جست‌وجوی استاد و پژوهشگر

Mojgan A. Jadidiمشاهده پروفایل

دانشیار

• Geospatial Visual Analytics
• Building Information Modeling (BIM)
• 3D GIS Integration
• +۵ مورد دیگر

Dr. Mojgan A. Jadidi serves as Associate Professor in the Teaching Stream and Director of Common Engineering & BSc Science within the Department of Civil Engineering at York University's Lassonde School of Engineering. A Professional Engineer (P.Eng) and founder of the GeoVA Lab, she leads research at the intersection of geospatial analytics, digital infrastructure, and innovative engineering education aligned with UN Sustainable Development Goals. Education: PhD in Geomatics, Université Laval (2014) MSc in Earthquake and Seismology Engineering, ROSE Center (Italy) & Université Joseph Fourier (France) BSc in Civil-Survey Engineering, Iranian University of Science and Technology Research Focus: Her pioneering work in Geospatial Visual Analytics spans 2D/3D environments, Building Information Modeling (BIM) and 3D GIS integration, and Spatial Quantum Computing applications for smart cities. She develops Infrastructure Digital Twins using sensor data fusion while revolutionizing engineering education through gamification and augmented/virtual reality pedagogies that transform complex spatial concepts into immersive learning experiences. Research Trends: Recent publications (2021-2023) demonstrate convergent innovation across three domains: (1) Building energy optimization through BIM-graph analytics, (2) Transportation safety via AI-driven situational awareness, and (3) Educational technology using VR sandboxes and visual-verbal comics. These works consistently integrate quantum computing principles and UN SDG frameworks to solve urban sustainability challenges. Scientific Recognition: ASEE Zone III Best Paper Award (2023) ASEE Saint Lawrence Best Research Paper & Poster (2022) 3D GeoInfo Conference Best Paper (2018) NSERC Postdoctoral Fellowship (2016) ESRI Student Award (2011) Erasmus Mundus Scholarship (2006) Research Leadership: As Associate Director of York's ESRI Center of Excellence, she manages multi-source funding from NSERC, Mitacs, and York University internal grants. Her professional service spans global organizations including ISPRS Commission IV (Secretary), IEEE Women in Engineering (Member), PEO Etobicoke (Chair), and buildingSMART Canada (Committee Member), driving standards for BIM and digital twin implementation in urban infrastructure. Lab Innovation: The GeoVA Lab develops cutting-edge tools including the TopoSurvey Game for immersive surveying education, PAN-Lassonde XR Sandbox for virtual lab experiences, and quantum computing frameworks for bike-sharing optimization, establishing new paradigms in spatial data interaction and engineering pedagogy.

Brian Greenspanمشاهده پروفایل

دانشیار

• Digital Humanities
• Utopian Studies
• New Narrative Media
• +۴ مورد دیگر

Brian Greenspan is an Associate Professor in the Department of English Language and Literature at Carleton University, within the Faculty of Arts and Social Sciences. His research focuses on digital humanities, utopian studies, and new narrative media, particularly exploring intersections between print narratives and emerging technologies like hypertext, video games, and augmented reality. Greenspan co-developed the StoryTrek locative media system, used for creating spatial storytelling projects that merge urban geography with fictional and historical narratives. He holds a Ph.D. from the University of Toronto and has received multiple grants including SSHRC Partnership Grants (2015-18), a Leverhulme International Research Network Grant (2014-16), and a Teaching Achievement Award (2017). His work emphasizes speculative archives and the ethical implications of digital media in cultural preservation and future imaginaries. Greenspan collaborates extensively with institutions like Carleton’s Hyperlab and has delivered keynote lectures globally, including at the Digital Humanities Summer Institute and the Canadian Game Studies Association. His research integrates interdisciplinary approaches to spatial narratives, wearable media, and critical utopian theory. Current projects involve mapping fictional cityscapes onto real urban environments to explore alternate historical and speculative futures. As a supervisor, Greenspan guides doctoral students in areas like digital games, cultural mediations, and narrative transformation. His grants include collaborations on infrastructure development, animation archives, and the political economy of digital games.

Erik Schemeمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Machine Learning
• Neuroprosthetics
• +۵ مورد دیگر

Erik Scheme is an Associate Professor in the Department of Electrical and Computer Engineering at the University of New Brunswick (UNB), and serves as Associate Director of the Institute of Biomedical Engineering (IBME). He holds a PhD and is a Professional Engineer (PEng). His roles include advising the Dr. J. Herbert Smith Centre for Technology Management and Entrepreneurship, emphasizing innovation in biomedical technologies and healthcare systems. His research focuses on advanced human-machine interaction through biomedical engineering, with a strong emphasis on myoelectric prosthetics, wearable sensors, and machine learning applications. Key areas include improving neuroprosthetic control via incremental learning, gait analysis using underfoot pressure sensors, and developing robust EMG-based gesture recognition systems. His work bridges clinical needs with technological innovation, addressing challenges in rehabilitation, activity monitoring, and user-centric design. Recent publications highlight advancements in adaptive control systems, sensor fusion, and ethical data practices in healthcare. His contributions span both theoretical frameworks (e.g., self-supervised learning models) and applied technologies (e.g., gold-plated 3D-printed electrodes). Dr. Scheme collaborates across disciplines, integrating robotics, signal processing, and clinical validation to create impactful solutions. His lab, affiliated with IBME, actively explores emerging areas like exhaled breath analysis for disease detection and federated learning in healthcare data analytics.

Laura J. Holtمشاهده پروفایل

استاد

• Addiction Research
• Clinical Psychology
• Substance Abuse Prevention
• +۷ مورد دیگر

Laura J. Holt is a Professor of Psychology at Trinity College, where she has been a faculty member since 2008. Her research focuses on addiction, substance use prevention, and community-based interventions. She holds a B.A. in Psychology from Trinity College, an M.S. and Ph.D. in Clinical Psychology from Rutgers University, and completed postdoctoral training at Yale University School of Medicine and the Department of Veterans Affairs. Her work emphasizes the role of family, peers, and societal factors in shaping psychological outcomes and effective treatment strategies. Holt’s research lab engages Trinity undergraduates in projects addressing healthier college relationships, substance use reduction, and community outreach. Students contribute through data collection, analysis, and publication preparation. She strongly advocates for liberal arts education, highlighting its role in fostering critical thinking, student-faculty collaboration, and community engagement. Her research themes include e-cigarette dependence, prescription stimulant misuse, and the intersection of mental health with substance use. She has explored motivational factors in substance use cessation and the impact of faculty-student rapport on academic success. Her lab’s activities emphasize practical skills for students pursuing clinical or counseling psychology careers. No scientific awards are explicitly listed in the provided materials. However, her extensive contributions to addiction research and mentorship are evident through her prolific publication record and collaborative projects. Holt advises students such as Alice Verdier ’22, Angie Delucia ’22, and Maddie Shapiro ’22, reflecting her commitment to undergraduate research. Her work integrates community partnerships and evidence-based interventions to address public health challenges, particularly among emerging adults. The Holt Research Lab serves as a hub for collaborative projects, offering students hands-on experience in qualitative and quantitative research methods (e.g., Atlas.ti, SPSS). This environment prepares students for graduate studies and careers in clinical psychology and related fields.

Kirk R. Pruhsمشاهده پروفایل

استاد

• Algorithmic problems related to green computing
• Fair allocation
• Resource management
• +۳ مورد دیگر

Professor Kirk R. Pruhs is a full Professor in the Department of Computer Science at the University of Pittsburgh's School of Computing and Information. He holds editorial roles at journals such as the Journal of Scheduling and ACM Transactions on Algorithms. His research focuses on algorithmic problems in green computing, scheduling, online optimization, and resource management. Pruhs has advised numerous PhD students and has a strong publication record in top venues like SODA, STOC, and FOCS. His work often addresses energy-efficient algorithms and computational resource management. Notable contributions include studies on stochastic scheduling, energy-efficient routing, and competitive analysis of online algorithms. Education: BS in Mathematics and Computer Science from Iowa State University (1984), PhD in Computer Science from University of Wisconsin-Madison (1989). Research Interests: Algorithmic challenges in green computing, fair allocation mechanisms, scheduling under uncertainty, and online optimization techniques. He explores how computational methods can improve energy efficiency and resource allocation in distributed systems. Recent articles focus on robust scheduling strategies, stochastic systems, and algorithmic approaches to network design and resource optimization. His work bridges theoretical computer science with practical applications in sustainable computing. Students: Includes Jonathan Beaver (2006), Mohamed Aly (2008), Christine Chung (2009), Daniel Cole (2013), Neal Barcelo (2015), Michael Nugent (2015), and Alireza Samadian Zakaria (2021). Labs/Teams: Engaged in algorithm design and analysis within the Department of Computer Science, contributing to initiatives in computational sustainability and high-performance computing.

Nidhi Hegdeمشاهده پروفایل

دانشیار

• Privacy-Preserving Machine Learning
• Algorithmic Fairness
• Distributed Systems
• +۲ مورد دیگر

Dr. Nidhi Hegde is an Associate Professor in the Department of Computing Science at the University of Alberta and a Canada CIFAR AI Chair at the Alberta Machine Intelligence Institute (Amii). Her research focuses on privacy-preserving machine learning, algorithmic fairness, and robust algorithm design for networked systems. Dr. Hegde's current research investigates differential privacy in bandit algorithms, debiasing frameworks for language models, and long-term fairness guarantees for minority groups. Her work combines theoretical foundations with practical applications in distributed systems and multi-agent learning environments. Recent publications address covariate shift effects in optimization, private matroid optimization, and reinforcement learning with functional noise. She teaches graduate courses on Responsible AI and Ethical Issues in Data Analytics, covering topics including data privacy, fairness in algorithms, interpretability, and accountability. Dr. Hegde maintains active research collaborations and previously led privacy research at Borealis AI (RBC's research institute).

• Software Engineering
• Video Game Development
• Artificial Intelligence for Software Engineering (AI4SE)
• +۴ مورد دیگر

Cristiano Politowski is an Assistant Professor in the Department of Computer Science at Ontario Tech University’s Faculty of Science. His research focuses on applying software engineering principles to video game development, with particular emphasis on software testing, artificial intelligence for software engineering (AI4SE), deep reinforcement learning, and empirical software engineering. Education includes a PhD in Computer Science and Software Engineering from Concordia University (2022), supervised by Professors Yann-Gaël Guéhéneuc and Fabio Petrillo. Prior to his current role, he held postdoctoral positions at Université de Montréal and École de Technologie Supérieure in Montréal, Canada. Research interests span game engine architecture analysis, automated testing methodologies for games, and bridging gaps between academic theory and industry practices in software engineering. His work often involves empirical studies on software quality, framework impacts, and event-driven systems. Publications reflect a focus on game development challenges, including studies on API compatibility, subsystem coupling visualization, and AI-driven game balance assessment. He actively contributes to the understanding of software processes in the video game industry through surveys and dataset curation initiatives like PlayMyData.

• Microeconomic Theory
• Game Theory
• Industrial Organization
• +۱ مورد دیگر

Maxim Ivanov serves as Associate Professor in the Department of Economics at McMaster University, where he teaches advanced courses including Microeconomic Theory II (ECON 722), Introduction to Game Theory (ECON 3M03), and Industrial Organization (ECON 784/3S03) through 2025. His research centers on strategic information transmission and game-theoretic modeling in economic contexts. His academic credentials include a PhD in Economics from Penn State University, a Master's in Economics from the New Economic School (Moscow), and a Master of Science (Cum laude) in Electrical Engineering from Tomsk State University of Control Systems and Radio Electronics. This interdisciplinary foundation supports his rigorous analytical approach. Ivanov's scholarly work focuses on Microeconomic Theory, Game Theory, and Industrial Organization, with particular emphasis on information design, cheap talk models, and strategic communication mechanisms. His research investigates how private information structures and communication protocols shape economic outcomes in competitive and organizational settings. His 10 journal publications (2010-2024) in outlets like Economic Theory , Games and Economic Behavior , and Journal of Economic Theory reveal a cohesive trajectory: evolving from foundational studies on information revelation (2010-2013) to sophisticated analyses of Bayesian persuasion and private information design (2021-2024). The work consistently addresses equilibrium selection and welfare implications in strategic communication. No scientific awards are documented in the available institutional records. Professor Ivanov maintains an active teaching schedule with no recorded advisees or graduate supervision in the provided data. The VIVO database indicates no active research grants, and co-author networks show exclusively solo publications within McMaster's system since 2015. No laboratory affiliations or research teams are mentioned in the institutional profiles.

Doug L. Jamesمشاهده پروفایل

استاد

• Computer Graphics
• Computer Sound Synthesis
• Physically Based Modeling and Animation
• +۳ مورد دیگر

Doug L. James is a Full Professor of Computer Science at Stanford University since 2015, following roles as Associate Professor at Cornell University (2006-2015) and Assistant Professor at Carnegie Mellon University (2002-2006). He holds a PhD in Applied Mathematics from the University of British Columbia (2001), alongside earlier degrees from the same institution and the University of Western Ontario. His research focuses on computer graphics, sound synthesis, and physically-based modeling, with notable contributions to fluid simulation, cloth animation, and medical modeling. Key achievements include the 2012 Technical Achievement Award from the Academy of Motion Picture Arts and Sciences for 'Wavelet Turbulence,' and the 2013 Katayanagi Prize. He serves as a consulting Senior Research Scientist at Pixar Animation Studios and has led roles like Technical Papers Chair at SIGGRAPH 2015. His work integrates physics-based principles with interactive systems, emphasizing real-time applications and data-driven methods. Research interests span sound synthesis for animations (e.g., cloth, water, impact sounds), deformable models for medical simulation, and tools like 'svMorph' for virtual surgery planning. His publications reflect a blend of algorithmic innovation and practical applications in film, gaming, and healthcare.

Casey Reasمشاهده پروفایل

استاد

• Generative Art
• Digital Media
• Computer Graphics
• +۴ مورد دیگر

Casey Reas is a Professor in the Department of Design Media Arts at the University of California, Los Angeles (UCLA), where he also co-directs UCLA Social Software. He holds a Master's in Media Arts and Sciences from MIT and a Bachelor's from the University of Cincinnati's College of Design. A pioneering figure in generative art and digital media, Reas co-founded the open-source programming language Processing, revolutionizing computational creativity for artists and designers. His work spans software installations, prints, and collaborative projects exhibited globally at institutions like the Centre Pompidou and the Whitney Museum. His research explores intersections of technology, art, and pedagogy, reflected in books such as Compressed Cinema and Making Pictures with Generative Adversarial Networks . Reas' practice emphasizes algorithmic processes and machine learning, exemplified in series like Untitled Film Stills and Compressed Cinema . He actively contributes to initiatives like UCLA’s Game Lab and the Conditional Studio, fostering interdisciplinary innovation. His work balances technical rigor with aesthetic exploration, bridging art, science, and technology.

Robert Xiaoمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۴ مورد دیگر

Robert Xiao is an Assistant Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Designing for People research cluster. He holds a Ph.D. from Carnegie Mellon University and a BMath from the University of Waterloo. His research focuses on interactive technologies, including VR/AR interfaces, sensing systems, and cybersecurity. Notable contributions include Lumitrack (tracking system), TouchTools (touch interaction), and CVE-2023-37271 (Python sandbox exploit). Education: Ph.D., Human-Computer Interaction Institute, Carnegie Mellon University; BMath, Computer Science & Combinatorics, University of Waterloo Affiliations: Core member of UBC's Designing for People cluster Research interests span novel input modalities, mixed-reality systems, and security challenges. He actively competes in DEF CON CTF (multiple 1st places) and publishes in top venues like CHI, UIST, and ISMAR. Recent work explores VR decision-making, low-latency tracking, and collaborative AR/VR environments. Awards: SIGCHI Outstanding Dissertation Award, CHI Honorable Mention, DIS Honourable Mention Teaching includes courses on computer systems (CPSC 213), human-computer interaction (CPSC 554X), and cybersecurity (CPSC 436S). His lab develops tools like SurfShare (surface sharing) and VirtualNexus (collaborative AR).

Brandon Stewartمشاهده پروفایل

دانشیار

• Quantitative Methods
• Social Sciences
• Text Analysis
• +۶ مورد دیگر

Brandon Stewart is an Associate Professor in the Department of Sociology at Princeton University, affiliated with the Department of Politics, Office of Population Research, and multiple interdisciplinary institutes. He holds a PhD in Government from Harvard University (2015) and a Master's in Statistics (2014). His research focuses on developing quantitative methods for social science applications, including automated text analysis and causal inference. Recent projects analyze propaganda in China's media and apply text-based methods to education, human trafficking, and international relations. His work has been published in top journals like American Journal of Political Science and Political Analysis. Awards include the 2024 Leo Goodman Award and Gosnell Prize. He advises students like Ian Lundberg (UCLA) and Rebecca Johnson (Georgetown), and leads initiatives in computational social science through affiliations with institutes like Princeton Institute for Computational Science and Engineering. His labs and teams explore AI ethics, recommendation systems, and language models' societal impacts.

Alexander Budzierمشاهده پروفایل

پژوهشگر ارشد

• Project Management
• IT-enabled Change
• Risk Management
• +۵ مورد دیگر

Alexander Budzier is a Research Fellow in the Department of Technology and Operations Management at Saïd Business School, University of Oxford. He specializes in managing projects across IT, infrastructure, energy, and mega-events, with a focus on risk mitigation and systems thinking. His roles include teaching on the MSc for Major Programme Management, MBA, and the Major Project Leadership Academy. Education: PhD from Saïd Business School (2014). Prior experience includes roles at T-Mobile International and McKinsey's Business Technology Office in Düsseldorf and Chicago, advising on IT and operations strategy. Research interests center on IT-enabled change, project setups, and risk analysis. Notable contributions include work on cost overruns in IT projects, the uniqueness trap in project management, and sustainable development via mega-events like the Olympics. Publications span journals like Harvard Business Review , iScience , and Event Management , with a focus on megaprojects, risk, and digital transformation. He has advised governments and corporations on infrastructure investments and project governance, emphasizing evidence-based decision-making.

Nima Monshizadeh Nainiمشاهده پروفایل

استاد

• Cyber-Physical Human Systems (CPHS)
• Control Theory
• Optimization
• +۵ مورد دیگر

Nima Monshizadeh Naini is a Professor in the Faculty of Science and Engineering at the University of Groningen. He holds the position of Chair of the IEM Program Committee and serves on the boards of ENTEG and YSEN. His academic journey includes a PhD in Control Systems from the University of Groningen (2013, Cum Laude), followed by postdoctoral research at the University of Cambridge (2016-2017) and the University of Groningen (2014). He has been an Assistant Professor since 2018 and was awarded the NWO Open Competition Grant in 2021. His research focuses on Cyber-Physical Human Systems (CPHS) , addressing two core areas: (1) Coordination of self-interested users in power systems and traffic networks using dynamic information design and game-theoretic mechanisms; and (2) Privacy-aware control and optimization with tailored encryption methods for dynamic systems. Applications include energy markets, microgrids, and smart grids. He has published extensively in top venues like IEEE CDC and Automatica, with key topics including privacy-preserving algorithms, distributed control, and optimal intervention design. His work contributes to UN Sustainable Development Goals related to affordable energy and responsible consumption. Education: PhD in Control Systems, University of Groningen (2013) Research Associate, University of Cambridge (2016-2017) Postdoctoral Researcher, University of Groningen (2014) Awards: Cum Laude distinction for PhD thesis (2013) NWO Open Competition Grant (2021) Advising & Grants: Supervised 5 PhD students Editorial roles in IEEE journals and conference proceedings Labs/Teams: Leading the Cyber-physical systems group within the Smart Manufacturing Systems institute.

• Financial Economics
• High-Frequency Trading
• Blockchain Technology
• +۳ مورد دیگر

Konstantin Sokolov is a Professor at the University of Memphis, affiliated with the Fogelman College of Business and Economics. His research bridges finance, technology, and market design, focusing on liquidity dynamics, high-frequency trading, and blockchain systems. University of Memphis - Fogelman College of Business and Economics Collaborations with institutions across the U.S. and globally His work explores market microstructure , cryptocurrency , and cybersecurity , with recent studies on ransomware impacts, gamification in finance, and blockchain governance. Articles show a trend toward integrating machine learning and network theory into financial systems. Key themes include: Liquidity and volatility in algorithmic trading environments Blockchain congestion and cybersecurity externalities Regulatory implications of fast trading technologies Behavioral responses to gamified financial platforms