جست‌وجوی استاد و پژوهشگر

• Operations Research
• Production Systems
• GPU Computing
• +۷ مورد دیگر

Rakesh Nagi is the Donald Biggar Willett Professor of Engineering at the University of Illinois, Urbana-Champaign, affiliated with the Department of Industrial and Enterprise Systems Engineering. He previously served as Department Head (2013-2019) and Interim Director of the Illinois Applied Research Institute (2016-2018). His academic journey includes roles at the University at Buffalo (SUNY) from 1993-2013, including Chair of Industrial and Systems Engineering (2006-2012). He earned his Ph.D. (1991) and M.S. (1989) from the University of Maryland, and B.E. (1987) from IIT Roorkee (formerly University of Roorkee). His research focuses on production systems, applied and military operations research, GPU-accelerated algorithms, facility layout optimization, and social network analysis. Notable contributions include location-theoretic approaches to facilities design, agile manufacturing systems, and influence maximization in social networks. He has published extensively in journals like Operations Research, Management Science, and IEEE Transactions series. Dr. Nagi's honors include the IISE David F. Baker Distinguished Research Award (2022), INFORMS MAS Koopman Prize (2021), and NSF CAREER Award (1996). His work bridges theoretical advancements with real-world applications in logistics, UAV routing, and illicit network detection. Current projects involve GPU-accelerated combinatorial optimization, risk-averse equilibrium models, and parallel computing frameworks for large-scale problems. Education: Ph.D. & M.S. in Mechanical Engineering, University of Maryland (1991, 1989) B.E. in Mechanical Engineering, IIT Roorkee (1987) Awards: Recipient of 15+ prestigious awards including fellowships and national recognitions Lead on $6.25M ARO MURI grant for Hard-Soft Information Fusion Labs & Teams: Director of High-Performance Computing Research Lab Principal Investigator for IARPA-funded Knowledge Discovery projects

Jessica Kaszaمشاهده پروفایل

استاد

• Biostatistics
• Causal Inference
• Cluster Randomised Trials
• +۳ مورد دیگر

Jessica Kasza is a Professor of Biostatistics at Monash University's School of Public Health and Preventive Medicine. She leads methodological advancements in longitudinal cluster randomized trials, particularly in stepped wedge and cluster crossover designs. Her research interests include causal inference, healthcare provider comparison, and optimizing trial designs for efficiency. She has held leadership roles, including President of the Statistical Society of Australia (2020–2022), advocating for an inclusive statistical community. She completed her PhD at the University of Adelaide and has been at Monash since 2013. Education: PhD in Statistics, University of Adelaide (2010) Bachelor of Mathematical and Computer Sciences (Honours), University of Adelaide (2005) Bachelor of Science in Pure Mathematics and Statistics, University of Adelaide (2004) Research Interests: Her work focuses on statistical methods for longitudinal cluster trials, causal inference frameworks, and improving healthcare provider comparisons. She has contributed to SDGs related to health and well-being through methodological innovations. Recent Projects: Includes initiatives like the Flexible Stepped Wedge Design Research (2025–2028) and the Residential Aged Care Enhanced Dementia Diagnosis Study (2022–2028). She collaborates on projects addressing rural healthcare access and clinical trial design optimization. Key Awards: Includes the 2016 AMREP Best Paper Award, multiple John McNeil Early Career Researcher Prizes (2016, 2018, 2019), and the 2019 Alfred Research Alliance Best Paper Award. Grants & Teams: Active in securing ARC and NHMRC grants. Collaborates with multidisciplinary teams on trials like the Mega-ROX HIE and SCANPatient studies. Her work emphasizes practical applications in healthcare and statistical rigor.

• Computer and Network Security
• Computer Networking
• Network Modeling and Performance Evaluation
• +۴ مورد دیگر

Cliff C. Zou is a Professor at the Department of Computer Science, University of Central Florida (UCF), and Program Coordinator for Master's degrees in Digital Forensics and Cyber Security and Privacy. He serves as a UCF Cybersecurity and Privacy Cluster member, Point-of-Contact for UCF CAE-CD/CAE-R designations, and leads the Data Systems Group. With a Ph.D. from University of Massachusetts, Amherst (2005), and B.S./M.S. from USTC, he has received numerous awards including the UCF-TIP Award (2013, 2024), Best Paper Awards, and Fellowships. Ph.D., Electrical & Computer Engineering, University of Massachusetts, Amherst (2005) M.S., Automation, University of Science & Technology of China (USTC) (1999) B.S., Automation, USTC (1996) His research spans Computer and Network Security , IoT Security , Blockchain Systems , Wireless Network Security , and Malware Analysis . Recent work focuses on adversarial machine learning, side-channel attacks, encrypted traffic classification, and secure IoT architectures. His publications (2025-2020) highlight trends in deep learning-based defense , WiFi fingerprinting , TrustZone security , and malware propagation . Scientific Awards: UCF Teaching Incentive Program (TIP) Award (2024, 2013) Best Paper Award (2023) Best Student Paper Award (ACSAC 2007) Guo Moruo Scholarship (USTC, 1996) Graduate Fellowships (University of Massachusetts, 1999-2001) Prof. Zou has advised 14 PhD graduates and numerous Master's/BS students, many now holding academic/industry roles. His funded projects include NSF grants (DGE-2325452, DGE-2042996, DGE-1723587, DGE-1915780), US Army PEO STRI collaborations, and Florida Center for Cybersecurity seed grants. He leads the cyberforensic.net educational platform and has contributed to free IoT security labs for professionals.

Anne-Marie Kermarrecمشاهده پروفایل

پژوهشگر

• Gossip-based networking
• P2P systems
• Social Networks
• +۶ مورد دیگر

Anne-Marie Kermarrec is a Senior Researcher at INRIA (France), with prior roles at Microsoft Research (UK) and the University of Rennes 1 (France). Her work focuses on decentralized systems, including gossip protocols, peer-to-peer networks, social networks, and collaborative filtering. PhD in Computer Science (Rennes, 1996) Her research spans epidemic algorithms, content-based search in large-scale networks, and scalable group communication. She pioneered gossip-based peer sampling and multicast infrastructures like Scribe and SplitStream. Her publications highlight applications in decentralized news recommendation (AllYours), network coding, and privacy-preserving social platforms (Gossple). Key article trends include gossip protocols , P2P systems , social network analysis , decentralized storage , and collaborative filtering . She received the Michel Monpetit Award (2011), ERC Starting Grant (GOSSPLE, 2008-2013), and an ICDCS Best Paper Award (2010). Michel Monpetit Award (2011) ERC PoC AllYours (2013) ERC Starting Grant GOSSPLE (2008-2013) ICDCS Best Paper Award (2010) Kermarrec led program committees for major conferences (e.g., EuroSys, Middleware) and chaired the ACM Software System Award. Her software contributions include AllYours (news recommender), GossipLib (gossip library), and GossipPeer (P2P platform maintenance).

Stephen Parkerمشاهده پروفایل

استاد

• Physics
• Material Science
• Catalysis
• +۳ مورد دیگر

Stephen Parker, Ph.D., is a Professor of Physics at Saint Martin's University, affiliated with the College of Arts and Sciences. His research focuses on catalysis, surface chemistry, and nanoparticle dynamics, with notable contributions to catalyst sintering kinetics and thin-film engineering. He holds a Ph.D. from the University of Washington (alongside M.S. and B.A. degrees from the University of Washington and Lawrence University, respectively). Education: Ph.D., University of Washington M.S., University of Washington B.A., Lawrence University Research Interests: Professor Parker explores material science phenomena at the nanoscale, particularly the behavior of supported metal nanoparticles in catalytic systems. His work addresses challenges in catalyst stability, surface reactivity, and the design of energy-efficient materials. Recent studies include oxygen reduction kinetics in thin films and the thermal stability of gold and copper nanoparticles on oxide substrates. Publications Trends: His articles span catalytic mechanisms, surface adsorption geometry, and computational modeling of nanoparticle behavior. Key themes include optimizing catalyst performance through understanding size-dependent energetics and improving material durability under operational conditions. Awards and Grants: No specific awards or grants are listed in the provided information. Advising and Labs: No student advisees or lab affiliations are explicitly mentioned in the text.

Tasha Beretvasمشاهده پروفایل

استاد

• Quantitative Methods
• Psychometrics
• Multilevel Modeling
• +۳ مورد دیگر

Tasha Beretvas is a Professor of Quantitative Methods in the Department of Educational Psychology and Associate Dean of Research and Graduate Studies at the College of Education, University of Texas at Austin. She holds the John L. and Elizabeth G. Hill Professorship and has led faculty affairs as Senior Vice Provost for Faculty Affairs. Research focuses on psychometric models, multilevel modeling with complex data structures (e.g., student mobility), and meta-analytic techniques for single-case designs. Key contributions include methodological advancements in multilevel modeling, meta-analysis of dependent effect sizes, and synthesis of single-subject experimental data. Her work appears in journals like Multivariate Behavioral Research , Psychological Methods , and Journal of Educational Psychology . Recent articles emphasize meta-analysis of single-case designs, handling missing data in meta-regression, and cluster wild bootstrapping for dependent effect sizes. She has pioneered tools like MultiSCED for multilevel analysis of single-case data. Scientific Awards Regents Award for Excellence in Undergraduate Teaching Grants Principal Investigator (PI) or Co-PI on multiple Institute of Education Sciences (IES) grants Leadership Elected member, Society for Research Synthesis Methodology Past Associate Editor, Journal of School Psychology and Journal of Educational Psychology Member, Design and Analysis Committee for the National Assessment of Educational Progress (NAEP)

Dipayan Banerjeeمشاهده پروفایل

استادیار

• Supply Chain Optimization
• E-Commerce Operations
• Last-Mile Delivery
• +۷ مورد دیگر

Dipayan Banerjee is an Assistant Professor of Supply Chain Management at the Quinlan School of Business, Loyola University Chicago. He holds a PhD and MS in Operations Research from Georgia Tech and a BS in Industrial Engineering and Management Sciences from Northwestern University. Research Interests: His work centers on supply chain optimization, e-commerce fulfillment, and last-mile delivery logistics, with specific emphasis on dynamic pricing, service region design, and equity in transportation systems. He also investigates revenue management and public school transportation scheduling. Publication Trends: His recent publications (2019–2025) focus on modeling and optimizing same-day and next-day delivery systems, incorporating time-varying access, fleet sizing, and pricing strategies. A recurring theme is the integration of equity and efficiency in logistics, particularly in public and urban transportation contexts. Transportation Science Meritorious Service Award, 2024 Finalist - Best Student Paper Award, INFORMS Transportation Science and Logistics Society, 2023 Finalist - Undergraduate Operations Research Prize, INFORMS, 2019 Advising and Grants: While no formal students are listed, he actively contributes to academic research and teaching in supply chain management. He has not received explicit grant mentions in the text but publishes in premier journals, suggesting competitive research support. He teaches courses including Introduction to Supply Chain Management and Inventory Management. Labs and Research Groups: Though not directly affiliated with a named lab in the text, his research aligns with logistics, transportation science, and applied artificial intelligence in business operations. His work may be connected to broader initiatives such as the Lab for Applied Artificial Intelligence or the CME Group Foundation Business Analytics Lab at Quinlan.

• Aging and the Life Course
• Disaster Impact and Recovery
• Housing Stability
• +۴ مورد دیگر

Dr. Alexis Merdjanoff serves as Assistant Professor of Social and Behavioral Sciences and Director of the Environmental Public Health Program at New York University's School of Global Public Health. Her research bridges sociology and public health, focusing on long-term disaster impacts on vulnerable populations, particularly examining how social inequalities shape health outcomes following natural hazards including hurricanes, floods, extreme heat, and wildfires. Her educational background includes a BS in Sociology (Magna Cum Laude) from New York University, followed by an MA and PhD in Sociology from Rutgers University. This strong sociological foundation informs her holistic approach to understanding disaster exposure, recovery processes, and resilience mechanisms. Dr. Merdjanoff's research interests span aging and the life course, disaster impact and recovery, housing stability, mental health, and social determinants of health. She employs mixed-methods research approaches, including semi-structured in-depth interviewing, focus groups, and survey analysis, to examine how environmental stressors create prolonged economic, emotional, and health burdens long after disaster events have passed. Her recent work explores the post-disaster resilience of older adults in high-risk coastal areas. Analysis of her recent publications reveals consistent themes across disaster types and populations, with particular emphasis on vulnerable groups including children, older adults, and racial/ethnic minorities. Her work increasingly addresses climate change impacts, cumulative disaster exposures, and the intersection of environmental hazards with social inequalities. Innovator Program Fellow, National Center for Atmospheric Research (2019) Butler-Williams Scholar, National Institute on Aging, National Institutes of Health (2019) Aging and Rural Health Research Award, American Public Health Association (2017) Best Dissertation in Mental Health, American Sociological Association (2016) Anne Foner Dissertation Prize, Rutgers University (2016) As Director of Research for the Population Impact, Recovery and and Resilience (PiR2) research program, Dr. Merdjanoff leads several major longitudinal studies including the Katrina@10 Program, Sandy Child and Family Health Study, and SCALE-UP East Boston project. She has secured funding from multiple sources including the National Institute on Aging and National Center for Atmospheric Research. Dr. Merdjanoff teaches courses including 'Qualitative & Field Methods in Global Public Health' and 'Global Issues in Social & Behavioral Health,' mentoring the next generation of public health researchers. Her work spans multiple research teams focused on environmental public health, with particular emphasis on the Gulf Coast Population Impact study examining Deepwater Horizon effects, and the Sandy Child and Family Health study analyzing Hurricane Sandy impacts. These teams employ interdisciplinary approaches combining sociology, epidemiology, environmental science, and public health practice.

Srinath Maheshمشاهده پروفایل

پژوهشگر

• Environmental Engineering
• Transportation Sustainability
• Emission Modeling
• +۳ مورد دیگر

Dr. Srinath Mahesh is a postdoctoral researcher at the DiTTlab within the Department of Transport and Planning at Delft University of Technology’s Faculty of Civil Engineering and Geosciences. Previously, he held a postdoctoral position at Trinity College Dublin’s Department of Civil, Structural, and Environmental Engineering. His research focuses on modeling the environmental impact of transportation systems, particularly quantifying vehicle emissions via real-world measurements (e.g., PEMS, remote sensing) and integrating emission models into traffic simulations. Current work involves the TULIPS project, advancing airport sustainability and aviation decarbonization. Education: PhD in Civil Engineering from Indian Institute of Technology Madras (IIT-M) M.Tech and B.Tech in Civil Engineering with a Transportation specialization Research Interests: Quantifying emissions from motorcycles, cars, buses, and trucks Integrating emission models into traffic simulation frameworks Sustainable airport landside transport systems Decarbonization strategies for aviation and urban freight Key Projects: TULIPS: Enhancing airport sustainability through decarbonization REDMAP: Roadside emissions analysis in Dublin Advising & Grants: While no student advisees are listed, his research contributions inform policy and sustainable infrastructure development. His work has been supported through institutional collaborations and project grants. Labs & Affiliations: Active in DiTTlab and affiliated with TU Delft’s Transport & Planning department, contributing to interdisciplinary research on sustainable mobility solutions.

• Biostatistics
• Public Health
• Health Services Research
• +۵ مورد دیگر

Paula Diehr is a Professor of Biostatistics and Health Services at the University of Washington's School of Public Health and Community Medicine. With a distinguished career spanning several decades, Dr. Diehr has established herself as a leading expert in biostatistics and health services research. Dr. Diehr's research focuses on critical methodological issues in public health, including small area statistics, health care utilization analysis, and statistical methods for population health research. Her work on the Diehr Rule for diagnosing pneumonia represents an important clinical decision tool, while her more recent work on the Healthy Life Calculator has contributed significantly to aging and longevity research. Her publications demonstrate consistent contributions to methodological advancements in public health research, particularly in statistical approaches for analyzing health care data and evaluating community-based interventions. Dr. Diehr has published extensively in top public health journals including Annual Review of Public Health, American Journal of Public Health, and Medical Care. UCLA Alumni Hall of Fame recipient Dr. Diehr has been instrumental in developing statistical methodologies that address real-world challenges in health services research, with particular emphasis on the proper application of statistical assumptions in large public health datasets and innovative approaches to analyzing health care utilization patterns. Her work bridges theoretical statistical methods with practical public health applications.

Bernard Herskovicمشاهده پروفایل

دانشیار

• Financial Economics
• Economic Theory
• Macroeconomics
• +۲ مورد دیگر

Bernard Herskovic is an Associate Professor of Finance at UCLA Anderson School of Management and a Faculty Research Fellow at the National Bureau of Economic Research (NBER). His research focuses on financial economics, economic theory, and macroeconomics with a particular emphasis on network theory applications to asset pricing and financial systems. Education : Ph.D. in Economics (2015, New York University), M.A. in Economics (2010, Pontifícia Universidade Católica do Rio de Janeiro), B.A. in Economics (2008, Universidade Federal de Minas Gerais) His groundbreaking work demonstrates how input-output network changes represent systematic risk factors in asset pricing. He also explores information leakage from short sellers and intermediary capacity limitations in financial markets. Key research themes include: Network effects in production systems Idiosyncratic volatility dynamics Dealer intermediation mechanisms Risk-bearing capacity in financial sectors Scientific Awards : Cubist Systematic Strategies Ph.D. Candidate Award (2015) C.V. Starr Center Fellowship (2012) McCracken Ph.D. Fellowship (2010–2015) PUC-Rio MA Dissertation Honorable Mention (2009) Herskovic teaches Investment Management courses in Anderson's MBA programs, emphasizing mathematical precision balanced with intuitive explanations. He has developed and taught international trade and finance courses since his Ph.D. training at NYU.

Pradip K Srimaniمشاهده پروفایل

استاد

• Parallel and Distributed Computing
• Interconnection Networks
• Self-Stabilizing Systems
• +۲ مورد دیگر

Pradip K Srimani is a Professor at the School of Computing , Clemson University , with research focus on Parallel and Distributed Computing , Self-Stabilizing Systems , and Graph Theory Applications . He is an IEEE Life Fellow and ACM Distinguished Scientist with over 250 publications. Research Interests Self-stabilizing algorithms for network graphs Ontology-based biomedical information retrieval High-performance computing resource management Biologically inspired distributed algorithms Network topology computation Recent publications demonstrate expertise in token circulation protocols, genome assembly frameworks, and semantic similarity measurement. He has served on program committees for APDCM , GPC-2018 , and IEEE BigMM conferences, while maintaining editorial roles at International Journal of High Performance Computing and Journal of Big Data . Scientific Awards IEEE Life Fellow ACM Distinguished Scientist

Douglas P. Woodwardمشاهده پروفایل

استاد

• Regional Economics
• Urban and Industrial Clustering
• Foreign Direct Investment
• +۵ مورد دیگر

Douglas P. Woodward is a Professor of Economics and Director of the Division of Research at the Darla Moore School of Business, University of South Carolina. He holds a Ph.D. in Economics from the University of Texas at Austin (1986), an M.A. from New York University (1981), and a B.A. from SUNY Purchase (1978). His academic career spans over three decades, beginning at the University of South Carolina in 1987. He has served as Director of the Division of Research since 1995. Educations: Ph.D., Economics, University of Texas at Austin (1986) M.A., Economics, New York University (1981) B.A., Economics, State University of New York at Purchase (1978) Woodward’s research focuses on regional economics, firm location, industrial clustering, and foreign direct investment. His co-authored book The New Competitors (1989) was recognized by Business Week and Fortune . His recent work explores African economic development, knowledge spillovers, and regional economic clusters globally. He has secured grants from the NSF and U.S. Department of Education, among others. He has served as President of the North American Regional Science Council (2012–2013) and the Southern Regional Science Association (2011–2012), and was named a Fellow of the latter in 2016. His policy contributions include testimony before governmental committees and media engagements on economic development. Labs/Teams: Director, Division of Research Editorial roles at Journal of Regional Science and Review of Regional Studies

Indranil Mukhopadhyayمشاهده پروفایل

استاد

• Biostatistics
• Statistical Genetics
• Genomics
• +۳ مورد دیگر

Indranil Mukhopadhyay serves as a Professor in the Department of Statistics at the University of Nebraska-Lincoln, where he conducts cutting-edge research at the intersection of statistics, genomics, and public health. His work bridges theoretical statistical methodology with urgent real-world health challenges, particularly in infectious disease modeling and genomic data analysis. His primary research interests encompass biostatistical methodology development for multi-omics integration, epidemiological modeling of infectious diseases (notably HIV/AIDS and COVID-19), and statistical genetics for complex trait analysis. He has pioneered robust computational frameworks for handling high-dimensional biological data, with emphasis on isoform quantification, gene expression clustering, and genetic association studies in diverse populations. Analysis of his recent publications reveals a strong trajectory toward public health applications , where statistical models directly inform pandemic response strategies and disease control policies. His work consistently demonstrates innovation in adapting mathematical frameworks (e.g., critical community size theory) to contemporary health crises, while maintaining rigorous methodological foundations in sequential estimation and robust statistics. No scientific awards were documented in the provided materials. Information regarding student advising, research grants, or laboratory infrastructure was not available in the source text. His publication record suggests active collaboration with medical researchers, particularly in studies involving Indian population cohorts and rare genetic disorders. No details about specific research laboratories or collaborative teams were provided in the available documentation.

Hironori Washizakiمشاهده پروفایل

استاد

• Systems Engineering
• Software Engineering
• Machine Learning
• +۳ مورد دیگر

Hironori Washizaki is a Professor at Waseda University 's School of Fundamental Science and Engineering and a Visiting Professor at the National Institute of Informatics. He serves as IEEE Computer Society 2025 President and has led initiatives in software engineering, ML design patterns, and IoT systems. His work bridges academia and industry through roles at SYSTEM INFORMATION CO.,LTD. and eXmotion Co., LTD. Research Interests: His work spans software engineering, quality assurance, ML/IoT design patterns, and education innovation. He leads the SmartSE professional education program and standardizes software engineering bodies of knowledge through ISO/IEC/JTC1/SC7/WG20 . Scientific Awards: Golden Core Member (IEEE CS) Spirit of Computer Society Award KDDI Foundation Award Science and Technology Award, MEXT Best Paper Awards at ICSE, CSEE&T, and IWESEP Leadership & Grants: He has secured major grants (JSPS, MEXT) and held editorial roles at IEEE Transactions on Emerging Topics in Computing, IJSEKE, and IEICE journals. As IEEE CS Japan Chapter Chair and SEMAT Japan Chapter Chair , he fosters international collaborations. Labs & Teams: He leads the Global Software Engineering Laboratory at Waseda, focusing on traceability, reuse, and quality. This lab drives projects like ProMeTA (program metamodel taxonomy) and Trace ANY (software maintenance metrics).