraction, and cold-climate wetland performance. Collaborates with industry partners and municipalities on applied research projects. His team includes researchers like Erik Groenenberg (MASc) and Manveer Kaur (MASc). Labs & Teams Hosts an active research team at UNBC focusing on AGS bioreactors, biofilm dynamics, and sustainable water solutions. Facilities include advanced wastewater treatment setups and analytical laboratories.

Shaon Bhatta Shuvoمشاهده پروفایل

استادیار

• Deep Learning
• Machine Learning
• Reinforcement Learning
• +۴ مورد دیگر

Dr. Shaon Bhatta Shuvo is an Assistant Professor at the University of Windsor's School of Computer Science. He holds a Ph.D. from the University of Windsor (2020–2024), an M.Sc. from South Asian University (2013–2015), and a B.Sc. from Noakhali Science and Technology University, Bangladesh. Research Interests: Deep Learning & Reinforcement Learning: Development and application of advanced algorithms for computer vision and natural language processing. AI-Based Decision Support Systems: Designing AI-driven systems for healthcare and social network analysis. Modelling and Simulation: Multi-agent simulations and mathematical modeling for complex systems, including pandemic preparedness and healthcare optimization. Research Trends in Publications: His work focuses on AI-driven solutions for healthcare (e.g., pandemic modeling, PPE demand prediction), social network analysis (link/node classification, knowledge graphs), and computational epidemiology. He emphasizes hybrid simulation models and data-driven approaches for real-world challenges. Awards: No scientific awards explicitly mentioned. Advising & Grants: No student advisees or grants listed. Labs/Teams: Not specified in available information.

Rishad Iraniمشاهده پروفایل

دانشیار

• Marine Robotics
• Motion Compensation Systems
• Multibody Dynamics
• +۳ مورد دیگر

Dr. Rishad Irani is Associate Professor in Mechanical and Aerospace Engineering at Carleton University, specializing in mechatronic systems for marine applications. His research focuses on motion control and robotic systems for challenging maritime environments. Core research areas: Marine motion compensation Underwater vehicle launch/recovery Robotic machining precision Offshore crane control Current projects develop advanced control algorithms for shipboard crane systems and novel actuation methods for marine platforms, with industry partnerships including Rolls-Royce Marine.

• Knowledge Graphs
• Question Answering Systems
• Data Management
• +۳ مورد دیگر

Abdelghny Orogat is a Contract Instructor at the School of Computer Science, Carleton University, located at Herzberg Laboratories in Ottawa. He specializes in Knowledge Graphs, Question Answering Systems, and Web Technologies with a focus on Data Management and Machine Learning applications. His research includes developing benchmarks for evaluating QA systems over Knowledge Graphs and advancing data analytics in telecom systems through Ericsson's frameworks. He has authored several articles on Knowledge Graph applications, automated benchmarking tools, and web adaptation techniques. Research interests prominently feature Knowledge Graphs, with contributions to datasets like QueryBridge and frameworks such as Maestro and SmartBench. His work bridges theoretical advancements in AI with practical applications in enterprise data management and web technologies. Articles from 2021-2024 highlight trends in QA system evaluation, automated benchmark generation, and scalable data systems. Dr. Orogat has no listed scientific awards or grants in the provided information. He currently holds no documented roles in labs or research teams beyond his instructional duties.

Edward Brownمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Hypertext
• Scientific Visualization
• +۳ مورد دیگر

Dr. Edward Brown is an Associate Professor in the Department of Computer Science at Memorial University of Newfoundland, part of the Faculty of Science. His research focuses on human-computer interaction, hypertext systems, scientific visualization, and legal aspects of technology. He holds degrees from Memorial University (B.Sc.), the University of Toronto (M.Sc., Ph.D.), and the University of Victoria (LL.B.). His current research includes augmented reality applications for marine navigation, multimedia teaching strategies for K-12 education, and the design of user interface agents. Notable projects involve developing hypermedia tools for educational environments and studying complexity in finite-domain problems using genetic algorithms. Dr. Brown also practices technology law and has expertise in intellectual property issues. Teaching responsibilities include courses such as CS2760 (Encountering the Computer) and CS3718 (Programming in the Small). His work bridges computer science with pedagogical innovation and legal implications of emerging technologies.