جست‌وجوی استاد و پژوهشگر

Dongsheng Luoمشاهده پروفایل

استادیار

• Data Mining
• Deep Learning
• Natural Language Processing
• +۵ مورد دیگر

Dr. Dongsheng Luo is an Assistant Professor at the Knight Foundation School of Computing and Information Sciences at Florida International University (FIU). He holds a Ph.D. in Information Science and Technology from Pennsylvania State University (2022) and a B.Eng. in Computer Science and Technology from Beihang University (2017). His research focuses on developing interpretable AI tools for complex data analysis, particularly in graph mining, deep learning, and natural language processing, with applications in neuroscience, healthcare, and environmental systems. Education: 2022: Ph.D., Penn State University 2017: B.Eng., Beihang University His research interests emphasize explainable AI, robust graph neural networks, and multimodal integration. Recent work includes frameworks for medical plan generation, causal discovery, and flood forecasting. He investigates methods to enhance model reliability and transparency, such as confidence-aware explanations and fidelity evaluation. Collaborations span biomedical informatics, climate science, and IoT systems. Publications highlight contributions to graph explainability, time series analysis, and molecular modeling. His work bridges theoretical advances with practical applications in healthcare, environmental monitoring, and communication systems.

Ross Buckمشاهده پروفایل

استاد

• Nonverbal Communication
• Emotional Expression
• Social-Ecological Systems
• +۴ مورد دیگر

Ross Buck is a Professor of Communication and Psychology at the University of Connecticut, affiliated with the College of Liberal Arts and Sciences and the Department of Communication. His research focuses on nonverbal communication, emotional expression, and their roles in human behavior, social structure, and adaptation. He has contributed extensively to understanding the evolution of emotional communication, cognitive-emotional interactions, and cross-cultural variations in emotional expression. Dr. Buck holds a Ph.D. from the University of Pittsburgh (1970). His work integrates biological, psychological, and social perspectives, exemplified in his books such as Human Motivation and Emotion and Emotion: A Biosocial Synthesis . He has been funded by prestigious agencies like the National Science Foundation and the National Institute of Mental Health. Research interests include empathy measurement, technology-mediated emotion, and the impact of spatial distance on emotional communication. He leads the UConn Communication Technology, Emotion, and Culture Lab and teaches courses like Motivation and Emotion, Nonverbal Communication, and graduate-level seminars. His recent projects explore brain mechanisms of empathy and cultural variations in primary social emotions. Notable grants include funding from the National Institute of Mental Health, Harry Frank Guggenheim Foundation, Russell Sage Foundation, and National Science Foundation. He blogs for Psychology Today and has been featured in ABC’s 20/20. His articles address topics like drone system trustworthiness, password manager adoption, and crisis communication in corporate reputations.

James Pomykalskiمشاهده پروفایل

دانشیار

• Information Systems
• Business Analytics
• Systems Analysis
• +۵ مورد دیگر

James Pomykalski is an Associate Professor of Finance and Analytics at the Sigmund Weis School of Business , Susquehanna University . He has been with the university since 2001, where he also served as Department Head and Director of the University Honors Program. His academic journey began with a BA in Mathematics from St. Norbert College, followed by an MS in Industrial Engineering/Operations Research from Purdue University, and a PhD in Systems Engineering from the University of Virginia. PhD, University of Virginia (1994) - Systems Engineering MS, Purdue University (1983) - Industrial Engineering/Operations Research BA, St. Norbert College (1981) - Mathematics Pomykalski's research focuses on integrating critical thinking , writing , and technology in business education. He has pioneered writing-intensive approaches in Information Systems (IS) courses to enhance analytical skills, developed case studies for Business Intelligence, and explored simulation models for decision support. His work bridges business analytics , systems analysis , and pedagogical innovation , emphasizing interdisciplinary learning and ethical considerations. His publications reveal a strong emphasis on curriculum development (e.g., IS 2002 model comparisons), business integration (using Enron as a case study), and systems analysis pedagogy . He has presented at prestigious conferences like ISECON and NABET, focusing on teaching methodologies and student engagement. Scientific Awards & Honors: Excellence in Teaching Award, National Society for Leadership and Service Honorary Member, Omicron Delta Kappa Honorary Member, Alpha Lambda Delta Meritorious Writing, Information Systems Educator Conference He has mentored students in projects spanning Business Intelligence , SQL Development , and Mobile-Aware Systems , while serving on numerous university and professional committees. His NASA-ASEE Summer Faculty Fellowships highlight his expertise in automation and advanced architectures .

Fatemeh Davoudiمشاهده پروفایل

استادیار

• Machine Learning
• Safety Analytics
• Predictive Modeling
• +۷ مورد دیگر

Fatemeh Davoudi is an Assistant Professor in the Department of Aviation and Technology at San José State University (SJSU), specializing in Manufacturing Systems. She directs the Machine Learning & Safety Analytics Lab and serves as the Graduate Advisor for the Master of Science in Engineering Technology (MSET) program. Her research focuses on applied machine learning in industrial systems, safety analytics, predictive modeling, quality management, and lean manufacturing. She holds a Ph.D. in Industrial Technology from Iowa State University with a minor in Statistics. Dr. Davoudi’s work includes projects funded by grants totaling over $500,000, such as Deep Learning for Process Monitoring in Semiconductor Manufacturing (Co-PI, $163,000) and Machine Learning in Autonomous Systems (Co-PI, $100,000). Her research spans safety analytics in occupational settings, geometric machine learning for reliability assessment, and theory-guided data science for industrial optimization. Education: Ph.D. Industrial Technology, Iowa State University (2018) Awards: AHFE 2020 Best Paper Award (Safety Management and Human Factors Track) Service: Guest Editor for International Journal of Environmental Research and Public Health , Board Member of ATMAE Her teaching includes courses on Six Sigma, Design of Experiments, and Lean Manufacturing. She advises students pursuing thesis and project work in machine learning applications for industrial systems optimization.

Arkady Shemyakinمشاهده پروفایل

استاد

• Bayesian Statistics
• Copula Analysis
• Non-Informative Priors
• +۳ مورد دیگر

Arkady Shemyakin is a Professor and Director of the Statistics Program at the University of St. Thomas, located in St. Paul, Minnesota. He holds a leadership role in the College of Arts and Sciences (CAS), focusing on Mathematics and Data Analytics. His academic career includes full-time teaching at Novosibirsk State University and visiting appointments at institutions like the University of Minnesota and Heriot-Watt University in Edinburgh, UK. Dr. Shemyakin's research centers on Bayesian Statistics, copula analysis, and non-informative priors, with applications to Insurance, Finance, and Public Health. He has contributed to methodologies for modeling dependencies in financial markets, risk assessment in insurance, and pandemic-related mortality forecasting. His work often bridges theoretical advancements with practical industry solutions. Shemyakin serves as President of the American Siberian Education Foundation and has previously led the Twin Cities chapter of the American Statistical Association. He actively contributes to academic publishing through editorial roles and peer review. Beyond academia, he enjoys chess, tennis, and skiing. Recent research trends include copula-based models for mortality analysis (e.g., pandemic mortality patterns), Hellinger distance applications in Bayesian priors, and economic capital frameworks for insurance companies. His interdisciplinary approach addresses both theoretical challenges and real-world applications in risk management and data-driven decision-making. No formal student advisement records are listed here. His professional service includes community-oriented educational projects and technology commercialization initiatives highlighted in his publications. He is affiliated with the Mathematics department at St. Thomas and collaborates with the Statistics Program's academic and outreach teams. His work often intersects with the university's focus on liberal arts integration and data-driven disciplines.

Jaho Seoمشاهده پروفایل

دانشیار

• Mechatronics
• Autonomous Mobile Machines
• Intelligent Construction Equipment
• +۵ مورد دیگر

Dr. Jaho Seo is an Associate Professor in the Department of Automotive and Mechatronics Engineering at Ontario Tech University, part of the Faculty of Engineering and Applied Science. He holds a PhD in Mechanical Engineering from the University of Waterloo and has extensive experience in academia and industry. His research focuses on mechatronics, autonomous systems, intelligent construction/agriculture machinery, and control systems. Education: PhD (Mechanical Engineering), University of Waterloo, 2011 M.Ing (MSc in Mechanical Engineering), École de Technologie Supérieure (Montreal), 2006 BSc (Agricultural Machinery & Process Engineering), Seoul National University, 1999 Research Interests: Dr. Seo specializes in mechatronics, autonomous mobile machines, and intelligent systems. His work emphasizes safety-control mechanisms, electro-hydraulic systems, and hardware-in-the-loop simulation. He has developed algorithms for autonomous excavation, vehicle dynamics, and sensor integration. Professional Activities: Board Member, IT Convergence Technology Division of the Korean Society of Mechanical Engineers (2016–2017) Local Arrangement Co-Chair, 30th Institute of Control, Robotics and Systems Annual Conference (2015) Government R&D evaluator for Korean ministries (2014–2017) Awards: Multiple Best Conference Paper Awards (2014–2016) KIMM Technical Support Award (2015) University of Waterloo Graduate Scholarship (2009–2011) Grants & Labs: He leads the AVeC Lab (Automated Vehicle and Construction Lab). His grants focus on autonomous systems, safety-control, and energy-efficient machinery. He has secured funding for projects related to excavator automation and agricultural machinery. Future Work: Dr. Seo is advancing autonomous construction equipment, real-time safety systems, and sustainable agricultural technologies. His lab collaborates with industry partners to commercialize innovations in electro-hydraulic systems and machine learning.

Volker Gassمشاهده پروفایل

استاد مدعو

• Space Systems
• Technology Innovation
• Space Policy

Volker Gass serves as Director of Strategic Initiatives at EPFL and Adjunct Professor across multiple departments including School of Engineering and College of Management of Technology. His academic background includes a PhD in Applied Micro-Systems Technologies from University of Neuchâtel and executive leadership training. Gass's research focuses on space technology innovation, including satellite systems, space materials, and educational applications of space science. His work bridges engineering development and space policy frameworks. Recent publications demonstrate three research priorities: (1) advanced space propulsion and thermal systems, (2) space qualification of terrestrial technologies, and (3) educational applications of space exploration concepts. These works balance technical innovation with practical implementation challenges. As former Director of the Swiss Space Center (Space Innovation), Gass led initiatives linking academic research with industry applications, including CubeSat development and space debris mitigation. He currently oversees strategic technology initiatives at EPFL while maintaining visiting professor status at MIT AeroAstro.

Han Yanمشاهده پروفایل

استادیار

• Banking
• Climate Finance
• Voluntary Disclosure

Han Yan is an Assistant Professor at UBC Sauder School of Business specializing in banking, climate finance, and corporate disclosure practices. He holds a PhD from NYU Stern and teaches managerial accounting courses. His research bridges finance and environmental economics, with recent focus on climate risk integration in financial systems. Prior to his finance career, he conducted significant research in materials science and nuclear engineering, publishing on cyclotron target systems and cellulose-based materials. This interdisciplinary background informs his current work on sustainable finance and environmental disclosure frameworks.

Mircea Dan Grigoriuمشاهده پروفایل

استاد

• Random Vibration
• Stochastic Calculus
• Structural Engineering
• +۵ مورد دیگر

Mircea Dan Grigoriu is a Professor and Interim Director of Graduate Studies at Cornell University's School of Civil and Environmental Engineering. He holds degrees from MIT (Ph.D., 1976), the University of Bucharest (M.S., 1972), and the Bucharest Institute of Civil Engineering (B.S., 1967). Education: B.S. Civil Engineering (1967), M.S. Mathematics (1972), Ph.D. Civil Engineering (1976). His research focuses on stochastic calculus, random vibration, numerical methods for stochastic problems, and earthquake engineering. He has authored over 200 journal papers and three books, including works on non-Gaussian processes and stochastic systems. Awards: 2016 Nathan M. Newmark Medal, 2005 Norman Medal, Alfred M. Freudenthal Medal (2002), and Doctor Honoris Causa (2004). He serves on editorial boards for journals like Probabilistic Engineering Mechanics and Structural Safety . Teaching emphasizes foundational concepts in mechanics and probability. Service includes roles in faculty reappointment and graduate program committees.

Christian Genestمشاهده پروفایل

استاد

• Statistics
• Dependence modeling
• Extreme-value theory
• +۶ مورد دیگر

Christian Genest is a Distinguished James McGill Professor in the Department of Mathematics and Statistics at McGill University. He holds a PhD from the University of British Columbia and has been a leading figure in statistics and probability for decades. His research focuses on dependence modeling, extreme-value theory, multivariate analysis, and their applications in environmental science, hydrology, insurance, and risk management. Education: BSc (1977) Université du Québec à Chicoutimi, MSc (1978) Université de Montréal, PhD (1983) University of British Columbia. Genest has received numerous accolades, including Fellowships from the Royal Society of Canada, American Statistical Association, Institute of Mathematical Statistics, and Fields Institute. He served as SSC President (2007-2008), Director of the Institut des Sciences Mathématiques (2012-2015), and held the Canada Research Chair in Stochastic Dependence Modeling (2011-2025). He has supervised 59 MSc, 9 PhD students, and 15 postdocs, with ongoing mentorship of 2 MSc, 3 PhD candidates, and 2 postdocs. Genest is a prolific speaker, having delivered over 364 talks globally, including plenaries at major conferences like the Statistical Society of Canada and the Fields Institute. His work bridges theoretical advancements and practical applications, with contributions to copula theory, extreme-value analysis, and statistical methodology. He advocates for public engagement, delivering outreach lectures at schools and colleges across Quebec. Award Highlights: 2011 SSC Gold Medalist, 2015 Royal Society of Canada Fellow, 2023 CRM-Fields-PIMS Prize, and 2024 Emanuel and Carol Parzen Prize for Statistical Innovation. Grants and Leadership: Coordinated the CRM Risk in Complex Systems thematic program (2017), edited major statistical journals, and chaired departmental interim leadership (2022-2023).

Tracy Beckerمشاهده پروفایل

دانشیار

• Structural dynamics and design
• Earthquake engineering
• Isolation & high-performance systems
• +۴ مورد دیگر

Tracy Becker is an Associate Professor in the Department of Civil and Environmental Engineering at the University of California, Berkeley, holding the Ed & Diane Wilson Presidential Chair in Structural Engineering. She serves as Vice Chair for Research & Technical Support and leads projects in structural dynamics, earthquake engineering, and novel material applications. Education: B.S. in Structural Engineering, University of California, San Diego (2006) M.S. in Civil and Environmental Engineering (SEMM), University of California, Berkeley (2007) Ph.D. in Civil and Environmental Engineering (SEMM), University of California, Berkeley (2011) Becker's research focuses on enhancing structural resilience through advanced isolation systems, hybrid simulation methodologies, and machine learning-driven design optimization. Her work addresses collapse behavior under extreme seismic loads, model updating techniques, and innovative steel component design to improve rotational capacity while minimizing damage. Recent publications highlight trends in base isolation performance evaluation, hybrid simulation advancements, and uncertainty modeling for infrastructure management. Key topics include friction pendulum systems, Gaussian process surrogate modeling for collapse prediction, and life-cycle analysis of bridge bearings. Scientific Awards: Best Paper Award at ICOSSAR International Conference Becker's contributions include experimental validation of isolation systems, development of data assimilation frameworks for structural models, and educational initiatives within the Structural Engineering, Mechanics and Materials (SEMM) program. She actively collaborates on full-scale testing and computational modeling projects.

• Structural Engineering
• Structural Reliability
• Earthquake Engineering
• +۲ مورد دیگر

Ziqi Wang is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of California, Berkeley, specializing in structural reliability, earthquake engineering, and uncertainty quantification. His research develops computationally efficient methods that integrate domain-specific knowledge for analyzing infrastructure resilience under natural hazards. Education: Ph.D. in Civil Engineering, Southwest Jiaotong University, China (2015) B.S. in Civil Engineering, Southwest Jiaotong University, China (2010) Research Interests: Professor Wang's work centers on interpretable probabilistic analysis for structural reliability, emphasizing methods that leverage civil engineering domain knowledge. Key focus areas include computational reliability techniques for high-dimensional problems, statistical physics applications for regional-scale hazard impact analysis, and physics-informed machine learning for seismic response prediction. His research bridges civil engineering with computational science to address challenges in infrastructure resilience. Publication Trends: Recent publications (2024-2025) demonstrate a strong shift toward hybrid modeling approaches combining physics-based principles with data-driven techniques. A recurring theme is the development of interpretable surrogate models for high-dimensional reliability analysis, particularly for lifeline networks and structural systems under seismic events. His work increasingly integrates statistical physics concepts to model systemic infrastructure behavior during disasters. Scientific Awards: Society of Hellman Fellows Fund Award (2024) Advising and Teaching: Professor Wang mentors graduate students through Individual Research (CIVENG 299) and teaches specialized courses including Uncertainty Quantification for Engineering (CIVENG 293), Engineering Risk Analysis (CIVENG 193), and Structural System Reliability (CIVENG 229). His teaching emphasizes practical computational methods for real-world engineering challenges. Laboratories and Research Groups: While specific lab names aren't detailed in source materials, his research aligns with Berkeley's Pacific Earthquake Engineering Research Center (PEER) initiatives, focusing on collaborative infrastructure resilience projects involving structural dynamics and regional risk modeling.

Sankaran Mahadevanمشاهده پروفایل

استاد

• Uncertainty Quantification
• Risk and Reliability Analysis
• Machine Learning
• +۷ مورد دیگر

Dr. Sankaran Mahadevan is the John R. Murray Sr. Professor of Engineering at Vanderbilt University's School of Engineering, with dual appointments in Civil and Environmental Engineering and Mechanical Engineering. He directs the Master's program in Risk, Reliability, and Resilience Engineering and co-directs the Laboratory for Systems Integrity and Reliability (LASIR). His research focuses on uncertainty quantification, risk analysis, machine learning, and decision-making under uncertainty, with applications to aerospace, civil, and mechanical systems. He leads NSF, NASA, DOE, and industry-funded projects on digital twin methodologies for aircraft, ship structures, and additive manufacturing. Education: PhD from Georgia Tech, MS from Rensselaer, BS from IIT Madras Professional Roles: Managing Editor of ASCE-ASME Journal of Risk and Uncertainty, Vice-President of ASCE Engineering Mechanics Institute Research interests include probabilistic modeling for infrastructure resilience, AI-driven prognosis, and safety-critical systems. He has authored 600+ publications, including two textbooks, and advised 70+ graduate students. Awards include AIAA, ASCE, and PHM Society Fellowships, and the SEC Faculty Achievement Award. Current projects include NASA-funded air traffic safety modeling and DOE-supported power grid reliability studies. His work bridges computational methods with real-world engineering challenges, emphasizing interdisciplinary collaboration across academia and industry.

Ghina Absiمشاهده پروفایل

استادیار

• Risk and Reliability
• Structural Engineering
• Hypersonic Structures
• +۳ مورد دیگر

Ghina Absi is an Assistant Professor of the Practice of Civil and Environmental Engineering at Vanderbilt University's School of Engineering. Her teaching focuses on structural engineering, blending academic rigor with industry-relevant practices. Education Ph.D., Civil and Environmental Engineering, Vanderbilt University M.S., St. Joseph University B.S., St. Joseph University Research & Professional Background Dr. Absi's research centers on risk and reliability in hypersonic structures, with a novel method for fusing multi-fidelity models in parameter estimation. Before academia, she worked as a structural engineer designing high-rise and complex steel structures in seismic and corrosive environments. She actively promotes project-based learning in engineering education, emphasizing hands-on experience. Affiliations & Links For further details, visit her LinkedIn profile: LinkedIn .

• Algebraic statistics
• Experimental design
• Industrial statistics
• +۳ مورد دیگر

Roberto Fontana is a Full Professor at the Department of Mathematical Sciences (DISMA) of the Polytechnic University of Turin. He is a member of the Interdepartmental Centre R3C (Responsible Risk Resilience Centre) and actively involved in the College of Management and Production Engineering and the Planning and Design Board. His research focuses on algebraic statistics, experimental design, industrial statistics, and multivariate statistics, with an emphasis on statistical analysis of physical and computer experiments. Fontana holds leadership roles in academic societies, including being an Effective Member of ERCIM (European Research Consortium for Informatics and Mathematics), ENBIS (European Network for Business and Industrial Statistics), and SIS (Italian Statistical Society). He serves as an Associate Editor for the Journal of Applied Statistics since 2017. His teaching spans multiple levels, including PhD courses on statistical modeling and machine learning, as well as undergraduate and graduate courses in statistics across disciplines like Management Engineering and Territorial Planning. He leads the ELBA project (2019–2022), establishing training centers for Intelligent Big Data analysis. Fontana’s recent publications emphasize advancements in contingency tables, Bernoulli distributions, and the integration of design of experiments with machine learning. He currently supervises PhD student Davide Ronco in the Mathematical Sciences program. His work bridges theoretical statistics with industrial applications, emphasizing robust experimental design and computational methods. Fontana actively collaborates on interdisciplinary projects, including environmental and material science applications.