جست‌وجوی استاد و پژوهشگر

Dan M. Frangopolمشاهده پروفایل

استاد

• Life-cycle civil engineering
• Structural reliability
• Infrastructure sustainability
• +۵ مورد دیگر

Prof. Dan M. Frangopol is the Fazlur R. Khan Endowed Chair of Structural Engineering and Architecture at Lehigh University's P.C. Rossin College of Engineering and Applied Science. He is a global leader in life-cycle civil engineering, focusing on probabilistic methods, infrastructure resilience, and sustainability. His research spans structural reliability, risk-based decision-making, and multi-hazard mitigation under climate change. Affiliations: Lehigh University (current), University of Colorado Boulder (23 years), and institutions in Romania and Belgium. Education: Dipl.-Ing. from Bucharest (1969), Doctor of Applied Sciences (summa cum laude) from University of Liège (1976), and multiple honorary doctorates. His research interests include life-cycle cost optimization, probabilistic mechanics, and infrastructure systems management. He pioneered the International Association for Bridge Maintenance and Safety (IABMAS) and the International Association for Life Cycle Civil Engineering (IALCCE). Key contributions include frameworks for resilient infrastructure under climate change and extreme events. Frangopol has authored/co-authored over 500 journal articles, 5 books, and 70 book chapters. He has supervised 50 PhD and 56 M.Sc. students, many of whom are now leading academics and practitioners. His awards include the inaugural Dan M. Frangopol Medal (2023), ASCE Noble Prize (2015, 2024), and multiple honorary memberships in national and international academies. He has advised numerous high-profile projects funded by NSF, FHWA, NASA, and others. His labs and initiatives include the Fazlur R. Khan Distinguished Lecture Series and the journal Structure and Infrastructure Engineering .

• Software Engineering
• Cybersecurity
• Data Science
• +۳ مورد دیگر

David Lo is an OUB Chair Professor and Director at the Information Systems and Technology Cluster , School of Computing and Information Systems , Singapore Management University . His research spans the intersection of Software Engineering , Cybersecurity , and Data Science , focusing on improving software quality, security, and developer productivity through socio-technical analysis and artifact evaluation. He has over 15 international Scientific Awards , including ACM Fellow (2023), IEEE Fellow (2022), and ASE Fellow (2021). His work has been funded by NRF , MOE , NCR , and AI Singapore . David leads the Software Analytics Research (SOAR) group and has mentored numerous PhD students , many of whom hold faculty positions or work in tech giants like Microsoft. He actively engages in service , chairing conferences like ICSE 2025 and ESEC/FSE 2024 , and serves on editorial boards of journals such as IEEE Transactions on Software Engineering . His recent keynotes address critical topics like AI for safer systems and LLM applications in software architecture , reflecting his vision for integrating AI into software engineering practices.

Razvan Bunescuمشاهده پروفایل

دانشیار

• Machine Learning
• Natural Language Processing
• Music Information Retrieval
• +۳ مورد دیگر

Razvan Bunescu is an Associate Professor in the Department of Computer Science at the University of North Carolina at Charlotte (UNCC), affiliated with the College of Computing and Informatics. His research focuses on machine learning, natural language processing, music information retrieval, and computational creativity. He holds a Ph.D. from the University of Texas at Austin and M.S./B.S. degrees from the University Politehnica of Bucharest. His work is funded by NIH (1R21EB022356) and NSF (1117489) grants, emphasizing diabetes management through wearable sensor data and blood glucose prediction models. Key research initiatives include the SmartHealth Lab , developing machine learning tools for healthcare, such as the OhioT1DM dataset for blood glucose prediction. He has co-chaired conferences like the Blood Glucose Level Prediction Challenge (BGLP) and served as an associate editor for IEEE Transactions on Computers . Notable awards include a Best Paper Award at the 2024 Figurative Language Processing Workshop. Education: Ph.D. Computer Science, University of Texas at Austin (2007) M.S. Computer Science, University Politehnica of Bucharest (1999) B.S. Computer Science, University Politehnica of Bucharest (1998) Professional Activities: Associate Editor, IEEE Transactions on Computers (2024–25) Program Co-Chair, International Summer School on Data Science (2018–24) Area Chair, ACL 2020 NLP Applications Track Awards: Best Paper Award at FigLang 2024. Grants: NIH R21EB022356: Adaptive Prediction of Blood Glucose Levels (2016–2020) NSF 1117489: Machine Learning for Blood Glucose Prediction (2011–2016) Advising: Supervised 20+ students, including PhD candidates Erfan Al-Hossami and Mika Chen. His lab’s work on blood glucose prediction has led to open-source tools like LSTM and ARIMA models, and datasets such as OhioT1DM. Current research explores creative AI, recommender systems, and hardware optimization.

Scott Burrisمشاهده پروفایل

استاد

• Public Health Law
• International Public Health Law
• Legal Epidemiology
• +۷ مورد دیگر

Scott Burris is a Professor of Law at Temple Law School and Professor in Temple's School of Public Health, where he directs the Center for Public Health Law Research. He has been a faculty member at Temple since 1991 and is internationally recognized for his pioneering work in public health law, particularly in legal epidemiology, policy surveillance, and the intersection of law with HIV/AIDS policy and substance abuse. Professor Burris received his J.D. from Yale Law School and his B.A. from Washington University in St. Louis. His career began during the early days of the HIV/AIDS epidemic, where he served as an attorney at the American Civil Liberties Union, lobbying and litigating on behalf of people with HIV. He edited the first systematic legal analysis of HIV in the United States, "AIDS and the Law: A Guide for the Public" (Yale University Press, 1987). Burris's research focuses on how law influences public health and health behavior, with particular emphasis on developing theory and methods for effective local health governance. His work spans international public health law, legal epidemiology, policy surveillance, substance abuse policy, and housing law. He has made significant contributions to understanding the impact of law on HIV prevention, opioid overdose prevention, and pandemic response. His recent work increasingly examines methodological rigor in legal epidemiology, the application of artificial intelligence to legal analysis, and the relationship between housing law and health equity. His extensive publication record includes over 200 books, book chapters, articles, and reports. Recent publications demonstrate his continued leadership in advancing the science of legal epidemiology, with particular attention to methodology, policy surveillance systems, and innovative applications of technology to legal analysis. American Public Health Association Law Section Lifetime Achievement Award (2014) Jay Healey Health Law Professors award (2018) Professor Burris has served as a consultant to numerous international organizations including the United Nations Development Programme, the World Health Organization, and the United Nations Office on Drugs and Crime. He founded the Public Health Law Research Program for the Robert Wood Johnson Foundation in 2009, which has supported over 80 empirical studies of the impact of law on health. His research has been funded by major organizations including the Robert Wood Johnson Foundation, the Open Society Institute, the National Institutes of Health, the Bill and Melinda Gates Foundation, and the Centers for Disease Control and Prevention. He is the founder of Legal Science, LLC, a private company dedicated to improving access to legal information and supporting policy surveillance practice. He also serves as an advisor to several international institutions including the Tsinghua University AIDS Institute, the Shanghai Academy of Social Sciences Research Center for HIV/AIDS Public Policy, and the Program in Bioethics at Monash University. His work bridges academic research, practical application, and policy development in the field of public health law.

Michael Weharمشاهده پروفایل

مدرس

• Computer Science
• Algorithms
• Computational Art
• +۷ مورد دیگر

Michael Wehar is a Lecturer in Computer Science at Bryn Mawr College , where he teaches Introductory Programming Courses. He is a multidisciplinary researcher and developer with a focus on algorithms , computational art , and software engineering , creating innovative tools that bridge computer science with creative applications. Co-founder of AlgoArt.org , a platform for algorithmic art creation and exhibition Creator of Word of The Hour , a multilingual vocabulary learning platform Co-developer of Treegle Dictionary , a structured definition platform His research spans computational complexity, human-computer interaction, and educational technology. Key areas include: Algorithmic Art : Generative design systems, interactive visualizations Pattern Matching : Matrix algorithms, Voronoi diagrams, formal verification Language Technology : Multilingual dictionaries, crowdsourced translation systems Educational Tools : Git repository analysis, interactive learning platforms His 15 most recent publications focus on topics ranging from 2D pattern matching to ETH-based complexity lower bounds , with significant contributions to automata theory and algorithm design. He has received academic recognition including the Best Faculty Poster at CCSC:EA 2022 and Honorable Mention at IFoRE 2022 . As a dedicated mentor, he has guided over 100 students across institutions like Swarthmore College, Temple University, and University at Buffalo in projects spanning: Web development frameworks AI applications in art and education Mobile productivity tools Language learning platforms Game development projects

Hwee-Joo Kamمشاهده پروفایل

دانشیار

• Cybersecurity
• Secure Coding
• Database Security
• +۵ مورد دیگر

Hwee-Joo Kam is an Associate Professor in the Information and Technology Management Department at The University of Tampa. She holds a D.Sc. from Dakota State University, after completing her M.A. (University of Nebraska-Lincoln) and B.S. (University of Nebraska). Research Focus: Dr. Kam specializes in cybersecurity education and policy, with an emphasis on secure coding practices, database security, and the intersection of cultural factors with organizational security. Her work explores motivational frameworks in security training, human factors in cybersecurity, and the application of behavioral theories to improve compliance and incident response. Professional Activities: She has published in journals like Computers & Education and Journal of Information Security Education , and her research has been recognized with a best paper nomination at ECIS 2015. Kam actively participates in cybersecurity workshops, including the WISE program at UC Berkeley and SEED at Syracuse University. Awards & Certifications: GIAC Mobile Device Security Analyst (GMOB) Certification (2014) WISE Scholarship for Cybersecurity Workshop (2015) SEED Cybersecurity Workshop Scholarship (2015) Teaching & Curriculum: She teaches courses on penetration testing, secure communication strategies, competitive intelligence (including cyberterrorism analysis), and social network analysis. Her pedagogical innovations include integrating real-world cybersecurity scenarios into classroom activities.

Wei Leمشاهده پروفایل

دانشیار

• AI
• Machine Learning
• Software Engineering
• +۵ مورد دیگر

Dr. Wei Le is an Associate Professor in the Department of Computer Science at Iowa State University. His primary affiliations include the Program Analysis & AI Lab and collaborative work with Mayo Clinic. He holds a Ph.D. in Computer Science from the University of Virginia (2010). His research focuses on the intersection of AI and software engineering, particularly in trustworthy AI systems, vulnerability detection, and program analysis. Key areas include AI for medicine, analyzing AI models, and improving software reliability through techniques like dataflow analysis and symbolic execution. Recent work emphasizes efficient vulnerability detection using deep learning (e.g., ICSE 2024), numerical instability in ML applications (FSE 2025), and GPU numerical testing (SC 2024). His research has been supported by NSF, Google, and DARPA. Notable awards include the Distinguished Paper Award at FSE 2016 and Best Presentation at FSE 2008. He has advised over 10 students and collaborates with institutions like Columbia University and UCLA. Teaching responsibilities include courses on program analysis (COM S 413/513), principles of programming languages, and advanced AI topics. He actively contributes to conferences as a PC member and area chair (e.g., ICSE, FSE).

Robyn Lutzمشاهده پروفایل

استاد

• Software Engineering
• Software Safety
• Molecular Programming
• +۵ مورد دیگر

Robyn Lutz is a Distinguished Professor of Computer Science and Faculty Member in Bioinformatics and Computational Biology at Iowa State University. She directs the Laboratory for Software Safety (LSS) and co-directs the Laboratory for Molecular Programming (LAMP). Her research focuses on software engineering for safety-critical systems, molecular programming, and formal methods. She has held roles such as ACM Distinguished Scientist and IEEE Fellow. Her work spans federally funded projects including NASA’s safety-aware ecosystems for unmanned systems and NSF initiatives on molecular programming and software dependability. She has authored influential publications on safety assurance cases, chemical reaction networks, and requirements engineering for nanoscale systems. Dr. Lutz has served on program committees for major conferences like ICSE, RE, and FSE, and delivered keynotes at venues like SAFECOMP and RE 2016. Her contributions include advancements in safety-critical software design, molecular systems verification, and interlocking safety frameworks for autonomous systems. She teaches courses such as Software System Safety and Requirements Engineering, and has developed tools like PLFaultCAT for safety analysis. Her labs focus on bridging software engineering principles with emerging domains like synthetic biology and nanotechnology.

Gordon Kindlmannمشاهده پروفایل

دانشیار

• Biomedical Image Analysis
• Scientific Visualization
• Systems
• +۵ مورد دیگر

Gordon Kindlmann is an Associate Professor of Computer Science at the University of Chicago, affiliated with the Systems Group research community. His work bridges computational imaging science and visualization theory, focusing on biomedical applications and machine learning integration. He leads projects in diffusion MRI analysis, surgical planning tools like SlicerDMRI, and theoretical advancements in visualization design. Research Interests: Biomedical Image Analysis Scientific Visualization Theory High Performance Computing Medical Imaging Algorithms Machine Learning Applications Recent Articles Trends: His work emphasizes cardiovascular modeling (e.g., aortic dissection prediction) and visualization validation techniques. Recent collaborations include optimizing visualization tools for scalability and accuracy in threaded data exploration. Awards: None explicitly listed in provided text. Grants/Advising: Involved in CDAC Discovery Grants (2019) and actively supports student research, though specific advisees are not listed here. His lab develops open-source tools like Diderot for tensor field visualization. Labs & Teams: Member of the Systems Group, a collaborative environment advancing systems research, programming languages, and software engineering.

Xin Weiمشاهده پروفایل

استاد مهمان

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۳ مورد دیگر

Xin Wei is a Visiting Professor in the Physics Department at Stanford University, affiliated with the School of Humanities and Sciences. Their research focuses on advancing artificial intelligence, machine learning, and natural language processing, with a particular emphasis on multimodal models, data valuation, and ethical AI practices. Xin Wei’s work bridges theoretical contributions with applied studies in areas such as large language models, peer review systems, and clinical AI adoption. They have published extensively on topics including model card analysis, distribution shifts, and dataset documentation. Research interests include the societal impact of AI, improving model transparency, and addressing disparities in AI performance across diverse datasets. Their recent work explores methods to enhance multimodal state-space models, adaptive agentic systems, and the ethical implications of AI in scientific writing and healthcare. Key contributions include frameworks like LlamaFusion for multimodal generation, Metashift for evaluating distribution shifts, and Opendataval for data valuation benchmarking. Xin Wei’s interdisciplinary approach integrates computer science, physics, and ethics to drive innovation while ensuring responsible AI development.

Shawn Jordanمشاهده پروفایل

دانشیار

• Engineering Design Education
• Culturally Relevant Pedagogy
• K-12 Engineering Education
• +۷ مورد دیگر

Shawn Jordan serves as Interim Director of the School of Integrated Engineering and Associate Professor in the Ira A. Fulton Schools of Engineering at Arizona State University. His academic appointments span multiple units including the School for the Future of Innovation in Society, Mary Lou Fulton Teachers College, and the Julie Ann Wrigley Global Futures Laboratory. His research fuses STEM with arts and cultures to create societal impact, focusing on context-centered engineering design education. Key areas include culturally relevant pedagogy for Navajo communities, K-12 engineering education, and the Maker movement's integration into formal education. He directs the STEAM Labs™ program engaging students in chain reaction machine design. NSF CAREER Award: 'Engineering Design Across Navajo Culture, Community, and Society' Co-PI on NSF Revolutionizing Engineering Departments grant 'Additive Innovation' PI on multiple NSF ITEST and Rogers Foundation grants for Native American STEM education Guinness World Record holder for Rube Goldberg machine complexity Jordan's scholarly output shows consistent growth in engineering education research, with recent focus on secondary data analysis frameworks, doctoral student development, and culturally responsive curriculum design. His work bridges formal education with maker culture through projects like STEAM Labs™. Presidential Early Career Award for Scientists and Engineers (2017) ASEE PRISM '20 Faculty Under 40' (2014) ASU President's Medal for Social Embeddedness (2022) Multiple ASU and Fulton Schools teaching awards He mentors across multiple doctoral programs including Engineering Education Systems and Design, Human and Social Dimensions of Science and Technology, and Mechanical Engineering. His service includes leadership roles in ASEE, ECEDHA, and advisory positions with the Inclusive Engineering Foundation and South Mountain Community College. Jordan directs the STEAM Labs™ Center for K-12 Research and Engagement, which develops chain reaction machine curricula. His work with the Navajo Nation involves community-based participatory design of culturally relevant engineering education. The lab connects university research with K-12 implementation through partnerships with tribal communities and school districts.

Wen Yeمشاهده پروفایل

استادیار

• User Experience Design
• Empathy-Driven Design
• Wearable Technology
• +۳ مورد دیگر

Wen (Vivian) Ye is an Assistant Professor of Practice in the Department of Design at the University of Texas at Austin. She holds dual Master of Fine Arts degrees from the University of California–Davis and the Marangoni Institute in Italy. Her academic role combines teaching design thinking and advanced design studio courses with industry experience from roles as a fashion designer at VERO MODA and a global fashion buyer for Armani. Her research focuses on user experience, empathy-driven design, and wearable technology, emphasizing cross-disciplinary collaboration. Ye actively participates in National Science Foundation (NSF) projects aimed at improving transportation and power systems through electric vehicles and clean energy solutions. She designs educational materials for these initiatives, bridging academic and industrial applications. Her work highlights innovation in sustainable technology and human-centered design principles. Her recent publications span data science code generation, neural network adaptation, and uncertainty quantification in machine learning. These contributions address foundational challenges in AI and computational methodologies, reflecting her dual expertise in design and technical systems.

Hessam Mahdavifarمشاهده پروفایل

دانشیار

• Coding and Information Theory
• Wireless Communications
• Data Privacy and Security
• +۵ مورد دیگر

Hessam Mahdavifar is an Associate Professor in the Department of Electrical and Computer Engineering at Northeastern University's College of Engineering. His research focuses on coding theory, wireless communications, data privacy, and privacy-preserving computing. He holds a PhD from the University of California San Diego (2012), an MS from UCSD (2009), and a BS from Sharif University of Technology (2007). Key research areas include analog subspace coding for non-coherent networks, polar coding for low-capacity channels, and privacy-preserving protocols for distributed learning. His work bridges information theory with practical applications in secure communication and federated learning systems. Notable contributions include analog secret sharing frameworks and coded computing techniques for resilient distributed algorithms. Awards: NSF CAREER Award (2020), Qualcomm Innovation Fellowship (2020), IEEE RFID Best Paper (2015), and International Mathematical Olympiad Silver Medal (2002/2003) Grants: NSF CAREER grant for coding subspace research, collaborative projects on polar coding and coded computing Labs/Teams: Active in Northeastern's Information Theory and Communications group, leading research on secure machine learning and wireless security His recent work emphasizes federated learning security (e.g., LightVeriFL protocols), privacy-preserving distributed algorithms, and code design for emerging communication paradigms like millimeter-wave covert systems.

Michael Colaresiمشاهده پروفایل

استاد

• International Relations
• Political Methodology
• Computational Social Science
• +۳ مورد دیگر

Michael Colaresi is the Associate Vice Provost for Data Science and William S. Dietrich II Professor of Political Science at the University of Pittsburgh, affiliated with the Dietrich School of Arts and Sciences. He holds roles in the Center for Research Computing and Data, Computational Social Science program, and the Intelligent Systems Program at the School of Computing and Information. His research focuses on computational social science, leveraging machine learning and text analysis to study national security secrecy, political violence, and human rights dynamics. Colaresi co-directs the Responsible Data Science, Complexity, and AI for Peace (RedSCAIP) Lab, emphasizing interdisciplinary collaboration to address societal challenges. Education: PhD in Political Science from Indiana University (2002). He founded the Social Science Data Analytics initiative at Michigan State University and now leads efforts in Pitt’s Institute for Cyber Law, Policy, and Security. His work has been funded by NSF grants and foundations like Hillman and RK Mellon. Research Interests: International Relations, computational methods, conflict forecasting, and the intersection of technology with democratic governance. His 2014 book *Democracy Declassified* explores secrecy dilemmas in liberal democracies and was shortlisted for the Conflict Research Society Prize. Recent projects include the ViEWS political violence early-warning system and HR-VEAW human rights analytics platform. Awards: Co-winner of the 2017 Journal of Peace Research Best Visualization Award and 2006 Gosnell Prize for Political Methodology. He serves as co-editor of *International Interactions* and collaborates with institutions like the Peace Research Institute Oslo (PRIO) and Uppsala University’s Violence Early Warning Project. Teaching: Courses include Computational Social Science, Bayesian Statistics, and Text-as-Data methods. His pedagogical focus emphasizes bridging social science theory with modern computational tools.

Thomas Ferrisمشاهده پروفایل

دانشیار

• Human Factors Engineering
• Cognitive Ergonomics
• Human-automation Interaction
• +۵ مورد دیگر

Dr. Thomas Ferris is an Associate Professor in Industrial & Systems Engineering at Texas A&M University, with an affiliation in Environmental & Occupational Health. He holds a Ph.D. in Industrial & Operations Engineering (Cognitive Ergonomics) from the University of Michigan (2010). His research focuses on human factors in complex systems, emphasizing tactile display design, cognitive workload management, and human-automation interaction. Key areas include driver distraction mitigation, medical anesthesiology support systems, and aviation weather alerting technologies. Education: Ph.D., Industrial & Operations Engineering (Cognitive Ergonomics), University of Michigan, 2010 Bachelor's Degree (Engineering Valedictorian), University of Iowa, 2003 Research Interests: Human factors in aviation and automotive systems Design of tactile and multimodal interfaces Cognitive efficiency in multitasking environments Psychophysiological workload assessment Emergency response system human factors Recent work emphasizes developing vibrotactile warning systems for construction operators, fatigue detection in aviation, and collaborative robot productivity analysis. His lab (Human Factors & Cognitive Systems) explores VR applications in remote physical examination and cybersickness mitigation strategies. Awards include the NSF Graduate Research Fellowship (2005-2008) and World Haptics Best Paper (2009). He has advised over 30 graduate students and published widely in Human Factors, IEEE Transactions, and Aviation safety journals.