جستجوی استاد راهنمای دانشگاهی

Adam Diamantمشاهده پروفایل

دانشیار

• Healthcare Analytics
• Artificial Intelligence
• Stochastic Optimization
• +۳ مورد دیگر

Adam Diamant is Associate Professor of Operations Management and Information Systems at York University's Schulich School of Business, where he holds the York Research Chair in Managing AI-Driven Technologies in Health Care. His research applies optimization, machine learning, and stochastic modeling to complex systems in healthcare delivery, supply chain logistics, and inventory management. Methodological expertise includes decomposition techniques, queueing theory, optimal control systems, and predictive analytics. Healthcare applications focus on surgical scheduling, patient flow optimization, and resource allocation during public health emergencies. Recent publications demonstrate strong focus on healthcare operations, including dynamic scheduling for home care providers, operating room management during complications, and PPE demand forecasting during COVID-19. Additional work examines cloud capacity planning and real-time decision systems.

John Friedlanمشاهده پروفایل

دانشیار

• Accounting
• Financial Reporting
• Auditing
• +۳ مورد دیگر

Dr. John Friedlan is an Associate Professor of Accounting at Ontario Tech University’s Faculty of Business and Information Technology, where he also serves as Program Director, Commerce. With over 20 years of experience, he has taught at York University’s Schulich School of Business and holds a PhD from the University of Washington. His research focuses on critical analysis of financial reporting, managerial accounting, and the integration of business analytics into decision-making. Dr. Friedlan has been recognized for his teaching excellence, including the Educator of the Year Award (1992) and the Seymour Schulich Award for Teaching Excellence (2000). His educational background includes a Bachelor of Science from McGill University, an MBA from York University, and a PhD from the University of Washington. Prior to academia, he worked at Nabisco Brands and served on the Board of Examiners at the Canadian Institute of Chartered Accountants, qualifying as a Chartered Accountant in 1980. Dr. Friedlan’s research explores topics such as supply chain resilience, risk-averse decision-making, and disruption management. His work bridges theoretical frameworks with practical applications, leveraging computational methods in operations research and analytics. Recent articles address challenges in electric vehicle infrastructure planning, supply chain recovery strategies, and environmental disclosure practices. He actively contributes to practitioner journals like CGA Magazine and CA Magazine , emphasizing real-world relevance. His scientific contributions include over 15 peer-reviewed articles, with a focus on optimizing complex systems under uncertainty. Beyond research, Dr. Friedlan advocates for experiential learning, integrating industry partnerships to prepare students for data-driven business environments.

Jian Tangمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence
• Bioinformatics
• +۵ مورد دیگر

Jian Tang is an Associate Professor in the Department of Decision Sciences at HEC Montréal, holder of a Canada CIFAR Chair in Artificial Intelligence Education. He earned a Ph.D. in Computer Science from Peking University. His research focuses on machine learning, bioinformatics, and AI applications in drug discovery and protein design. He teaches courses like Machine Learning II: Deep Learning and has supervised four MSc projects in data science and AI applications. Key research interests include graph neural networks, knowledge graphs, protein structure prediction, and AI-driven scientific discovery. His recent work spans LLM reasoning, geometric diffusion models for molecular design, and multi-modal learning for biomedical applications. Notably, he received the HEC Montréal's 2022 New Researcher Award for exceptional scientific contributions. Publications highlight advancements in protein engineering, antibody design, and AI in healthcare. Collaborations include work with institutions like CDPQ on AI R&D and Bombardier on machine learning for demand forecasting. His lab explores cutting-edge AI techniques to address complex problems in medicine and computational biology.

Gilbert Laporteمشاهده پروفایل

استاد

• Logistics
• Mobility
• Combinatorial Optimization
• +۳ مورد دیگر

Gilbert Laporte is a Professor at HEC Montréal since 1976, holding the Canada Research Chair in Distribution Management. He is a globally recognized expert in logistics, mobility, and combinatorial optimization, with over 500 publications and 19 books. His affiliations include GERAD and CIRRELT research centers. Key awards include Fellow of the Royal Society of Canada (1998), Grand Prize for Excellence in Teaching (2001), Grand Prize for Excellence in Research (2012), and the Order of Canada (2019). He earned an honorary PhD from Eindhoven University of Technology in 2016. Research focuses on transportation systems, vehicle routing, and sustainable logistics. Recent work addresses electric truck routing, drone integration, and decarbonization strategies. His contributions span theoretical advancements and real-world applications in humanitarian logistics and urban infrastructure resilience. Laporte collaborates on global challenges, including flood mitigation in Hanoi and dengue fever operational research. His work emphasizes interdisciplinary solutions, combining algorithmic rigor with societal impact.

Ekram Hossainمشاهده پروفایل

استاد

• Wireless Communications
• 6G and Beyond Cellular Networks
• AI/Machine Learning
• +۵ مورد دیگر

Dr. Ekram Hossain is a Professor in the Department of Electrical and Computer Engineering at the University of Manitoba, serving as Associate Chair (Graduate Studies). He is a Fellow of the Canadian Academy of Engineering and the Engineering Institute of Canada, and an IEEE Fellow (2015). His research focuses on wireless communication networks, AI-driven 6G systems, and resource management. He leads the WiCoNS research group and holds editorial roles in top journals like IEEE Transactions on Mobile Computing. Education: Ph.D. in Electrical Engineering (University of Victoria, 2001) Professional Roles: IEEE Distinguished Lecturer (2012-2020), Board Member of IEEE Communications Society Research Interests span 6G networks, reconfigurable intelligent surfaces, non-orthogonal multiple access, and green radio. Notable contributions include over 20 books and numerous award-winning papers. Awards include the 2024 IEEE Education Award and Clarivate Highly Cited Researcher recognition (2017-2024). Awards & Recognition: Multiple IEEE awards, Royal Society of Canada membership, and leadership in professional organizations like IEEE Canada. Advising & Grants: Supervised over 30 graduate students. Secured funding from NSERC and industry partners for projects on heterogeneous networks and 5G/6G technologies. Active in global initiatives like the Next G Alliance Research Council. Labs/Teams: WiCoNS group focuses on AI-driven wireless systems, edge computing, and network virtualization.

• Revenue Management
• Retail Operations
• Customer Choice Modeling
• +۵ مورد دیگر

Guang Li is an Assistant Professor of Management Science and a Scotiabank Scholar at the Smith School of Business, Queen's University. Her research focuses on revenue management, customer choice modeling, and intersections between operations management and marketing, accounting, and finance. She has been funded by NSERC and published in top journals like Operations Research and Manufacturing & Service Operations Management . Education: Ph.D. in Operations Management (2016) – University of Southern California M.Eng. in Materials Science and Engineering (2008) – MIT M.Sc. in Advanced Materials (2008) – National University of Singapore B.Eng. in Materials Engineering (2007) – Nanyang Technological University Research Interests: Guang’s work spans revenue optimization, retail operations, strategic pricing, and sustainability. She employs discrete choice models, NLP, and data analytics to address challenges in supply chains, consumer behavior, and social media impact on mental health. Articles Trends: Recent studies (2023–2025) highlight strategic pricing under consumer learning, remanufacturing technology portfolios, and pandemic-driven retail shifts. Earlier work (2015–2018) explores nested logit models and charitable inventory planning. Awards: Scotiabank Scholar (Queen’s University) Advising & Grants: Funded by NSERC, her projects address retail resilience, customer choice dynamics, and eco-friendly operations. No advisee names are listed in the provided texts. Affiliations: Cross-appointed at the Scotiabank Centre for Customer Analytics, Queen’s University.

• Data Analytics
• Signal Processing
• Operations Research
• +۴ مورد دیگر

Dr. Mikhail Nediak is an Associate Professor at the Smith School of Business, Queen's University. He holds a PhD in Operations Research from Rutgers University and dual MSc degrees in Computer Science and Applied Mathematics. His research focuses on complex Management Science and Operations Research problems with computational components, including revenue management, dynamic pricing, and data-driven optimization. He serves as Associate Dean for Research at the Moscow School of Management SKOLKOVO and holds the Scotiabank Scholar title at Queen's. Education: PhD in Operations Research, Rutgers University (2002) MSc in Computer Science, Rutgers University (2002) MSc in Applied Mathematics, Moscow Institute of Physics and Technology (1997) BSc in Natural Sciences, Moscow Institute of Physics and Technology (1997) Research Interests: Dr. Nediak explores data analytics, signal processing, and optimization algorithms applied to revenue management and strategic consumer behavior. His work integrates techniques like integer programming, control theory, and stochastic simulation to address real-world business challenges. Recent studies examine dynamic pricing under social influence, resale price maintenance, and indirect lending risk pricing. Key Contributions: His articles highlight advancements in scalable bid pricing, strategic consumer cooperation, and discriminatory pricing models. These contributions bridge theoretical optimization frameworks with practical business applications. Awards & Positions: Scotiabank Scholar, Scotiabank Centre for Customer Analytics Associate Director of Research, Smith School of Business Advising & Leadership: Currently supervising academic work across doctoral and master's programs, with a focus on mentoring students in Operations Research and Analytics. His leadership in research administration at Queen's and SKOLKOVO reflects his commitment to advancing academic rigor and industry collaboration.

• Renewable Energy Systems
• Nanomedicine
• Cancer Therapy Modeling
• +۴ مورد دیگر

Madjid Soltani is an Adjunct Assistant Professor specializing in interdisciplinary research at the intersection of energy systems, biomedical engineering, and computational modeling. His work focuses on renewable energy storage technologies, nanomedicine, and personalized cancer therapies. He explores innovative solutions for energy transition challenges, including hydrogen production, battery advancements, and exergoeconomic assessments of energy systems. In biomedical applications, his research addresses drug delivery systems, tumor microenvironment modeling, and radiopharmaceutical therapies. His contributions span theoretical frameworks, computational simulations, and experimental validations. Key research interests include energy storage (e.g., compressed air, liquid air), theranostics, computational oncology, and exergoeconomic analysis. He has published extensively on topics such as biomass integration in energy systems, CRISPR-driven biosensors, and microfluidic tumor models. His work often bridges engineering and healthcare, emphasizing sustainability and precision medicine. Despite no explicit institutional affiliation listed, his research collaborations likely involve multidisciplinary teams in academia and industry. Research Themes: Renewable energy systems, nanomedicine, computational modeling, cancer therapy, exergoeconomics. Notable Contributions: Development of spatiotemporal models for radiopharmaceutical transport, optimization of energy storage frameworks, and bio-inspired thermal efficiency solutions.

Serguei A. Mokhovمشاهده پروفایل

دانشیار مدعو

• Computer Science
• Software Engineering
• Cybersecurity
• +۹ مورد دیگر

Serguei A. Mokhov is an Affiliate Associate Professor in the Department of Computer Science and Software Engineering at Concordia University’s Gina Cody School of Engineering. He also holds the position of Affiliate Assistant Professor at the Concordia Institute for Information Systems Engineering. Additionally, he serves as the Manager for Network, Security & HPC within GCS ENCS and AITS under the Gina Cody School. His research focuses on cybersecurity, high-performance computing (HPC), digital forensics, real-time systems, and distributed computing frameworks like OpenISS and GIPSY. He is actively involved in developing tools for forensic analysis (e.g., Forensic Lucid) and real-time interactive systems for performing arts and multimedia applications. His work bridges computer science with creative technologies, emphasizing interdisciplinary collaboration. Notable projects include the OpenISS framework for real-time broadcast services and the GIPSY system for intensional programming. He has also contributed to machine learning applications in recommendation systems and cybersecurity. His teaching and research support roles involve integrating containerization (e.g., Kubernetes) and HPC into academic and industrial contexts. Recent publications highlight advancements in forensic computing, real-time gesture recognition, and knowledge graph-enhanced recommendation systems. His research often addresses challenges in scalability, interoperability, and real-time performance across diverse domains from digital forensics to interactive art installations.

Claudio Contardoمشاهده پروفایل

دانشیار

• Operations Research
• Logistics Management
• Vehicle Routing
• +۳ مورد دیگر

Claudio Contardo is an Associate Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University. His research focuses on Operations Research, Logistics Management, Vehicle Routing, Location Analysis, Integer and Combinatorial Optimization, and Artificial Intelligence. He holds an ORCID identifier (0000-0001-7595-3904) and maintains an active academic presence through publications and collaborations. His work emphasizes optimization algorithms for complex systems, including transportation networks, biomedical logistics, and automated systems. Recent contributions include iterative exact algorithms for biomedical sample transportation and counterfactual explanations for k-Nearest Neighbors models. His research bridges theoretical optimization with practical applications in urban mobility, healthcare logistics, and AI explainability. Contardo’s methodologies often involve decomposition techniques (e.g., Dantzig-Wolfe, column generation) and integration of mathematical programming with data-driven approaches. Despite prolific output, no explicit awards or grants are listed in the provided materials. His CV and full publication list are accessible via the provided link.

William Thurberمشاهده پروفایل

دانشگاهی

• Business Analytics
• Supply Chain Management
• Operations Research
• +۳ مورد دیگر

William Thurber is an Associate Teaching Professor in the Faculty of Business and Information Technology (FBIT) at Ontario Tech University, specializing in Communications/Marketing. He joined FBIT in 2009 after a career in private-sector entrepreneurship and leadership roles in national trade associations, including a notable anti-impaired driving initiative. Active in both academic and community roles, he serves on the Board of the Oshawa Kicks Soccer Club and contributes to research in business analytics and supply chain resilience. Thurber holds an MBA from Clarkson University and a Bachelor of Arts from Eisenhower College. His research focuses on optimizing supply chain networks, risk management in logistics, and sustainable energy infrastructure planning. He is affiliated with the Software and Informatics Research Centre (SIRC) and collaborates with the Business Analytics & AI Research Group, advancing data-driven decision-making techniques. His work integrates computational methods to address real-world challenges such as electric vehicle charging station planning, disruption risk mitigation in supply chains, and resilient infrastructure design. While no specific awards are listed, his contributions to academic and applied research have impacted operational efficiency and sustainability in business systems.

Asifa Aamirمشاهده پروفایل

دانشگاهی

• Information Systems
• Business Processes and IT
• User Experience
• +۴ مورد دیگر

Asifa Aamir is an Associate Teaching Professor at Ontario Tech University's Faculty of Business and Information Technology. Her research focuses on information systems, instructional technologies, and hybrid learning models. She investigates strategies to bridge gender gaps in STEM through gamification and user-centric design. Her work also explores the strategic use of new technologies in academia and business environments. Education: SAP Certified Application Associate - Business Process Integration (SAP S/4HANA) Master of Business Administration (Technology Management), University of Duisburg-Essen Master of Philosophy (Information Systems Engineering), Ontario Tech University Master of Science (Computer Sciences), UMIST, Manchester Bachelor's, Quaid-e-Azam University, Pakistan Research Interests: Asifa's work spans information systems engineering, business-process optimization, and the integration of technology in education. She emphasizes user experience design, hybrid learning frameworks, and the impact of emerging technologies on academic and corporate landscapes. Her projects often address accessibility and equity in STEM through innovative instructional tools. Research Trends: Her publications highlight optimization methodologies (e.g., Benders decomposition) and risk management in supply chains, transportation systems, and environmental policy. Recent work emphasizes sustainable infrastructure (e.g., EV charging networks) and data-driven decision-making in logistics. Awards: None explicitly listed. Advising & Grants: While no student advisees are noted, her role emphasizes pedagogical innovation and curriculum development. She contributes to experiential learning initiatives within the Faculty of Business and IT. Labs/Teams: Collaborates with the Business Analytics & AI Research Group, focusing on data-driven solutions for business and academic challenges.

Christopher L E Swartzمشاهده پروفایل

استاد

• Applied Optimization
• Process Operations
• Process Design
• +۷ مورد دیگر

Dr. Christopher L E Swartz is a Professor and the ArcelorMittal Dofasco Chair in Process Automation and Information Technology within the Department of Chemical Engineering at McMaster University. He earned his Ph.D. in Chemical Engineering from the University of Wisconsin-Madison and has held academic positions at the University of Cape Town for 11 years before joining McMaster in 2000. His research focuses on applied optimization in process operations and design, with key thrusts in design for dynamic performance, dynamic real-time optimization, and supply chain planning/scheduling optimization. His scholarly work spans interdisciplinary subfields such as nonlinear model predictive control (MPC), robust optimization, and industrial process modeling. He has led collaborations through the McMaster Advanced Control Consortium (MACC), where he served as Director for a decade, and partnered with institutions like Imperial College London and California Institute of Technology as a visiting scholar. Teaching roles include Process Control (CHEMENG 3P04) and Digital Computer Process Control (CHEMENG 6E03/4E03) at McMaster University.

• Hydraulic Transients
• Water Distribution Systems
• Pipeline Optimization
• +۳ مورد دیگر

Brian Karney is an Adjunct Associate Professor in the Department of Civil Engineering at McMaster University. His work focuses on hydraulic transients, water distribution systems, and energy efficiency in pipeline networks. Academic rank: Adjunct Associate Professor Institution: McMaster University Research areas: Transient flow analysis, pipeline optimization, and sustainable infrastructure Dr. Karney’s research interests bridge theoretical and applied hydraulic engineering. He investigates transient fault detection, air management in pressurized systems, and energy transformations in water networks. His work includes field testing of mobile DMA units for leakage assessment and computational modeling of surge protection strategies. Recent scholarly activity trends show a focus on transient pressure modeling (e.g., Godunov schemes for dam-break flows), air valve optimization, and value-based decision frameworks for pipe maintenance. His studies address challenges like energy dissipation in rapid filling pipelines and dynamic effects in two-phase flows. Key collaborative efforts involve international conferences (IAHR, ASCE) and interdisciplinary projects on climate adaptation, water quality, and infrastructure resilience. While no formal awards are listed, his publications span 30+ years of influential contributions to hydraulic transient theory and practice.

David Rolnickمشاهده پروفایل

استادیار

• Machine Learning
• Climate Change
• Environmental Science
• +۳ مورد دیگر

David Rolnick is an Assistant Professor and Canada CIFAR AI Chair at McGill University's School of Computer Science and Mila – Quebec AI Institute. His research focuses on applying machine learning to address climate change challenges, including biodiversity monitoring, land use classification, climate modeling, and materials discovery. He co-founded Climate Change AI and leads initiatives like the NSF-NSERC Global Center on AI and Biodiversity Change (ABC). Rolnick's work emphasizes developing transfer learning and meta-learning techniques to handle sparse data in climate-related applications, such as predicting energy demand and simulating cloud formations. He has been recognized with the Sloan Research Fellowship and MIT Technology Review's '35 Innovators Under 35' distinction. Education: Postdoctoral research at the University of Pennsylvania (NSF Mathematical Sciences Postdoctoral Fellow), PhD from MIT (NSF Graduate Research Fellow). Research interests span AI applications in climate science, including energy systems optimization, satellite imagery analysis for environmental monitoring, and causal representation learning in climate data. His lab explores ethical AI deployment, particularly mitigating negative applications like oil exploration while addressing energy consumption concerns in ML. Key projects include ClimART (a climate radiative transfer benchmark), OpenForest (a forest monitoring data catalog), and collaborations on fusion energy modeling. Awards include the AI2050 Fellowship for transformative research impact. Awards: Sloan Research Fellow, AI2050 Fellow, MIT TR35 Grants: NSF-NSERC Global Center, Climate Change AI initiatives Labs/Teams: McGill Climate AI Group, Mila collaborations