جستجوی استاد راهنمای دانشگاهی

Lisa Yanمشاهده پروفایل

استاد آموزشی

• Computer Science Education
• Computing Ethics
• Teaching Assistant Training
• +۲ مورد دیگر

Lisa Yan serves as a Teaching Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, appointed in Spring 2022. She teaches core computer science education courses including CS 195 (Social Implications of Computer Technology), CS H195 (Honors variant), CS 294-189 (Teaching Process Design), and CS 375 (Teaching Techniques), holding regular office hours in Soda Hall for student engagement. Her academic credentials include: PhD in Electrical Engineering from Stanford University (2019) MS in Electrical Engineering from Stanford University (2015) BS in Electrical Engineering and Computer Science from UC Berkeley (2013) Dr. Yan's research centers on data-driven analysis of student learning in large-scale computer science courses, with significant contributions to computing ethics pedagogy and teaching assistant development programs. Her work develops innovative methodologies for assessing student earnestness in interactive lectures, creating flexible learning extensions, and designing integrity-focused assessments. Earlier research focused on software-defined networking and network switch performance optimization, demonstrating technical depth before her pivot to educational innovation. Current projects emphasize scalable teaching techniques and mastery learning frameworks that address challenges in modern CS education. Analysis of her 14 publications (2013-2024) reveals a strategic shift from computer networking (pre-2018) to computer science education research (2018-present). Recent work (2020-2024) dominates in venues like SIGCSE, featuring tools such as Otter-Grader for Jupyter notebook grading and the Earnest Insight Toolkit for lecture participation analysis. This evolution highlights her commitment to solving practical educational challenges through data analysis and tool development, particularly for large undergraduate courses. She received recognition through: The Faculty Award for Outstanding Mentorship of GSIs (2024) Lisa actively mentors Graduate Student Instructors and collaborates with educational technology initiatives. Her research team includes dedicated support staff like Taylor Kaserman (taylor.kase@berkeley.edu), reflecting structured collaboration in developing teaching innovations. She contributes to curriculum design committees within EECS, focusing on assessment integrity and scalable pedagogical methods for growing student populations. Her work operates through the EECS department's educational infrastructure, utilizing Soda Hall resources for both teaching coordination and research development, with strong connections to Berkeley's broader computing education ecosystem.

Erica R.H. Fuchsمشاهده پروفایل

استاد

• Technology Policy
• Global Manufacturing
• Innovation Policy
• +۳ مورد دیگر

Erica R.H. Fuchs is the Kavčić-Moura Professor in the Department of Engineering and Public Policy at Carnegie Mellon University (CMU), directing the Critical Technology Initiative (CTI). She holds courtesy faculty positions in Materials Science and Engineering and the Heinz College. Her research focuses on emerging technology development, commercialization, and global manufacturing, with emphasis on national policy implications. Fuchs leads interdisciplinary efforts at CTI to advance critical technology assessment frameworks, ensuring smart investments and policies for national security and economic competitiveness. Formerly, she directed the Manufacturing Futures Initiative, now an endowed institute at CMU. Education: She earned a Ph.D. (2006), M.Sc. (2003), and B.Sc. (1999) in Engineering Systems, Technology Policy, and Materials Science from MIT. Post-MIT, she was a UNIDO fellow in Beijing. Research Interests: Global innovation policy, technology commercialization pathways, and the intersection of technology with economic and security objectives. She authored influential works like the 2021 report *Securing America’s Future*, advocating for a National Technology Strategy to align multi-objective outcomes (security, equity, prosperity). Key Contributions: Catalyzed the National Network for Critical Technology Assessment, mobilizing 13+ universities to address technology gaps. Testified in Congress on supply chain resilience, EV battery policies, and semiconductor strategies. Advises entities like the National Semiconductor Technology Center and MIT’s Institute for Data, Systems, and Society. Affiliations: National Bureau of Economic Research (Research Associate), National Institute of Standards and Technology (NSTC Board), and Brookings Institution panelist. Her work is frequently cited in *Axios*, *Bloomberg*, and the *New York Times*.

Monowar Bhuyanمشاهده پروفایل

دانشیار

• Machine Learning
• Anomaly Detection
• Systems and AI Security
• +۶ مورد دیگر

Monowar Bhuyan is an Associate Professor in the Department of Computing Science at Umeå University, Sweden, leading the Cyber Analytics and Learning Group within ADSLab. He holds a Ph.D. in Computer Science from Tezpur University and has held academic positions at Assam Kaziranga University and Umeå University. His research focuses on machine learning, anomaly detection, edge AI, and distributed systems security. He has secured over 35 MSEK in grants from WASP, STINT, and EU Horizon programs. Education Ph.D. in Computer Science and Engineering, Tezpur University (2014) M.Tech. in Information Technology, Tezpur University (2009) B.E. in Computer Science and Engineering, IETE (2007) Research Interests Distributed/Federated/Responsible Machine Learning Cybersecurity and Anomaly Detection in Edge Clouds AI for DDoS Defense and Cyber Resilience Edge AI and Serverless Computing Recent Contributions His recent work addresses secure federated learning, DDoS attack detection in cloud-edge systems, and responsible AI. Key publications include novel frameworks for VSI-DDoS detection and federated learning optimizations. Awards & Grants Best Paper Awards at ICONIP 2023 and ACM ICACCI 2012 WASP NEST Grant (AIR2 Project, 5 MSEK) EU Horizon Europe Grant (SovereignEdge.Cognit, 8.27 MSEK) Lab & Collaborations He leads the Cyber Analytics and Learning Group (ADSlab), collaborating with institutions like KTH, Linköping University, and Nara Institute of Science and Technology (NAIST). The lab focuses on AI-driven security solutions for distributed systems.

Rebecca Nugentمشاهده پروفایل

استاد

• Clustering Methodology
• Record Linkage
• Educational Data Mining
• +۵ مورد دیگر

Rebecca Nugent is the Stephen E. and Joyce Fienberg Professor of Statistics & Data Science and Department Head at Carnegie Mellon University. She holds a PhD in Statistics from the University of Washington (2006), an MS in Statistics from Stanford (2006), and a BA in Mathematics, Statistics, and Spanish from Rice University (2002). Her research spans clustering methodology , record linkage , educational data mining , public health , and semantic organization , with a focus on high-dimensional data and adaptive learning environments. She leads the Integrated Statistics Learning Environment (ISLE) and Corporate Capstone programs, emphasizing low-barrier data platforms for education and industry collaboration. Academic Roles : Department Head, Carnegie Mellon; Affiliated Faculty, Block Center for Technology and Society Research Grants : NSF (2017-2019), NIH (2018), Carnegie Mellon ProSEED/Simon Initiative (2020, 2018), Berkman Fund (2014) Her 15 most recent publications focus on data science pedagogy, clustering algorithms, record linkage applications in historical and medical data, educational data mining, and semantic organization studies. Awards include the ASA Waller Education Award (2015) and the William H. and Frances S. Ryan Award (2015) . She mentors a diverse group of PhD, Master's, and undergraduate students, with alumni pursuing careers in academia, industry, and sports analytics.

• Computer Networks
• Network Reliability
• Wireless Mesh Network
• +۳ مورد دیگر

Dr. Sie Teng Soh is an Associate Professor at Curtin University's School of Electrical Engineering, Computing and Mathematical Sciences. With qualifications including a PhD from Louisiana State University, he specializes in computer networks, wireless systems, and algorithm design. Research focuses on: Network topology optimization for UAV systems Energy-efficient IoT task scheduling Reliable wireless communication protocols Game-theoretic network management Green computing in software-defined networks Publication trends show advancing work in UAV network optimization, with recent articles addressing max-min rate optimization, energy harvesting in IIoT, and machine learning approaches for coverage prediction. His research consistently addresses practical challenges in wireless network deployment under real-world constraints. Teaching areas include advanced courses in network reliability and traffic engineering. Professional service includes editorial roles for IEEE Transactions on Parallel and Distributed Systems and program committee memberships for major conferences including FAST and EuroSys.

Nate Apathyمشاهده پروفایل

استادیار

• Health Policy
• Health Services Research
• Health Informatics
• +۳ مورد دیگر

Nate Apathy is an Assistant Professor of Health Policy & Management at the University of Maryland School of Public Health and an Affiliated Research Scientist at the Regenstrief Institute. He holds a PhD in Health Policy & Management from Indiana University (2020) and completed a postdoctoral fellowship in health services research at the University of Pennsylvania (2022). His research focuses on health information technology's role in healthcare delivery reform, regulatory impacts on health IT innovation, and the use of EHR metadata to assess care quality. He examines organizational strategies to reduce IT-based burdens, particularly in primary care and specialty settings. His work bridges health policy, services research, and informatics, with emphasis on EHR documentation dynamics, clinician workflows, and interoperability challenges. Notable studies include analyses of physician EHR time allocation, telemedicine integration, and the impact of team-based documentation tools. He has contributed to national discussions on electronic health record legal settlements, opioid prescribing guidelines, and nursing home post-acute care specialization. Nate’s research has been published in journals such as Health Affairs , Annals of Internal Medicine , and Journal of the American Medical Informatics Association . He collaborates with institutions like the Leonard Davis Institute of Health Economics and focuses on translating informatics insights into actionable policy recommendations.

Abdulrahman Takiddinمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Cyber-Physical Systems
• +۳ مورد دیگر

Abdulrahman Takiddin is an Assistant Professor in the Department of Electrical & Computer Engineering at the Florida A&M University–Florida State University College of Engineering. He holds a Ph.D. in Electrical Engineering from Texas A&M University (2023), an M.S. in Data Analytics from Hamad Bin Khalifa University (2020), and a B.Sc. in Information Systems from Carnegie Mellon University (2014). His research focuses on cybersecurity in smart grids and cyber-physical systems, leveraging machine learning and graph neural networks to detect adversarial attacks such as false data injection and electricity theft. Key areas include resilient power systems, adversarial evasion attack mitigation, and spatio-temporal analysis of power distribution networks. Recent work emphasizes graph-based approaches for enhancing cyber resilience, including eigenvector centrality-enhanced networks and transfer learning solutions for small data scenarios. His publications address both foundational cybersecurity challenges and applied solutions for electrified transportation systems and smart grid infrastructure. Notable trends in his articles include advancements in unsupervised learning for voltage stability protection and recurrent graph networks for replay attack detection. His research also intersects with bioinformatics and artificial intelligence applications in healthcare, though the majority of his work centers on energy systems and cybersecurity.

Han Wangمشاهده پروفایل

استادیار

• Computer Science
• Data Privacy
• Cybersecurity
• +۲ مورد دیگر

Han Wang is an Assistant Professor in the Electrical Engineering and Computer Science department at the University of Kansas School of Engineering. His research develops privacy-preserving frameworks for distributed systems, machine learning, and data analytics. Core research areas include differential privacy implementations for federated learning environments, privacy-preserving outsourcing of anomaly detection, and adversarial attack mitigation. Recent work focuses on developing staircase randomized response mechanisms that enhance privacy without compromising data utility in location services and video analytics. Publications demonstrate consistent innovation in privacy engineering with applications spanning vehicle trajectory protection, energy trading systems, and video recognition security. Methodological approaches combine theoretical privacy guarantees with practical system implementations.

Scott Banksمشاهده پروفایل

مدرس

• Bioenergy
• Thermochemical Conversion
• Catalytic Pyrolysis
• +۵ مورد دیگر

Dr. Scott Banks is a Lecturer in Chemical Engineering & Applied Chemistry at Aston University's College of Engineering and Physical Sciences. He is affiliated with the Energy and Bioproducts Research Institute (EBRI), where he researches thermochemical conversion technologies with a focus on sustainable bioenergy solutions. Education: PhD in Ash control methods to limit biomass inorganic content and its effect on fast pyrolysis bio-oil stability, Aston University (2014) Aston University Modular Award – Introduction to Learning and Teaching Practice (2020-2021) Research Focus: His work centers on catalytic pyrolysis, biomass ash control, bio-oil stabilization, and gasification char utilization. He develops advanced thermal conversion methods to create circular economy solutions and supports greenhouse gas reduction through renewable energy systems. Current work explores hydrogen production pathways from biomass derivatives. Publication Trends: Recent articles demonstrate a strong focus on biomass pyrolysis optimization, renewable policy frameworks, and sustainable feedstock development. His research employs experimental thermochemical analysis and reactor design to advance bioenergy conversion efficiency. Teaching: Module leader for Life Cycle Analysis, Renewable Energy, and Research Methods in the MSc Sustainable Engineering program.

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).

Lei Liuمشاهده پروفایل

استاد

• Biostatistics
• Data Science
• Survival Analysis
• +۵ مورد دیگر

Lei Liu, PhD, is a Professor of Biostatistics, Medicine, and Statistics and Data Science at Washington University in St. Louis. He holds positions in the Roy and Diana Vagelos Division of Biology & Biomedical Sciences (DBBS), the Institute for Informatics, Data Science and Biostatistics (I2DB), and the Center for Biostatistics and Data Science (CBDS). His research focuses on biostatistical and data science methods, including survival analysis, longitudinal data modeling, and machine learning applications in healthcare. He collaborates with clinicians across disciplines like cardiology, ophthalmology, and addiction medicine. Dr. Liu’s work emphasizes high-dimensional omics data analysis, medical cost modeling, and joint multi-outcome models. He is an Associate Editor of Biometrics and a former member of the NIH Biostatistical Methods and Research Design Study Section. He mentors underrepresented minority researchers through the NHLBI PRIDE program.

Andreas S. Schulzمشاهده پروفایل

استاد

• Mathematical Optimization
• Algorithm Design
• Operations Research
• +۵ مورد دیگر

Prof. Dr. Andreas S. Schulz is a faculty member at Technische Universität München (TUM), holding a chair in the Department of Mathematics and the Department of Business and Economics. He previously served as the Patrick J. McGovern Chair of Management and Professor of Mathematics at MIT. His research focuses on mathematical optimization, algorithm design, and their applications in logistics, production, healthcare systems, and online advertising. He has held visiting professorships at institutions such as the Sauder School of Business (UBC) and ETH Zurich. Prof. Schulz’s research bridges operations research, theoretical computer science, and economics. He develops analytical methods to solve complex decision-making problems in business, including scheduling, resource allocation, and network optimization. A key interest is applying mathematical approaches to enhance healthcare delivery and system efficiency. Education: PhD in Operations Research (MIT), prior academic roles at MIT and visiting institutions. Key Achievements: Alexander von Humboldt Professorship (2014), Humboldt Research Award (2010), Glover-Klingman Prize (2006). Research Themes: Robust optimization, approximation algorithms, scheduling theory, and algorithmic game theory. His publications span topics like integer programming, optimal transport, and congestion games. He collaborates across disciplines, emphasizing practical applications of theoretical insights.

• Indoor Environmental Quality (IEQ)
• Thermal Comfort
• Building Science
• +۴ مورد دیگر

Dr. Thomas Parkinson is a Lecturer at The University of Sydney and Deputy Director of the IEQ Lab within the School of Architecture, Design and Planning. His research focuses on high-performance buildings, indoor environmental quality (IEQ), and human thermal physiology. He holds a PhD in Architectural Science from The University of Sydney and has led technical development of the SAMBA IEQ Monitoring System. He previously worked at the Center for the Built Environment at UC Berkeley. Education: BEnvMgt, BSc(Hons1), PhD in Architectural Science (University of Sydney). Research interests include thermal comfort dynamics, sensor technology for built environments, and adaptive comfort models. Key contributions include the ASHRAE Global Thermal Comfort Database II and studies on workplace dissatisfaction in 600 office buildings. Awards: 2022 Ralph G. Nevins Award (ASHRAE) for thermal comfort research, 2018 Best Paper Award (Building and Environment). He reviews for journals like Building and Environment and serves on ASHRAE Technical Committees. Teaching: Courses include BADP1001 Empirical Thinking and DESC9067 Mechanical Services. Current advisee: Sepideh Borghei (PhD project on indoor greenery's impact). Affiliations: Lawrence Berkeley National Laboratory, UC Berkeley's Center for the Built Environment. Active in ASHRAE committees and professional networks.

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.

David S Kossonمشاهده پروفایل

استاد

• Nuclear Waste Management
• Environmental Remediation
• Leaching Assessment
• +۵ مورد دیگر

Dr. David S. Kosson is a distinguished faculty member at Vanderbilt University, holding the Gass Family Chair in Energy and the Environment. He serves as Professor of Civil and Environmental Engineering, Chemical and Biomolecular Engineering, and Earth and Environmental Sciences. As Director of the Consortium for Risk Evaluation with Stakeholder Participation (CRESP) and the Environmental Laboratory, he leads multidisciplinary research addressing nuclear waste management, environmental remediation, and policy. His work has established frameworks like the U.S. Leaching Environmental Assessment Framework (LEAF), impacting national waste management policies. Dr. Kosson earned his Ph.D., M.S., and B.S. in Chemical Engineering from Rutgers University. He previously chaired Vanderbilt’s Civil and Environmental Engineering Department (2000–2012). His research focuses on nuclear/chemical waste containment, contaminant mass transfer, and eco-cultural risk assessment. He advises U.S. federal agencies on defense waste remediation and chemical weapons demilitarization. Education: Ph.D., Chemical and Biochemical Engineering, Rutgers University M.S., Chemical and Biochemical Engineering, Rutgers University B.S., Chemical Engineering, Rutgers University Key Roles: CRESP Principal Investigator Environmental Laboratory Director Former Department Chair (Civil & Environmental Engineering) His research integrates laboratory experiments with field data to model long-term behavior of waste forms and geological interfaces. Notable contributions include studies on cement-rock interactions, PFAS leaching, and ecological risk assessment at DOE sites like Hanford and Oak Ridge. He has authored over 200 publications, advancing risk-informed decision-making in waste management. Scientific contributions span nuclear waste durability, eco-cultural justice frameworks, and sustainable materials engineering. He collaborates internationally on deep geological disposal systems and environmental policy.