جست‌وجوی استاد و پژوهشگر

Jacob Motaمشاهده پروفایل

استادیار

• Muscle Function Assessment
• Neuromuscular Adaptations
• Occupational Health (Firefighters/Law Enforcement)
• +۴ مورد دیگر

Jacob Mota, Ph.D. , is an Assistant Professor in the Department of Kinesiology & Sport Management at Texas Tech University. His research focuses on neuromuscular adaptations and muscle function assessment across diverse populations including firefighters, law enforcement officers, and athletes. Ph.D. in Human Movement Science (2020), University of North Carolina Chapel Hill School of Medicine M.S. in Kinesiology (2016), Texas Tech University B.S. in Exercise and Sport Sciences (2014), Texas Tech University Dr. Mota's work examines the relationship between chronic health conditions and musculoskeletal injury risk in occupational athletes, with emphasis on resistance training adaptations and muscle quality analysis. His Neuromuscular and Occupational Performance Laboratory develops evidence-based strategies for injury prevention and performance optimization. Recent publications analyze firefighter health standards, muscle asymmetry impacts on occupational performance, and technological advancements in muscle assessment. His research integrates exercise physiology, biomechanics, and public safety health metrics. Outstanding Mentorship of Undergraduate Students in Research – University of Alabama (2022) Apple Polishing Award – TTU Mortar Board (2023) Dr. Mota teaches courses in applied exercise physiology and advanced strength conditioning, contributing to Texas Tech's Kinesiology undergraduate and graduate programs.

• Brain-Computer Interfaces
• Electroencephalography (EEG)
• Biomedical Engineering
• +۷ مورد دیگر

Jane E. Huggins is a Research Professor in the Department of Biomedical Engineering and Physical Medicine and Rehabilitation at the University of Michigan. Her work focuses on developing EEG-based brain-computer interfaces (BCIs) into clinical tools for individuals with physical impairments, addressing challenges like signal processing, task design, and in-home technical support. University of Michigan Appointments: Biomedical Engineering (2024–Present), Physical Medicine and Rehabilitation (2024–Present) Research Interests: Jane’s research bridges BCIs with augmentative and alternative communication (AAC) systems, emphasizing accessibility, commercial readiness, and integration with established clinical infrastructure. Her projects explore event-related potentials (P300), neural prostheses, and user-centered design for equitable healthcare technologies. Grant Funding Highlights: She has secured major grants from NIH, NSF, General Motors, and Cerebral Palsy Alliance Research Foundation to advance BCI applications in accessibility, autonomous vehicles, and lifelong assistive technology deployment. Professional Contributions: Jane actively presents at international BCI conferences and collaborates with the UMDBI Lab on clinical trials and software innovations for BCI systems.

Najmaddin Akhundovمشاهده پروفایل

استادیار

• Integer Programming
• Algorithm Development
• Simulation-based Optimization
• +۵ مورد دیگر

Najmaddin Akhundov is an Assistant Professor in the Decision Sciences and Marketing Department at the Robert B. Willumstad School of Business, Adelphi University. His expertise lies in operations research, with a focus on integer programming, stochastic optimization, and simulation-based methods applied to scheduling, logistics, energy systems, and risk management. Education: Ph.D., Industrial and Systems Engineering, University of Tennessee (2022) M.S., Systems Design Engineering, University of Waterloo (2015) B.S., Industrial Engineering, Baku Engineering University (2011) Research Interests: Dr. Akhundov’s research spans both methodological and applied domains. Methodologically, he advances integer programming , algorithmic development , simulation-based optimization , and stochastic programming . Application-wise, he tackles complex scheduling problems (staff, maintenance, power generators, production), reverse and last-mile logistics, evacuation planning, sustainable port management, and risk-informed maintenance planning. Recent publications (2019-2024) reveal a consistent trajectory toward integrating advanced optimization techniques with real-world operational challenges. Studies range from exploiting symmetry in job sequencing to configuring last-mile distribution networks, pricing risk in energy markets, and optimizing surveillance strategies against invasive species. Collectively, these works highlight a commitment to bridging theory and practice in operations research. Awards & Honors: INFORMS ENRE Best Publication Award in Natural Resources (2022) Harvey J. Greenberg Research Award – Honorable Mention, INFORMS Computing Society (2022) Graduate Fellowship Award, University of Tennessee (2018-2022) Best Graduate Presentation, Dana Knox Student Research Showcase (2018) Study Abroad Fellowship, Ministry of Education of Azerbaijan (2013-2015) Merit-Based Scholarships from Azercell Telecom and Baku Engineering University Teaching & Mentoring: At Adelphi, Dr. Akhundov teaches courses such as Management of Production/Operations and Statistical Methods, having previously taught Applied Operations Research, Optimization Techniques, and Mathematical Programming with MATLAB. While no specific advisees are listed in the provided text, his active research program and course offerings indicate ongoing engagement with both undergraduate and graduate students. Laboratories & Teams: While no dedicated laboratory is explicitly mentioned, his collaborative work with researchers from the University of Tennessee, University of Waterloo, and multiple international partners suggests participation in interdisciplinary research teams focused on optimization and logistics.

Yuhan Dingمشاهده پروفایل

عضو هیئت علمی

• Applied Mathematics
• Data Science
• Numerical Analysis
• +۳ مورد دیگر

Yuhan Ding is an Associate Teaching Professor of Applied Mathematics and Program Director of the Master of Data Science program at Illinois Institute of Technology's College of Computing. Their research focuses on numerical analysis, adaptive algorithms, and computational methods. Ding has contributed to the development of adaptive approximation techniques and integration libraries like GAIL, emphasizing guaranteed error control and algorithmic efficiency. Education details are not explicitly provided in the text, but their work aligns with advanced computational mathematics and data science education. Research interests include multivariate approximation, algorithm design, and mathematical modeling. Advising and grant details are not specified here. The GAIL library demonstrates expertise in creating robust computational tools for scientific applications.

• Auditory Neuroscience
• Hearing Science
• Speech Perception in Noise
• +۲ مورد دیگر

Skyler G. Jennings, Au.D., Ph.D., serves as an Adjunct Professor in the Department of Surgery at the University of Utah. His academic work focuses on auditory neuroscience and audiology, specifically investigating speech perception mechanisms in noisy environments and the role of the medial olivocochlear reflex in auditory adaptation. Dr. Jennings completed his undergraduate education at the University of Utah and Utah State University, followed by graduate studies at Purdue University where he earned his master's degree, clinical doctorate in Audiology (Au.D.), and Ph.D. His research program centers on understanding how the auditory system calibrates to changing acoustic soundscapes, with particular emphasis on why individuals with cochlear hearing impairment struggle to adapt due to compromised outer hair cell function affecting efferent feedback mechanisms. Analysis of his 14 publications (2009-2019) reveals consistent investigation into auditory processing in noise, cochlear mechanics, and hearing loss effects. Key research themes include amplitude modulation detection, overshoot phenomena, auditory filter tuning, and computational modeling of individual differences. His work demonstrates how notched-noise precursors improve low-frequency modulation detection and reveals sharper cochlear tuning in musicians, with significant implications for hearing assistive technologies. Dr. Jennings has contributed to methodological advancements in auditory research through the development of the PsyAcoustX MATLAB toolbox for psychoacoustic experimentation. His collaborative research with investigators including Bidelman, Strickland, and Dubno spans auditory neuroscience, computational modeling, and clinical audiology applications.

Sarah N. Giddingsمشاهده پروفایل

استادیار

• Physical Oceanography
• Environmental Fluid Dynamics
• Coastal Oceanography
• +۷ مورد دیگر

Sarah N. Giddings is an Assistant Professor in the Integrated Oceanography Division at Scripps Institution of Oceanography, University of California, San Diego (UCSD). She joined the faculty in January 2014 and leads the Environmental Fluids and Coastal Oceanography Laboratory, conducting research on coastal and estuarine dynamics, mixing, and transport processes. Her research interests lie at the intersection of physical oceanography and environmental fluid dynamics, focusing on coastal circulation, estuarine exchange flows, saltwater intrusion, wave-current interactions, and the impacts of climate variability on coastal systems. She employs field observations, numerical modeling, and laboratory techniques to investigate how natural and anthropogenic factors influence coastal water quality and ecosystem health. Her recent publications reveal a strong focus on coastal hydrodynamics, with studies on infragravity waves, estuarine residence time, river plume mixing, and harmful algal bloom transport. Her work spans diverse regions including Southern California, the Salish Sea, San Diego Bay, and the Caribbean. Stanford Society of Women Engineers Teaching Excellence Award, 2010 NSF Ocean Science Postdoctoral Research Fellowship (starting January 2013) Dr. Giddings has been actively involved in teaching and mentoring, offering graduate courses in fluid mechanics, MATLAB, and estuarine processes. She has also contributed to numerous outreach initiatives, including public science events, K–12 education programs, and museum exhibit development. Her laboratory supports a team of researchers investigating pressing coastal environmental challenges.

Victor Chernozhukovمشاهده پروفایل

استاد

• High-Dimensional Statistics
• Econometrics
• Quantile Regression
• +۳ مورد دیگر

Victor Chernozhukov is a Professor at the Department of Economics and Center for Statistics at the Massachusetts Institute of Technology (MIT) . He also holds international fellowships at the University College London's CEMMAP and is a Professor by Courtesy at the New Economic School in Russia. His research spans econometrics, high-dimensional statistics, quantile regression, and causal inference. Education: Ph.D. in Economics from Stanford University (2000), M.S. in Statistics from University of Illinois at Urbana-Champaign (1997) His work focuses on developing statistical methods for high-dimensional data, including central limit theorems , post-selection inference , and quantile regression . He has contributed to partial identification , Bayesian inference , and extreme value analysis , with applications to economic policy evaluation. Recent publications emphasize high-dimensional causal inference , adaptive confidence bands , and set estimation . His research has been supported by the National Science Foundation and recognized with the Alfred P. Sloan Research Fellowship . Scientific Awards: Alfred P. Sloan Research Fellowship (2005-2007) Castle-Krob Career Development Chair (2004-2007) Grants include long-term support from the National Science Foundation since 2001 and software development collaborations for Stata and MATLAB implementations.

Brian Borchersمشاهده پروفایل

استاد

• Optimization
• Inverse Problems
• Geophysical Inverse Problems
• +۳ مورد دیگر

Roles and Affiliations : Professor of Mathematics at New Mexico Tech. Member of the Mathematics Department since at least 1992, actively involved in teaching and research. Maintains a research-focused website with links to publications, projects, and codes. Education : BS in Computer Science, MS and PhD in Mathematics from Rensselaer Polytechnic Institute. Research Interests : Specializes in optimization and inverse problems, including linear/nonlinear programming, geophysical inverse problems, and applications in hydrology and geophysics. Co-authored a widely used textbook Parameter Estimation and Inverse Problems (3rd ed., 2018). Active in developing computational tools like CSDP for semidefinite programming and CRONUScalc for cosmogenic nuclide dating. Publications : Over 50 peer-reviewed articles in journals such as Computational Optimization and Applications , Soil Science Society of America Journal , and International Journal of Remote Sensing . Focus areas include optimization algorithms, geophysical modeling, and remote sensing applications. Consulting and Grants : Available as a consultant for numerical analysis and inverse problems. Supervised projects involving data assimilation, convex optimization, and compressive sensing. Mentored students on funded research projects. Labs/Teams : Collaborates with interdisciplinary teams in geophysics (e.g., Rick Aster, Cliff Thurber) and soil science (Jan Hendrickx). Involved in sensor test facilities for landmine detection and environmental monitoring.

Richard Davisمشاهده پروفایل

استاد

• Carbon Capture and Conversion
• Process Modeling and Simulation
• Solar Thermal Chemistry
• +۵ مورد دیگر

Richard Davis serves as Professor and Department Head of Chemical Engineering at the University of Minnesota Duluth's Swenson College of Science and Engineering. His research spans carbon capture technologies, solar thermal chemistry, and metallurgical process modeling. His educational background includes a Post Doctoral Research Fellowship and Ph.D. in Chemical Engineering from UCSB, and a B.S. in Chemical Engineering from BYU. Research interests focus on engineering mathematics, separations, process modeling for environmental management, and carbon capture systems. Publication analysis reveals strong emphasis on CO2 capture (35% of recent work), metallurgical processes (25%), and educational innovation (20%), with growing focus on graphene-based catalysts and computational methods. His work bridges fundamental research with practical engineering applications. UMD Jean G. Blehart Distinguished Teacher UMD Outstanding Advisor UCSB Outstanding Teacher Omega Chi Epsilon Honor Society Member Tau Beta Pi Engineering Honor Society As Department Head and SCSE ABET Coordinator, he leads curriculum development integrating computing and safety across chemical engineering programs. He advises SME, Tau Beta Pi, and Omega Chi Epsilon student chapters while serving on the Minnesota Minerals Coordinating Committee. His research connects with industry through process modeling for mining and metallurgical operations.

Michael G. Kayمشاهده پروفایل

دانشیار

• Logistics Network Design
• Metaheuristics
• Freight Transportation
• +۴ مورد دیگر

Michael G. Kay is an Associate Professor in the Edward P. Fitts Department of Industrial and Systems Engineering at North Carolina State University's College of Engineering. Since joining in 1992, he has served as Director of the Integrated Manufacturing Systems Engineering graduate program and as Co-Director of the Operations Research Program. His educational background includes a Ph.D. in Industrial Engineering from NC State University (1992), an MS in Industrial Engineering from the University of Florida (1984), and a BA in Economics from the University of Florida (1981). Kay's research focuses on logistics engineering, particularly the design of public logistics networks using driverless delivery vehicles. His work explores innovative solutions for freight transportation, warehousing, and production system design, with applications ranging from military logistics to sustainable supply chains. Key research areas include metaheuristic optimization, material handling systems, and multimodal transportation networks. Analysis of Kay's recent publications reveals a strong interdisciplinary focus spanning operations research, logistics engineering, and supply chain innovation. His work increasingly incorporates emerging technologies like blockchain and additive manufacturing to solve complex industrial problems. Research trends demonstrate consistent application of stochastic optimization methods to real-world challenges in transportation, manufacturing, and military logistics. Throughout his career, Kay has developed significant software tools including: Logjam (Julia package for logistics engineering) Matlog (Logistics Engineering Matlab Toolbox) Lgpy (Logistics Engineering Python Package) GAOT (Genetic Algorithm Optimization Toolbox)

Charles S. Peskinمشاهده پروفایل

استاد

• Immersed Boundary Method
• Mathematical Physiology (Heart, Neuro)
• Partial Differential Equations in Biology
• +۷ مورد دیگر

Charles S. Peskin is a Professor of Mathematics at the Courant Institute of Mathematical Sciences, New York University. He specializes in mathematical modeling and simulation of biological systems, particularly cardiovascular physiology and neurophysiology. His work focuses on the Immersed Boundary Method, a computational framework for fluid-structure interaction problems. Peskin has authored influential textbooks such as Modeling and Simulation in Medicine and the Life Sciences (2nd ed., 2002) and developed simulation tools used in biomechanics research. His research spans mathematical biology, computational fluid dynamics, and stochastic processes in biological systems. He advises PhD students on interdisciplinary projects at the interface of mathematics and life sciences. Key contributions include modeling heart valve dynamics, neural signaling mechanisms, and biomolecular motor systems. Affiliations: Courant Institute, NYU Research: Immersed Boundary Method, Cardiac Mechanics, Neurophysiology Modeling Publications: 100+ articles, 2 books Teaching: Courses on PDEs in Biology, Biomolecular Motors, and Simulation Techniques Software: MATLAB programs for cardiovascular system simulations His work bridges applied mathematics with biomedical engineering, emphasizing computational methods for complex biological systems. Recent work includes studies on entropy principles in biology and rotary molecular motor mechanisms.

Sheng Xuمشاهده پروفایل

دانشیار

• Computational fluid dynamics
• Biological flows
• Supersonic turbulence
• +۲ مورد دیگر

Sheng Xu is Associate Professor at Southern Methodist University, specializing in computational fluid mechanics and aerodynamics. He holds a Ph.D. from Cornell University (2002) and previously worked at GE Energy on steam turbine aerodynamics, with postdoctoral research at Cornell and Princeton. Research develops computational methods for biological flows, supersonic turbulence, flow control, and insect/swimmer hydrodynamics. The immersed interface method—a core focus—models solids using singular forces and solves fluid flows with jump conditions. Current applications include dragonfly wing kinematics and particle collision dynamics. Publications in Journal of Computational Physics, SIAM Journal on Scientific Computing, and Journal of Fluid Mechanics address turbulent boundary layers, particle collisions, and biological flight mechanics. Recent work advances interface methods for non-smooth boundaries and manufactured solutions for code validation.

Stilian A. Stoevمشاهده پروفایل

استاد

• Stochastic Processes
• Time Series Analysis
• Long-range Dependence
• +۴ مورد دیگر

Stilian A. Stoev is a Professor of Statistics and serves as Bridge Program Director and Associate Director of the PhD Program at the University of Michigan's Department of Statistics. He holds a Ph.D. in Mathematics and Statistics from Boston University (2005) and an M.Sc. in Mathematics from Sofia University (1998). His research focuses on stochastic processes, long-range dependence, heavy-tailed distributions, and extreme-value theory with applications in finance, oceanography, and computer networks. He teaches courses such as Statistics 412 and has contributed to methodological advancements in statistical inference for stochastic processes. Research Interests: His work addresses time series analysis, limit theorems for Markov chains, long-range dependence modeling, and the estimation of Hurst parameters using wavelets. He explores applications in stochastic finance and communication networks, emphasizing both theoretical developments and practical implementations through computational tools like MATLAB and R. Grants & Advising: As a program director, he oversees academic and research initiatives. His advising responsibilities include mentoring PhD and Master's students in statistical theory and applications. No specific grants are detailed in the provided texts. Labs/Teams: No specific laboratory affiliations are mentioned, though his research involves interdisciplinary collaborations typical in statistical methodology development.

Boragan Aruobaمشاهده پروفایل

استاد

• Macroeconomics
• Monetary Economics
• Econometrics
• +۱ مورد دیگر

Boragan Aruoba is a Professor in the Department of Economics at the University of Maryland, where he has been a faculty member since 2004. He is a macroeconomist with theoretical and empirical interests in monetary economics, nonlinear macroeconomic dynamics, and econometric methods. His research has been supported by the National Science Foundation, and he serves as an editor for the Journal of Monetary Economics and as a Research Associate at the National Bureau of Economic Research (NBER). Education: PhD in Economics, University of Pennsylvania, 2004 Research Interests: Aruoba's work spans both theoretical and empirical macroeconomics. On the theoretical side, he studies nonlinearities in macroeconomic models, particularly dynamics near the zero lower bound (ZLB) on nominal interest rates. His empirical research focuses on data revisions, yield curve modeling, and real-time macroeconomic measurement. His tools include dynamic stochastic general equilibrium (DSGE) models, state-space methods, and machine learning techniques applied to policy shocks. Scientific Contributions: Developed the Aruoba-Diebold-Scotti Business Conditions Index , now produced by the Federal Reserve Bank of Philadelphia. Created Aruoba Term Structure of Inflation Expectations (ATSIX) , also implemented by the Philadelphia Fed. Co-developed GDPplus , a new measure of U.S. GDP growth, adopted by the Federal Reserve Bank of Philadelphia. Advising and Grants: Aruoba has advised students such as Pablo Cuba-Borda, now at the Federal Reserve Board of Governors. His research is supported by the National Science Foundation and he teaches macroeconomics, computational methods, and forecasting at both undergraduate and graduate levels. Affiliations and Roles: Editor, Journal of Monetary Economics Research Associate, NBER (Monetary Economics Program) Faculty member, Department of Economics, University of Maryland

Ling Liمشاهده پروفایل

استادیار

• Sustainable Bioenergy Systems
• Bioproducts
• Clean and Renewable Energy
• +۱۷ مورد دیگر

Ling Li is an Assistant Professor of Sustainable Bioenergy Systems at the School of Forest Resources, University of Maine, within the College of Natural Sciences, Forestry and Agriculture. Her work focuses on improving energy efficiency in the wood industry and advancing carbon-neutral bioproducts through innovative technologies and numerical modeling of hydrothermal behavior in wood and engineered wood products. She is actively engaged in research on biomass utilization, biochar applications for soil and environmental remediation, and sustainable bioenergy systems. Ph.D. in Forest Engineering, University of New Brunswick, Canada B.Sc. in Wood Science and Engineering, Nanjing Forestry University, China Dr. Li's research interests span bioproducts , clean and renewable energy , forestry-based biomass utilization , wood-water relations , and biochar applications for enhancing soil moisture and drought resilience in wild blueberries. She also explores the use of biochar for PFAS remediation. Her work integrates experimental and numerical methods to study the mechanical and thermal behavior of engineered wood products and mass timber systems. The recent publications reflect a strong trend in wood modification , moisture dynamics , structural performance of laminated timber , and energy-efficient drying technologies . Her studies increasingly incorporate biochar and membrane-based dehumidification systems for sustainable solutions in agriculture and industrial processing. Her scientific awards include: The Second Place of Wood Award, U.S. Forest Products Society (2014) First Prize, Student Poster Competition, Forest Products Society Eastern Canadian Section (2013) Forest Products Society Student Award, Eastern Canadian Section (2011) Dr. Li has advised graduate students and served on examination and advisory committees. Her research is supported by the Maine Agricultural and Forest Experiment Station and the McIntire-Stennis program (Project ME042205). She teaches courses such as SFR 450 – Processing of Biomaterials and SFR 455 – Bioenergy Sources, Systems, and Environmental Effects. She leads the Biomass Energy Laboratory at Nutting Hall and collaborates on interdisciplinary projects involving energy recovery systems for kiln drying processes. She is a member of the Society of Wood Science and Technology and serves as a reviewer for journals including International Journal of Heat and Mass Transfer , Construction and Building Materials , and Journal of Wood Science and Technology .