جست‌وجوی استاد و پژوهشگر

Wan Shouمشاهده پروفایل

استادیار

• Multiscale manufacturing
• Laser-based manufacturing and materials processing
• Novel manufacturing processes
• +۱۲ مورد دیگر

Wan Shou is an Assistant Professor in the Department of Mechanical Engineering at the University of Arkansas. His research focuses on multiscale manufacturing, advanced materials, and functional devices, with applications in wearables, robotics, and sustainable technologies. Ph.D., Mechanical Engineering, Missouri University of Science and Technology M.S., Mechanical Engineering, University of Louisiana at Lafayette B.E., Textile Engineering, Tianjin Polytechnic University, China Dr. Shou’s research spans laser-based manufacturing , nanomanufacturing , machine learning-assisted processes , and bioresorbable electronics . He explores 3D printing of polymer and metal composites, energy materials , and functional textiles for wearable sensors and environmental applications. Recent publications highlight his work in additive manufacturing , computational design of composites, and self-powered sensing systems . His team integrates machine learning with materials discovery to optimize performance. Editor’s pick of Science Magazine US Patent 11,752,700: Data-driven material formulation US Patent 11,993,850: Laser-assisted nanoparticle printing Dr. Shou’s patents and publications reflect a commitment to innovative manufacturing and environmentally conscious design . His work bridges materials science , robotics , and smart systems , advancing energy and water technologies.

Ahmad Al-Dabbaghمشاهده پروفایل

استادیار

• Control Systems
• Automation Systems
• Fault Diagnosis
• +۳ مورد دیگر

Ahmad Al-Dabbagh is an Assistant Professor in Manufacturing Engineering and holds a Principal's Research Chair in Control Systems (Tier 2) with the School of Engineering at The University of British Columbia. As a Senior Member of IEEE and ISA, he contributes significantly to the field of resilient automation and control systems through research, teaching, and professional service. His academic journey includes postdoctoral fellowships at Imperial College London, the University of Toronto, and the University of Alberta, where he also earned his PhD in Electrical and Computer Engineering. Dr. Al-Dabbagh's research focuses on designing resilient automation and control systems by addressing critical challenges in fault diagnosis, cyber security, and alarm management. His work spans theoretical foundations and practical applications in industrial control systems, with particular emphasis on detection and isolation of faults and cyber attacks, control reconfiguration, event-triggered control, remote state estimation, and alarm systems design. His research interests also extend to causality analysis, prediction methods, and root cause analysis for industrial processes. His extensive publication record demonstrates consistent contributions to control systems security and reliability, with recent work focusing on sophisticated methods for detecting false data injection attacks, analyzing alarm correlations using advanced machine learning techniques, and developing recommender systems for human operators in industrial environments. The trajectory of his research shows an evolution from foundational control theory toward increasingly complex applications in cyber-physical security and human-system interaction in industrial settings. NSERC Postdoctoral Fellowship NSERC Alexander Graham Bell Canada Graduate Scholarship (CGS – D3) Queen Elizabeth II Graduate Scholarship Governor General's Academic Medal (Gold) As a graduate student supervisor, Dr. Al-Dabbagh mentors the next generation of control systems engineers while maintaining an active research program. He serves as an Associate Editor on the IEEE Control Systems Society Conference Editorial Board and is a licensed Professional Engineer in British Columbia and Ontario. His teaching portfolio includes courses such as System Identification, Digital Enterprise, Systems and Control, and Internet of Things, reflecting the breadth of his expertise. Dr. Al-Dabbagh leads the Okanagan Laboratory for Control Systems Research, where his team develops innovative approaches to enhance the security and reliability of industrial automation systems. The laboratory serves as a hub for interdisciplinary research that bridges theoretical control engineering with practical industrial applications, particularly in the energy, manufacturing, and process industries.

Rohit Kannanمشاهده پروفایل

استادیار

• Learning + Optimization
• Optimization Under Uncertainty
• Global Optimization
• +۲ مورد دیگر

Rohit Kannan is an Assistant Professor in the Grado Department of Industrial and Systems Engineering at Virginia Tech. He holds a Ph.D. and M.S. in Chemical Engineering from MIT and a B.Tech. from IIT Madras. His research focuses on integrating machine learning with global optimization and optimization under uncertainty, emphasizing energy systems applications. Previous roles include postdoc positions at Los Alamos National Laboratory and the Wisconsin Institute for Discovery. Education: Ph.D., Chemical Engineering, Massachusetts Institute of Technology, 2018 M.S., Chemical Engineering Practice, MIT, 2014 B.Tech., Chemical Engineering, IIT Madras, 2012 Research Interests: Global optimization, optimization under uncertainty, computational optimization, energy systems, and machine learning integration. Recent Highlights: Recipient of the Excellence in Teaching Spotlight Award (2024) Lead researcher in stochastic optimization and energy systems (e.g., hybrid polygeneration systems) Developed algorithms for chance-constrained nonlinear programs and distributionally robust optimization Service & Leadership: Elected Vice-Chair of Global Optimization, INFORMS Optimization Society (2025–2026) Reviewer for top journals like Operations Research and Mathematical Programming Advisor to ISE InclusiveVT and Graduate Admissions Committee Labs & Collaborations: Directs a research group advancing optimization and machine learning for energy and engineering systems. Active in interdisciplinary projects with LANL and UW-Madison.

Hyosang Leeمشاهده پروفایل

استادیار

• Tactile Sensing
• Robotics
• Soft Robotics
• +۴ مورد دیگر

Hyosang Lee is an Assistant Professor in the Robotics Section of the Mechanical Engineering Department at Eindhoven University of Technology (TU/e). He holds a PhD from KAIST and has held research positions at the Max Planck Institute and University of Stuttgart. His work focuses on tactile sensing technologies, including artificial skin development, soft robotics, and integration of sensory systems with AI. Bachelor's: Mechanical Engineering, Korea University Master's: Robotics and Mechanical Engineering (double major) PhD: Mechanical Engineering, KAIST (2017) Research interests span tactile sensor design, electrical impedance tomography (EIT), and human-robot interaction. His group emphasizes creating scalable, flexible tactile systems for robots. Recent work includes air pressure sensing for force estimation and biomimetic skin materials. Publications highlight innovations in multi-directional force sensing, soft component technologies, and haptic interfaces for autism therapy. He teaches 'Dynamics and Control of Robotic Systems' and serves on the editorial board of npj Robotics . No formal student advisees are listed, though his lab, the Tactile Sensing and Robotic Skin Group , likely involves graduate researchers. His research contributes to UN Sustainable Development Goals related to health and technology.

James Andersonمشاهده پروفایل

استادیار

• Optimal Control Theory
• Robust Control
• Mathematical Programming
• +۴ مورد دیگر

James Anderson is an Assistant Professor in the Department of Electrical Engineering at Columbia University, with affiliations to the Data Science Institute (DSI) and multiple research centers including the Computing Systems for Data-Driven Science and Foundations of Data Science. Prior to Columbia, he was a Senior Research Scientist at Caltech’s Computing + Mathematical Sciences division (2016–2019) and held a Junior Research Fellowship at the University of Oxford’s Department of Engineering Science (pre-2012). He earned his DPhil (PhD) in Engineering Science from Oxford in 2012. His research focuses on optimal/robust control theory, mathematical programming, data privacy, and cyber-physical systems, with applications in smart grids, systems biology, and power systems. Recent work emphasizes energy storage strategies, distributed control algorithms, and cybersecurity in critical infrastructure. His publications span advanced control methodologies (e.g., reinforcement learning for LQR problems), energy market dynamics, and resilient system designs. Notable contributions include frameworks for decision-focused energy storage arbitrage and defenses against false data attacks in power grids. He actively collaborates on federated learning approaches for distributed systems and has pioneered techniques for system-level synthesis in cyber-physical architectures. Anderson’s affiliations include the Data Science Institute (DSI) and specialized centers focused on data-driven science and energy systems. His work bridges theoretical control advancements with real-world applications in energy and healthcare.

Dominika Ignasiakمشاهده پروفایل

پژوهشگر

• Biomechanics
• Musculoskeletal Modeling
• Spinal Surgery
• +۳ مورد دیگر

Dr. Dominika Ignasiak is a Researcher affiliated with the Institute of Biomechanics at ETH Zürich. Her work focuses on spinal biomechanics, musculoskeletal modeling, and computational analysis of spinal pathologies. She contributes to understanding the biomechanical implications of surgical interventions, spinal deformities, and age-related changes in spinal alignment and loading. Her research integrates clinical data with advanced musculoskeletal modeling techniques, particularly in predicting postoperative outcomes and assessing spinal load distributions under dynamic conditions. Key areas include spinal stenosis, idiopathic scoliosis, and the biomechanics of spinal fusion surgery. Dr. Ignasiak collaborates on translational studies bridging computational simulations with clinical applications. Her publications emphasize the role of personalized models in optimizing surgical strategies and understanding degenerative spinal conditions. While no formal awards are listed, her contributions to spinal biomechanics research are evident through her active publication record in high-impact journals. Dr. Ignasiak is based at ETH Zürich’s Institute of Biomechanics, where she engages in cutting-edge research and contributes to both academic and clinical advancements in orthopedic biomechanics.

Ye Zhishengمشاهده پروفایل

دانشیار

• Inventory Control
• Reliability Engineering
• Emergency Response Systems
• +۴ مورد دیگر

Ye Zhisheng is the Dean’s Chair and Associate Professor in the Department of Industrial Systems Engineering & Management at the National University of Singapore (NUS). His research focuses on reliability engineering, inventory control, emergency response systems, and statistical modeling. He holds a PhD in Industrial and Systems Engineering from NUS, along with a BEng in Material Science and Engineering and a BEco in Economics from Tsinghua University. His work emphasizes practical applications in mission-critical systems, predictive maintenance, and data-driven decision-making. Current research initiatives include optimal maintenance policies for manufacturing systems, degradation analysis of bearings, and federated learning approaches for battery lifecycle prediction. He has pioneered methods for integrating physics-informed neural networks into prognostics and health management (PHM) systems. Key technical contributions span advanced statistical methodologies like sieve estimation for survival data, phase-type distributions modeling, and condition-based maintenance optimization. His interdisciplinary approach bridges operations research, mechanical engineering, and computer science to address complex reliability challenges. Recent projects include resilient consensus-based power grid management and contamination source identification frameworks. Notable collaborations involve developing intelligent cross-domain fault diagnosis systems using transformer networks and advancing the Internet of Federated Things (IoFT) for distributed data analytics. His work has been applied in aerospace, telecommunication infrastructure, and medical emergency response systems.

Andrew Gersickمشاهده پروفایل

مدرس

• Animal Behavior
• Collective Behavior
• Social Dynamics
• +۳ مورد دیگر

Andrew Gersick is a Lecturer in the Department of Ecology and Evolutionary Biology at Princeton University. His research focuses on animal behavior, particularly in large social species such as spotted hyenas, zebras, and cowbirds. He explores topics including collective behavior, social dynamics, communication systems, and ecological adaptations. His work integrates field studies with technological tools like accelerometers to analyze activity patterns and signaling mechanisms. Notably, he investigates how zebra stripes repel biting flies and how hyenas use vocalizations for individual recognition. Gersick also contributes to conservation efforts, such as the Great Grevy’s Rally in Kenya, and studies social learning in avian species like cowbirds. His recent articles highlight interdisciplinary approaches, combining ecology, physiology, and technology to understand animal behavior in natural and social contexts. While no awards are explicitly listed, his contributions to understanding collective behavior and conservation biology are significant. Advising and grants: No formal advisees or grant details are provided in the text. His work appears to focus on collaborative research and field-based methodologies. Labs/Teams: No specific laboratory or team affiliations are mentioned beyond his departmental role at Princeton.

Zackary Johnsonمشاهده پروفایل

دانشیار

• Marine Microbial Ecology
• Biological Oceanography
• Algal Biotechnology
• +۴ مورد دیگر

Zackary Johnson , the Juli Plant Grainger Associate Professor of Biological Oceanography and Marine Biotechnology at Duke University, leads interdisciplinary research at the intersection of marine microbiology and biogeochemical innovation. Affiliated with the Nicholas School of the Environment and based at the Duke Marine Laboratory , his work spans microbial ecology, algal biotechnology, and climate mitigation strategies. Education: Ph.D. in Marine Science (Duke University, 2004), B.S. in Biology (MIT, 1994) Research Interests focus on marine microbial communities, particularly the model phytoplankton Prochlorococcus , algal cultivation for sustainable bioproducts, and the ecological impacts of ocean acidification. His lab investigates microbial interactions across diverse environments—from coastal estuaries to open-ocean gyres—and develops technologies for carbon-negative aquaculture systems. Publications highlight expertise in microbial biogeography, algal biofuels, and climate-resilient marine food webs. Recent work explores drone-based ocean color sensing, Gulf Stream eddy microbiomes, and the role of Labyrinthulomycetes protists in carbon export. Scientific Awards: Juli Plant Grainger Associate Professorship DOE and NSF-funded projects Grants include high-profile initiatives like the Marine Algae Industrialization Consortium (MAGIC) and REU Site program for coastal research training. His lab maintains a dedicated research site for studying microbial dynamics and sustainable algal cultivation.

August Evrardمشاهده پروفایل

استاد

• Cosmology
• Astrophysics
• Galaxy Clusters
• +۲ مورد دیگر

Professor August Evrard is a distinguished academic at the University of Michigan, holding the Arthur F. Thurnau Professorship in Physics and Astronomy. He is affiliated with the Department of Physics within the College of Literature, Science, and the Arts. Known for his contributions to cosmology and astrophysics, he pioneered the Problem Roulette tool, recognized with the Provost's Teaching Innovation Prize. His research focuses on galaxy clusters, dark matter, and cosmological surveys like the Dark Energy Survey (DES) and XXL Survey. He has been honored as an AAS Fellow (2025) and has contributed to advancements in physics education through innovative teaching methods and technologies. In research, Prof. Evrard explores topics such as dark matter halo dynamics, galaxy cluster properties, and weak lensing analyses. His work spans observational cosmology, computational modeling, and multi-wavelength astronomy. Notable projects include studies on galaxy cluster mass distributions, the relationship between X-ray emissions and velocity dispersions, and the application of machine learning to astrophysical data analysis. His contributions to education highlight the integration of AI-driven tools to enhance learning, as seen in initiatives like the Problem Roulette and course recommendation systems. Prof. Evrard's awards include the Provost's Teaching Innovation Prize for Problem Roulette and his AAS Fellowship. His academic leadership and innovative approaches to both research and education solidify his role as a pivotal figure in astrophysics and STEM pedagogy.

• Machine Learning
• Spatial Statistics
• Financial Econometrics
• +۳ مورد دیگر

Fabio Sigrist is a Professor of Applied Statistics and Data Science at the Institute of Financial Services Zug (IFZ) , part of the Lucerne University of Applied Sciences and Arts . He also holds a Senior Scientist and Lecturer position at the Seminar for Statistics, ETH Zurich . His career spans academic research, industry consulting, and project leadership in finance and data science. PhD in Statistics (2013), ETH Zurich MSc in Mathematics with distinction (2008), ETH Zurich MEd in Mathematics Education (2008), ETH Zurich Sigrist’s research focuses on integrating Machine Learning with Spatial Statistics for applications in Financial Econometrics and Credit Risk . His work includes developing novel algorithms like GPBoost and KTBoost , advancing spatio-temporal modeling , and applying tree-based boosting to financial problems. Projects such as CreHos (credit risk in hospitality) and NISMO (interpretable real estate modeling) highlight his interdisciplinary approach. His publications address challenges in large-scale spatial data , loss given default modeling , and stock volatility prediction . He contributes to software development with tools like spate (R package) and varycoef (spatially varying coefficients).

Petteri Nurmiمشاهده پروفایل

استاد

• Environmental Monitoring
• Internet of Things (IoT)
• Artificial Intelligence (AI)
• +۷ مورد دیگر

Petteri Nurmi is a Professor of Computer Science at the University of Helsinki, affiliated with the Department of Computer Science and the Helsinki Institute of Sustainability Science (HELSUS). His research focuses on IoT systems, environmental monitoring, AI-driven solutions, and sustainable computing. He leads projects such as the NordForsk-funded initiative (2024-2028) and the Team Finland Knowledge programme (2024-2026), emphasizing large-scale IoT deployments and quantum computing integration. Key research interests include drone-based air quality monitoring, low-cost sensor networks, and AI applications in environmental science. Nurmi has published extensively in top venues like IEEE IoT Journal and ACM workshops. His work bridges technical innovation with societal challenges, such as urban pollution reduction and sustainable resource management. He supervises doctoral students in the Computer Science program and collaborates internationally on projects like underwater plastic detection (SEAGULL) and smart city infrastructure. Nurmi’s contributions to edge computing and pervasive sensing have been recognized through grants totaling over €2M. His lab develops tools for data-intensive systems, including thermal imaging for energy efficiency analysis and AI-driven sensor fusion frameworks.

• Entrepreneurship
• Tourism Management
• Sustainable Business Models
• +۲ مورد دیگر

Dr. Silvia Baiocco serves as Assistant Professor at University of Rome Tor Vergata, teaching entrepreneurship, tourism management, and marketing courses across Bachelor and Master programs including 'Creation of Enterprises and Entrepreneurship' (Master), 'Fundamentals of Service Management' (Bachelor), and 'Tourism and Cultural Management for Sustainability' (Bachelor). Her institutional affiliation centers on Business Economics (sector ECON-07/A) with research rooted in co-evolutionary theory. Her research critically examines sustainable business model innovation through three interconnected lenses: (1) tourism-destination co-evolution in historic villages and Alberghi Diffusi, (2) university-industry knowledge exchange for sustainable spin-offs via PNICube Observatory frameworks, and (3) technology integration in smart tourism through AI-driven destination management. She emphasizes context-specific adaptation in both high-income (Italy) and low/middle-income settings (Ghana), with strong focus on social impact and heritage preservation. Analysis of her 2023-2025 publications reveals accelerating focus on digital tourism transformation (AI applications, smart city integration) and resilience-building in accommodation firms. Her work consistently applies co-evolutionary frameworks to decode organizational adaptation, particularly in sustainable entrepreneurship contexts. The PNICube Observatory reports highlight her policy-relevant contributions to university research valorization. As educator, Dr. Baiocco actively shapes future business leaders through courses spanning startup creation to sustainable destination management. Her research trajectory indicates deepening engagement with technology-mediated sustainability solutions and cross-sectoral innovation ecosystems, particularly through ongoing PNICube Observatory initiatives.

Kiran Pedadaمشاهده پروفایل

دانشیار

• Marketing Strategy
• Digital Marketing
• Emerging Markets
• +۳ مورد دیگر

Kiran Pedada is an Associate Professor of Marketing at the Asper School of Business, University of Manitoba, and holds the F. Ross Johnson Fellow and The Associates Fellow in Marketing and Inclusive Business. Previously, he was an Assistant Professor at the Indian School of Business (ISB) and a Visiting Scholar at the University of North Carolina. He has been recognized as ISB’s Teacher of the Year (2020 and 2021) and named a top MBA professor by BusinessBecause. His research focuses on marketing strategy, digital transformation, emerging markets, and inclusive business practices. Dr. Pedada earned his Ph.D. in Marketing from Texas Tech University, where he won the Helen Devitt Jones Excellence in Graduate Teaching Award. His doctoral work on international marketing alliances in emerging markets won the prestigious AMS Mary Kay Inc. Doctoral Dissertation Award. Before academia, he worked in management consulting and corporate strategy. Research Interests : Marketing strategy in digital environments Social and financial impact of marketing Global marketing expansion via digital ecosystems Emerging markets dynamics Brand competitiveness through digital orientation Key Contributions : His research has been published in top journals like Journal of Marketing Research and Journal of the Academy of Marketing Science. He co-authored cases on digital transformation for Harvard Business Publishing and serves on editorial boards of key marketing journals. His work has been featured in Forbes, Fortune, and CNN. Awards : AMS Mary Kay Inc. Doctoral Dissertation Award (2019) F. Ross Johnson Fellowship Teacher of the Year (ISB, 2020 & 2021) He actively advises on digital readiness of SMEs and ESG integration in alliances. His current projects explore metaverse applications and rural microentrepreneurship in India.

Beata Csathoمشاهده پروفایل

استاد

• Remote Sensing
• Glaciology
• Climate Change
• +۳ مورد دیگر

Beata Csatho PhD is a Professor in the Department of Earth Sciences at the University at Buffalo, affiliated with the College of Arts and Sciences. Her research focuses on remote sensing, glaciology, climate change, and geophysics. She holds a PhD in Geophysics from the University of Miskolc, Hungary (1993). Her work integrates geophysical, remote sensing, and climatic data to study ice sheet dynamics and cryospheric changes. She leads the Remote Sensing lab and teaches courses like GLY 465/565 (Environmental Remote Sensing) and GLY 325 (Geophysics). Recent research emphasizes Greenland and Antarctic ice dynamics, ICESat-2 validation, and developing tools like Ghub for collaborative glaciology. She advises PhD and Master's students and collaborates on major projects like ISMIP7 and IceBridge. Her lab focuses on advancing laser altimetry, DEM correction, and cryosphere observation techniques.