جست‌وجوی استاد و پژوهشگر

Jeanne S. Hillمشاهده پروفایل

مدرس ارشد

• Statistical Education
• Probability Distributions
• Engineering Applications
• +۳ مورد دیگر

Dr. Jeanne S. Hill is a Senior Lecturer in the Department of Statistical Science at Baylor University and serves as the Undergraduate Program Director. She holds a Ph.D. in Statistics from the University of Missouri-Rolla (now Missouri University of Science and Technology), an M.S. in Mathematics from Arkansas State University, and dual B.S. degrees in Physics and Mathematics from Arkansas State University and Northwestern State University. Her research focuses on selection procedures for probability distributions with engineering applications and promoting statistical education at all levels, including undergraduate research opportunities. She has advised numerous undergraduate majors and directed capstone projects. Her work also extends to interdisciplinary areas like healthcare policy analysis, as seen in her 2015 study on hospitalist use. Married to David Ryden of Baylor’s Mathematics Department, she has three children. Education: Ph.D., Statistics (Missouri S&T, 1998); M.S., Mathematics (Arkansas State, 19??); B.S., Physics & Mathematics (Arkansas State/Northwestern State) Her research interests emphasize statistical selection methods, reliability engineering, and educational outreach. Recent publications span engineering reliability analysis and healthcare policy, demonstrating her interdisciplinary impact. As a dedicated educator, she advocates for expanding undergraduate research within Baylor’s statistical programs. Professional activities include faculty roles at Oklahoma State University (1998–2001) and Tulane University before joining Baylor in 2002. She actively contributes to academic advising and curriculum development.

Brady Coxمشاهده پروفایل

استاد

• Geotechnical Earthquake Engineering
• Subsurface Imaging
• Soil Dynamics
• +۲ مورد دیگر

Dr. Brady Cox is a Professor in Civil and Environmental Engineering at Utah State University, with previous appointments at University of Texas and University of Arkansas. He holds a Ph.D. in Geotechnical Engineering from University of Texas (2006). Research specializes in geotechnical earthquake engineering, subsurface imaging, and in-situ site characterization for seismic design. Teaching includes foundation design, soil mechanics, soil/rock dynamics, and geotechnical earthquake engineering. Research focuses on experimental field testing combined with computational analyses for subsurface imaging, with applications in nuclear facilities, transportation infrastructure, and earthquake reconnaissance. Major awards include Presidential Early Career Award for Scientists and Engineers (2012), ASTM Geotechnical Testing Journal Award (2019), and ISSMGE Young Researcher Award (2017) Directs field deployments for seismic characterization globally, including Ecuador, Haiti, Japan, New Zealand, Peru, and Turkey. Manages NHERI@UTexas facility with large-scale mobile shakers. Recent publications advance surface wave inversion methods, uncertainty quantification, and 3D ambient noise tomography.

Gabriel Piconeمشاهده پروفایل

استاد

• Health Economics
• Applied Econometrics
• Development Economics
• +۳ مورد دیگر

Gabriel Picone is a Professor of Economics and Chair of the Department of Economics at the University of South Florida , where he leads academic initiatives in health economics, applied econometrics, and development economics focusing on Sub-Saharan Africa. His career spans decades of research and teaching excellence. Academic Background: Ph.D. in Economics, Vanderbilt University (1993) Research Focus: Health Economics: Analyzing disease prevention, healthcare utilization, and policy impacts Applied Econometrics: Developing statistical models for health and economic outcomes Sub-Saharan Africa Development: Investigating economic growth, health interventions, and demographic trends Industrial Organization: Studying retail market behaviors and alcohol industry economics Publication Trends: Over 25 years, his work spans diverse fields including malaria prevention economics, healthcare policy analysis, econometric methodology, alcohol consumption patterns, and pharmaceutical market regulation. Geographic focus remains strongly on Sub-Saharan Africa with parallel research in U.S. and EU health systems.

Panos Trahaniasمشاهده پروفایل

استاد

• Robotics
• Computer Vision
• Humanoid Robots
• +۱ مورد دیگر

Panos Trahanias is Professor and Vice Chair in the Department of Computer Science at the University of Crete, and heads the Computational Vision and Robotics Laboratory (CVRL) at Foundation for Research and Technology - Hellas (FORTH). His research bridges computational vision, robotics, and embedded systems, with specific focus on humanoid robot navigation, real-time SLAM implementations, and adaptive control systems. Recent investigations include developing climbing quadruped robots, robust grip-lifting mechanisms, and probabilistic contact estimation methods for dynamically challenging terrains. Medical applications feature prominently through neural network approaches for ventilator waveform analysis in critical care settings. Hardware innovation is demonstrated through FPGA-accelerated visual SLAM architectures and reconfigurable embedded systems designed for resource-constrained robotic platforms. His work consistently advances the integration of probabilistic methods, deep learning, and adaptive control in autonomous systems.

Keren Liمشاهده پروفایل

استادیار

• Distributed Learning
• Federated Learning
• Deep Learning
• +۷ مورد دیگر

Keren Li is an Assistant Professor in the Department of Mathematics at the University of Alabama at Birmingham (UAB), affiliated with the College of Arts and Sciences. She holds a PhD in Statistics from the University of Illinois at Chicago (2018), an MS in Mathematics from Louisiana State University (2004), and a BA in Mathematics from Nankai University (2001). Before joining UAB in 2022, she served as an Associate Scientist at UAB's Informatics Institute (2023–2024) and a Postdoctoral Fellow at Northwestern University’s NSF-Simons Center for Quantitative Biology and Department of Statistics and Data Science (2018–2022). Her research focuses on distributed learning, federated learning, deep learning, bioinformatics, and financial mathematics. Key projects include developing tools like DNAcycP (predicting DNA cyclizability) and RiboDiPA (analyzing ribosome profiling data). She also explores statistical methods for optimal design and generalized linear models. Her work bridges computational methods and real-world applications, with contributions to genomics, energy networks, and financial modeling. Her lab ( klilab ) emphasizes interdisciplinary collaboration and innovative algorithm development.

Florian Huberمشاهده پروفایل

استاد

• Bayesian Econometrics
• Macroeconomics
• State Space Modeling
• +۳ مورد دیگر

Florian Huber is a Professor of Economics and Vice-Head of the Department of Economics at the University of Salzburg. His research focuses on Bayesian macroeconometrics, particularly large-scale non-linear multivariate time series modeling. He has published in top journals such as the Journal of Econometrics and the Journal of Applied Econometrics. His work integrates machine learning and nonlinear methods to analyze macroeconomic dynamics and uncertainty. Huber serves as a Scientific Consultant to the Oesterreichische Nationalbank (OeNB), European Central Bank (ECB), and European Commission. He holds roles as Associate Editor of Macroeconomic Dynamics, Senior Scientist at the International Institute for Applied Systems Analysis (IIASA), and Research Fellow of Bocconi University’s Baffi Center. His accolades include the 2024 Kurt-Zopf-Förderpreis and Fellow status in the Society for Economic Measurement. Research interests span Bayesian econometrics, state space modeling, forecasting, and financial spillovers. His recent work addresses topics like growth-at-risk, nonlinear VAR models, and real-time inflation forecasting. Huber’s contributions bridge theoretical econometrics with policy-relevant analysis, emphasizing the integration of big data and structural models.

Ala'a Al-Habashnaمشاهده پروفایل

استاد مدعو

• Wireless Communication Networks
• 5G/6G Technologies
• Machine Learning Applications
• +۵ مورد دیگر

Ala'a Al-Habashna is an Adjunct Professor at Carleton University's School of Computer Science within the Faculty of Engineering and Design. He holds a PhD from Carleton University and focuses on advanced wireless communication systems, 5G/6G networks, machine learning applications, and discrete-event simulation. His research integrates AI-driven solutions for network optimization, spectrum management, and smart urban infrastructure analysis. Education: PhD in Computer Science, Carleton University Research Interests: 5G/6G Networks, Machine Learning for Communications, Cognitive Radio Systems, IoT Integration, and Urban Modeling via Computer Vision Focus on resource allocation algorithms, channel modeling, and AI-driven network architectures Key Article Trends: Recent work emphasizes AI integration in next-gen networks (e.g., RIS-assisted MIMO, GenAI-6G), 5G energy efficiency, and urban analytics using street-view imagery. Earlier contributions include DEVS-based simulation frameworks for fire modeling and D2D video streaming optimization. Collaborations & Funding: Active partnerships include Ericsson Canada for projects like Channel Reconstruction for LTE/NR and Spectrum Sharing with Machine Learning . A funded PhD position is available in Wireless Communication and 5G Networks requiring expertise in Mathematical Optimization. Labs & Teams: Engaged in Ericsson-Carleton Partnership initiatives and leads interdisciplinary teams addressing 6G challenges. Research leverages Carleton's advanced wireless and AI facilities.

Derya Aksarayمشاهده پروفایل

استادیار

• Robotics
• Control Theory
• Formal Methods
• +۴ مورد دیگر

Derya Aksaray is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University, where she directs the Dependable Autonomy Lab (DAL). She holds a PhD in Aerospace Engineering from Georgia Tech (2014) and has prior roles as an Assistant Professor at the University of Minnesota (2018-2022), and postdoctoral positions at MIT CSAIL (2016-2017) and Boston University (2014-2016). Her research focuses on control theory, formal methods, and machine learning for robotics and autonomous systems, particularly in uncertain and dynamic environments. Education: PhD, Aerospace Engineering, Georgia Institute of Technology (2014) MS, Aerospace Engineering, Georgia Institute of Technology (2011) BS, Aerospace Engineering, Middle East Technical University (2008) Research Interests: Formal methods for autonomous systems Reinforcement learning with temporal logic constraints Multi-agent coordination and distributed planning Resilient control for robotics and aerospace systems Energy-aware planning for UAVs and heterogeneous systems Lab Activities: The Dependable Autonomy Lab develops theory and algorithms for achieving reliable autonomous robot behaviors, with experimental validation on ground and aerial robots. Current projects include resilient planning under uncertainty, distributed multi-agent systems, and reinforcement learning with formal guarantees. Advising: Prof. Aksaray supervises graduate students in PhD and MS programs, focusing on control theory, formal methods, and robotics applications. Former advisees include Ali Tevfik Buyukkocak (PhD, 2024) and Ryan Peterson (MS, 2020). Professional Affiliations: Member of the American Institute of Aeronautics and Astronautics (AIAA) and Institute of Electrical and Electronics Engineers (IEEE).

Peng Zhangمشاهده پروفایل

استاد

• Power and Energy
• Quantum-Engineered Power Grids
• AI-Enabled Power Grids
• +۷ مورد دیگر

Peng Zhang is a tenured Full Professor of Electrical and Computer Engineering and a SUNY Empire Innovation Professor at Stony Brook University. He also holds affiliate professorships in Computer Science and Applied Mathematics & Statistics. His research focuses on cyber-physical grid resilience, including quantum-engineered grids, AI-enabled systems, and cybersecurity. He leads the Power Lab, developing technologies like software-defined grids and programmable microgrids. PhD: Electrical Engineering, University of British Columbia (Canada) Masters: Tsinghua University Bachelor's: Shandong University Research interests span quantum grids, AI-driven grid optimization, microgrid stability, and formal methods for resilience. Key projects include NSF-funded initiatives on resilient networked microgrids and quantum-security frameworks. Recent publications emphasize quantum computing applications in power systems, cybersecurity solutions, and fault management. Awards include the 2018 IEEE Technological Innovation Award and Excellence in Energy Award. Advises numerous PhD students and leads labs such as the Quantum Grids Lab and AI-Grid Lab. Active in grants and industry collaborations, including with Eversource Energy and DOE projects.

Kim Nicholsمشاهده پروفایل

استاد آموزشی

• Primatology
• Primate Paleontology
• Functional Anatomy
• +۳ مورد دیگر

Kim Nichols is an Associate Teaching Professor in the Department of Anthropology and Geography at Colorado State University , part of the College of Liberal Arts. Her academic focus spans Primatology, Primate Paleontology, and Functional Anatomy, with research emphasizing nonhuman primate skeletal variation and Eocene primate paleocommunities. She advocates strongly for undergraduate research opportunities, supervising numerous student projects that contribute to paleontological and anthropological studies. Education: M.A. in Anthropology, University of Colorado at Boulder (focus on Howling Monkey locomotion in Costa Rica) B.A. in Anthropology, University of California at Santa Cruz (nonhuman primate anatomy, forensic anthropology, archaeology) Research Interests: Nonhuman primate skeletal variation in captive/wild populations Functional anatomy of primates Early Eocene primate paleoecology and distribution Paleontological field methods and fossil collection Teaching & Fieldwork: Leads ANTH 470 Paleontology Field School in Wyoming, emphasizing hands-on fossil discovery and analysis. The course has collected over 800 mammalian fossils, including 100+ primate specimens since its inception. Advising & Outreach: Mentored students in CURC presentations and professional conferences (Society of Vertebrate Paleontology, GSA). Advocates for integrating field research into undergraduate education to enhance scientific literacy. Labs/Teams: Core member of the Paleontology Field School Lab, managing fossil collections from the Bighorn Basin. Collaborates with Dr. Tom Bown on Eocene primate studies.

Natalya Pya Arnqvistمشاهده پروفایل

دانشیار

• Statistical Regression Modelling
• Functional Data Analysis
• Shape Preserving Smoothing
• +۷ مورد دیگر

Natalya Pya Arnqvist is an Associate Professor in Mathematical Statistics at Umeå University, Sweden. She is affiliated with the Department of Mathematics and Mathematical Statistics and has active roles in research groups focused on Functional Data Analysis, Semiparametric Regression, and Statistical Learning for Spatio-Temporal Data. Her career includes prior positions at Nazarbayev University (2015-2020), University of Bath (2011-2015), and KIMEP University (2000-2005). Education : PhD in Statistics (University of Bath, UK, 2007-2010), CSc in Physical and Mathematical Sciences (Institute for Mathematics, Kazakhstan, 2000-2005). Her research centers on statistical regression modelling and functional data analysis , with significant contributions to shape constrained additive models (SCAMs) and model-based functional clustering . She has developed R packages such as scam , fdaMocca , and nilde for these methodologies. Recent publications highlight applications in applied demography , defect detection , and nonlinear state space modeling , reflecting her focus on bridging statistical theory with industrial and ecological challenges. She teaches undergraduate and graduate courses in probability, regression, and statistical learning.

Tasos Christofidesمشاهده پروفایل

استاد

• Probability Inequalities
• Demimartingales
• Stochastic Orders
• +۲ مورد دیگر

Tasos Christofides is a Professor in the Department of Mathematics and Statistics at the University of Cyprus, School of Natural and Applied Sciences. He has been serving in this position since 2004 after previously holding the rank of Associate Professor from 1991 to 2004. Prior to his appointment at the University of Cyprus, he was an Assistant Professor at the State University of New York at Binghamton from 1987 to 1991. His educational background includes a Ph.D. (1987) and MSE (1985) in Mathematical Sciences from The Johns Hopkins University, USA, and a Mathematics degree (1983) from the University of Athens, Greece. Professor Christofides specializes in Probability Inequalities, Demimartingales, Stochastic Orders, Survey Methodology, and Indirect Questioning Techniques. His research primarily focuses on theoretical statistics with applications to survey methodology, particularly in developing techniques for handling sensitive questions while preserving respondent privacy. His work bridges probability theory with practical survey design, making significant contributions to both theoretical foundations and applied methodologies. His publication record demonstrates consistent contributions to statistical theory, with a particular emphasis on U-statistics, demimartingales, and randomized response techniques. The trajectory of his research shows progression from foundational work on U-statistics and probability inequalities in the early career to more applied survey methodology techniques in later years, while maintaining strong theoretical underpinnings. Professor Christofides serves as Associate Editor for several prestigious statistical journals including Communications in Statistics-Theory and Methods, Communications in Statistics-Computation and Simulation, Journal of Statistical Theory and Practice, and Statistics and Probability Letters. His editorial service reflects his standing in the statistical community and his expertise across multiple domains of statistical theory and methodology. While specific grant information is not provided in the available text, his sustained research output and editorial positions indicate active engagement with the research community.

• Reinforcement Learning
• Robust Optimization
• Machine Learning
• +۱۰ مورد دیگر

Fei Miao is a Pratt & Whitney Associate Professor at the School of Computing, University of Connecticut, and a courtesy faculty member of the Department of Electrical & Computer Engineering. She serves as Director of the Miao Embodied AI Lab and is affiliated with the Institute for Advanced Systems Engineering. Previously, she was a postdoc researcher at the GRASP Lab and PRECISE Lab with Professors George J. Pappas and Daniel D. Lee at the University of Pennsylvania. Dr. Miao received her PhD in Electrical and Systems Engineering from the University of Pennsylvania in 2016, where she also earned a dual Master's degree in Statistics from the Wharton School. She completed her undergraduate studies at Shanghai Jiao Tong University, earning a Bachelor's degree in Automation with a minor in Finance in 2010. Her research focuses on developing the foundations for the science of Embodied AI, with emphasis on assuring safety, efficiency, robustness, and security of cyber-physical systems through the integration of learning, optimization, and control. Her technical expertise spans multi-agent reinforcement learning, robust optimization, uncertainty quantification, control theory, and game theory. These methods are applied to connected and autonomous vehicles, intelligent transportation systems, transportation decarbonization, smart cities, and power networks. Her work involves both theoretical development and practical implementation, including system modeling, theoretical analysis, algorithmic design, and experimental validation using real urban transportation data, simulators, and small-scale autonomous vehicles. Dr. Miao's publication record reveals a strong focus on robustness in AI systems for transportation applications, with recent work emphasizing uncertainty quantification, safety guarantees, and multi-agent coordination. Her research demonstrates a clear trajectory from foundational theoretical work to practical implementations in real-world transportation systems. Her notable awards include the prestigious NSF CAREER Award (2021) for "Distributionally Robust Learning, Control, and Benefits Analysis of Information Sharing for Connected and Autonomous Vehicles," a Best Paper Award at ICCPS'21 for "DeResolver: A Decentralized Negotiation and Conflict Resolution Framework for Smart City Services," and the "Charles Hallac and Sarah Keil Wolf Award for Best Doctoral Dissertation" during her PhD studies. Dr. Miao has secured significant research funding, including a $509,573 NSF CAREER Award (2021-2026) and a $2.3 million NSF collaborative grant as PI of UConn (2020-2023). She has also received multiple NSF grants for projects related to electric vehicle fleets, vehicular sensing, and control for smart city systems. She actively collaborates with researchers across institutions and has given talks at leading universities and industry research labs including CMU, Microsoft Research, Northeastern, Caltech, UCLA, USC, UCSD, Facebook FAIR, Lawrence Berkeley National Lab, UC Berkeley, Nvidia, Stanford, Princeton University, Columbia University, Waymo, and New York University.

• Galaxy Formation and Evolution
• Black Holes
• Active Galactic Nuclei (AGN)
• +۶ مورد دیگر

Erin Hicks, Ph.D., is Chair and Professor in the Department of Physics & Astronomy at the University of Alaska. She holds a Ph.D. in Astronomy & Astrophysics from the University of California, Los Angeles (2006), an M.S. in Astronomy & Astrophysics (2001), and a B.S. in Physics with minors in Astronomy and Mathematics from Washington State University (1999). Education: Ph.D., Astronomy & Astrophysics, UCLA, 2006 M.S., Astronomy & Astrophysics, UCLA, 2001 B.S., Physics, Washington State University, 1999 Her research focuses on galaxy formation and evolution, particularly the roles of black holes and active galactic nuclei (AGN) in shaping galaxy dynamics. Key interests include AGN feedback mechanisms, high-redshift galaxy properties, and observational techniques like adaptive optics and integral field spectroscopy. Her work integrates n-body simulations to model galaxy evolution. Publications highlight studies on molecular inflows/outflows in AGN, kinematics of high-redshift galaxies, and the interplay between star formation and AGN activity. Recent work emphasizes spatially resolved observations of gas dynamics in distant galaxies. No scientific awards were explicitly mentioned. She advises no listed students and has no noted lab affiliations. Career highlights include postdoctoral fellowships at the University of Washington and the Max Planck Institute for Extraterrestrial Physics.

George Korresمشاهده پروفایل

استاد

• Power System Analysis
• Power System Operations
• Power Systems Protection
• +۲ مورد دیگر

Professor George Korres specializes in Electric Power Engineering at the National Technical University of Athens. His research encompasses power system analysis, protection schemes, and industrial control systems. Teaching responsibilities include courses on: Supervision/Management of Energy Systems Energy Control Centers Power System Protection Recent research focuses on advanced state estimation techniques for modern power grids, particularly hybrid measurement systems combining SCADA and PMU data. Publications demonstrate applications in transmission networks, HVDC systems, distribution grids with renewable integration, and adaptive protection for island systems.