جست‌وجوی استاد و پژوهشگر

Arpan Guhaمشاهده پروفایل

استادیار

• Light and Human Health
• Wellness
• Cognition
• +۶ مورد دیگر

Arpan Guha is an Assistant Professor in the Department of Civil Engineering at the University of Cincinnati's College of Engineering & Applied Science. His research focuses on light's impact on human health and performance, advanced lighting metrology, and occupant-centric design strategies. He holds a Ph.D. in Architectural Engineering from the University of Nebraska-Lincoln (2020). Education: Ph.D. in Architectural Engineering, University of Nebraska-Lincoln, 2020 His research interests include high-dynamic-range imaging, low-resolution occupancy sensing, and 'occupant-first' design frameworks. He has received prestigious awards including the Edison-Price Fellowship (2022-2023) and the Robert J. Besal Scholarship (2018). Dr. Guha leads projects funded by the Nuckolls Fund for Lighting Education, focusing on human factors in lighting through mentorship and hands-on research at the Mt. Sinai Light and Health Research Center. His work spans interdisciplinary topics such as energy-efficient UVC systems in HVAC, smart grid communication protocols, and electric vehicle lifecycle analysis. He has developed novel AI-based frameworks for predicting thermal and visual comfort using infrared sensors and CNN algorithms. Awards: Edison-Price Fellow (2022-2023) Robert J. Besal Fund Scholarship (2018) Dr. Guha teaches undergraduate and graduate courses in architectural engineering and actively participates in professional organizations like the IALD International Association of Lighting Designers.

Larry Huمشاهده پروفایل

استادیار

• Sustainable Construction
• Construction Project Management
• Smart Construction Technologies
• +۳ مورد دیگر

Dr. Larry Hu is an Assistant Professor in the Department of Building and Construction Management at the School of Design and Built Environment, University of Canberra. His expertise lies in Sustainable Construction, Construction Project Management, and Smart Technologies. Previously, he taught at institutions including Deakin University, Edith Cowan University, and the University of Melbourne. He leads four major research projects, including environmental sustainability education programs and studies on skill shortages in construction sectors. His research focuses on optimizing construction processes through methodologies like Data Envelopment Analysis (DEA) and BIM technology. Key contributions include enhancing sustainability, reducing costs, and improving safety in construction projects. He holds certifications as a First-Class Constructor and Investment Project Management Professional in China, with 8 years of industry experience in roles such as construction management engineer and project consultant. Dr. Hu’s work aligns with UN Sustainable Development Goals, emphasizing cost reduction, carbon reduction, and value creation. His publications span journals like Buildings and Sustainability , covering topics from thermal comfort in urban buildings to smart city development. He actively contributes to academic governance as an editorial board member of Scientific Reports and Journal of Civil Engineering and Construction . Grants & Projects: Includes ACT Government-funded initiatives for digital building hubs and NSW government sustainability education programs. Professional Roles: Member of AUBEA, Australian Institute of Building (AIB), and topical advisory panels for Journal of Sustainability and Journal of Buildings .

Sudhir P. Mudurمشاهده پروفایل

استاد

• 3D Graphics
• 3D Reconstruction
• Virtual and Augmented Reality
• +۹ مورد دیگر

Sudhir P. Mudur is a Professor in the Department of Computer Science and Software Engineering at Concordia University, Montreal. He has held leadership roles including Chair of the Department and Visiting Professorships at institutions like the Central University of Florida, Ecole Minerales de Nantes, and Michigan State University. With over four decades of experience, Mudur's work spans fundamental and applied research, academic administration, and interdisciplinary collaboration in computer graphics, visualization, and cultural heritage. Education: Bachelor of Technology (B. Tech. Honours) in Electrical and Electronic Engineering, Indian Institute of Technology (IIT) Bombay, 1970. PhD in Computer Science, Tata Institute of Fundamental Research (TIFR), Mumbai, 1976. Research Interests: Mudur focuses on 3D graphics, virtual/augmented reality, computer vision, and cultural heritage documentation. His work includes realistic rendering techniques, geometric modeling, and applications in CAD/CAM, entertainment, and medical visualization. Recent projects involve 3D reconstruction from GIS data, interactive performance systems (ISSv2), and AR/VR for historical narratives. Key Contributions: Development of the Illimitable Space System (ISSv2) for real-time interactive applications in media arts. Advances in point cloud processing and shape reconstruction from unorganized data. Documentation of cultural heritage through virtual environments and 3D scanning. Research on global illumination and Monte Carlo methods in rendering. Leadership in academic administration, including roles at the National Centre for Software Technology (NCST) in India. Awards and Recognition: Best Paper Award at ICVGIP 2002. Silver Prize at Quebec University Research Forum 2006. Third Best Paper Award in Computers & Graphics (1999). Recognition for contributions to Indian computer graphics and software innovation. Teaching: Mudur has taught extensively, including courses on computer graphics, game development, system software, and multimedia computing at Concordia and institutions worldwide. His teaching spans both undergraduate and graduate levels, emphasizing practical skills and theoretical foundations.

Sergei Turitsynمشاهده پروفایل

استاد

• Nonlinear Science
• Optical Communications
• Fiber Optics
• +۳ مورد دیگر

Sergei Turitsyn is a Professor and Director of the Aston Institute of Photonic Technologies (AiPT) at Aston University. He holds the Royal Society Wolfson Research Merit Award since 2005 and specializes in nonlinear science, optical communications, and fiber laser technologies. His work spans soliton theory, high-speed optical systems, and Raman-based amplification. He leads the Photonics Research Group within the School of Engineering and Applied Science. Education: Joint MSc/BSc in Physics (1982) and PhD in Theoretical and Mathematical Physics (1986) from Novosibirsk University and Institute of Nuclear Physics, Russia. Prior to Aston, he was a Humboldt Fellow at Heinrich-Heine University (1992–1998). Research focuses on nonlinear dynamics, fiber lasers, and machine learning applications in communications. Recent articles emphasize neuromorphic photonics, dispersion compensation, and bi-chromatic laser systems. Awards include the Royal Society Wolfson Merit Award for sustained research excellence. Supervised 27 PhD students in areas like fiber lasers and nonlinear devices. Active in international conference committees and collaborates globally on projects like multiwavelength Raman lasers and bismuth-doped amplifiers. Leads AiPT, advancing photonic technologies through interdisciplinary research.

Victor Churchillمشاهده پروفایل

استادیار

• Computational Mathematics
• Scientific Machine Learning
• Image Reconstruction
• +۵ مورد دیگر

Victor Churchill is an Assistant Professor of Mathematics at Trinity College since 2023. He holds a Ph.D. and A.M. from Dartmouth College, an M.S. from New York University's Courant Institute, and a B.A. from Boston College. His research focuses on computational mathematics, scientific machine learning, and image reconstruction, particularly in Bayesian uncertainty quantification for synthetic aperture radar imaging and learning unknown dynamical systems using neural networks. He has held a postdoctoral position at The Ohio State University under Dr. Dongbin Xiu and previously worked at Dartmouth under Dr. Anne Gelb. Research Highlights: His work includes deep learning of PDEs, ensemble prediction for robust neural network training, and chaotic system learning from partial observations. Recent contributions address coarse time-scale observations and uncertainty quantification in SAR imaging. He was awarded the SIAM Science Policy Fellowship (2023-2024) to engage with federal science policy advocacy. Teaching: He teaches computational science courses at both undergraduate and graduate levels, integrating his research into lectures through case studies and data-driven examples. His pedagogical approach emphasizes applied computational mathematics and real-world problem-solving. Affiliations: Previously affiliated with The Ohio State University as a Visiting Assistant Professor of Scientific Computation. Active in computational math communities, including SIAM policy engagement. Personal Interests: An avid runner with marathon personal bests, he also enjoys bonsai cultivation, architectural design, and animal care. His unconventional hobbies include experimenting with hair color transformations.

Angshuman Guinمشاهده پروفایل

پژوهشگر

• Intelligent Transportation Systems (ITS)
• Freeway Operations
• Connected and Autonomous Vehicles
• +۷ مورد دیگر

Dr. Angshuman Guin is a Senior Research Engineer at the School of Civil and Environmental Engineering, Georgia Institute of Technology. He returned to Georgia Tech as faculty in 2007 after industry experience. His research focuses on enabling data-driven decisions in transportation systems through innovations in data collection, quality assurance, and processing. Key areas include Freeway Operations, Connected/Autonomous Vehicles, Intelligent Transportation Systems, and Smart Cities. He co-founded InstaData Systems to translate research into practice. Dr. Guin holds a Ph.D. from Georgia Tech and serves on Transportation Research Board (TRB) committees including Information Systems, Human Factors, and Safety Management. He reviews for journals like IEEE Transactions on ITS and ASCE Journal of Transportation Engineering. His work spans 93+ publications, emphasizing simulation, emissions analysis, intersection safety, and digital twin frameworks. Recent projects include optimizing Atlanta’s MLK Smart Corridor using reinforcement learning, evaluating Restricted Crossing U-Turn emissions, and developing tools for autonomous vehicle merging behaviors. He collaborates with Georgia DOT and FHWA on projects like incident detection systems and corridor performance metrics. Dr. Guin’s research bridges theory and practice, contributing to safer, smarter transportation systems through advanced analytics and emerging technologies.

• Cost-Effectiveness Analysis
• Health Technology Assessment
• Epidemiology
• +۳ مورد دیگر

Jean-Eric Tarride is a Professor in the Department of Health Research Methods, Evidence, and Impact at McMaster University's Faculty of Health Sciences. His academic career centers on advancing evidence-based healthcare through rigorous methodological research in health economics and outcomes assessment, with significant contributions to Canadian and international health policy. Dr. Tarride's research spans cost-effectiveness analysis , health technology assessment , and epidemiology , with emphasis on disease burden quantification and economic evaluation of medical interventions. His work addresses critical areas including osteoporosis, obesity, infectious diseases, palliative care, and Alzheimer's disease, frequently utilizing Canadian population-based datasets to inform real-world health decision-making. Analysis of his recent publications (2023-2025) reveals growing focus on ultrarare disease economics , virtual care evaluation , and international pharmaceutical policy (Brazil, Korea). Methodologically, he employs retrospective cohort studies , budget impact analyses , and risk-stratified cost-effectiveness modeling , demonstrating consistent application of health economics principles to diverse clinical contexts. No scientific awards were mentioned in the provided text. While Dr. Tarride maintains an extensive publication record with over 200 scholarly outputs in the last decade, specific details about student advising, grant funding, or laboratory leadership were not provided in the source material. His collaborative work suggests engagement with multidisciplinary research teams across Canada and internationally. Dr. Tarride's research program appears integrated within McMaster University's health research ecosystem, though specific laboratory affiliations or dedicated research teams were not detailed in the available information.

• Numerical Optimization
• Derivative-Free Optimization
• Stochastic Optimization
• +۳ مورد دیگر

Lindon Roberts is a Lecturer in the School of Mathematics and Statistics at the University of Sydney . He holds a DPhil (Doctor of Philosophy) from the University of Oxford and previously served as an MSI Fellow at the Australian National University. His research focuses on numerical optimization, including nonconvex, derivative-free, and stochastic optimization, with applications in machine learning. He currently teaches courses such as MATH2070 (Optimization and Financial Mathematics) and FMAT3888 (Projects in Financial Mathematics). Education & Professional Background: PhD (DPhil) in Mathematics, University of Oxford MSI Fellow, Australian National University Research Interests: Numerical optimization techniques Derivative-free and stochastic optimization methods Algorithm design for machine learning applications Nonconvex optimization challenges His work bridges theoretical optimization and practical implementation, particularly in imaging and data-driven fields. Funding & Grants: 2024: 'Robust Derivative-Free Algorithms for Complex Optimisation Problems' (Australian Research Council DECRA) 2022: 'Theory and Algorithms for Numerical Optimisation' (University of Sydney Faculty Startup) Key Research Trends in Publications: Recent articles emphasize optimization algorithms for imaging (e.g., X-ray and neutron beam techniques) and bilevel learning frameworks. His work on inexact hypergradients and scalable subspace methods highlights advancements in handling complex optimization landscapes.

Koos (Cornelis) Zevenhovenمشاهده پروفایل

پژوهشگر

• MRI Scanner Technology
• Intelligent Dynamics
• Ultra-Low-Field MRI
• +۳ مورد دیگر

Koos Zevenhoven is a doctoral researcher at Aalto University's School of Science, Department of Neuroscience and Biomedical Engineering. He leads a research group focused on innovative MRI technologies, particularly ultra-low-field MRI and hybrid MEG-MRI systems. His work emphasizes portable, cost-effective medical imaging solutions and 'intelligent dynamics' techniques to solve hardware challenges. Zevenhoven's research spans MRI hardware development, signal processing, and clinical applications in neuroimaging. He has collaborated internationally, including with UC Berkeley, and has over 30 publications. His thesis, defended in 2023, addresses unconventional MRI scanner design and dynamic pulse-waveform coupling. Education: Engineering Physics and Mathematics (Aalto University) Leadership: Research group leader for 10 years during his PhD Key Projects: First prototypes of combination brain scanners for epilepsy treatment planning Patents: Dynamical pulse-waveform coupling (DynaCAN) techniques Research interests include magnetic noise reduction, sensor design, and biomedical instrumentation. His work bridges theoretical physics and practical medical applications, aiming to improve diagnostic tools' accessibility and accuracy.

Andrew Millsمشاهده پروفایل

استاد

• Aerospace Systems
• Control Systems
• Health Monitoring
• +۷ مورد دیگر

Professor Andrew Mills holds the position of Professor of Innovation in Aerospace Systems Monitoring and Control at the School of Electrical and Electronic Engineering, University of Sheffield. He also serves as Deputy Director of the Control, Monitoring and Systems University Technology Centre (UTC), focusing on industry and research council-funded projects. His work emphasizes applied research in aerospace, including sensing solutions, health monitoring, and control systems for gas turbines. He collaborates closely with Rolls-Royce and coordinates PhD/MSc projects to bridge academic and industrial research. Education : MEng (Engineering), Chartered Engineer (CEng) from the University of Sheffield. Research Interests : Gas Turbine Health Monitoring Embedded Systems in Extreme Environments Fleet Monitoring Algorithms Vision-Based Sensing Systems Thermal System Control Laws Prognostics and Health Management (PHM) Grants & Projects : Lead Investigator (PI) and Co-Investigator (CI) on grants such as: "Advanced Intelligent EHM" (TSB HITEA II, 2014–2017) "Wireless Sensing for Monitoring" (Rolls-Royce, PI, 2013–2015) "Autonomous Intelligence for Civil UAS" (Rolls-Royce, PI, 2012–2013) Labs & Teams : Leads the Control, Monitoring and Systems UTC, fostering collaboration between academia and industry for aerospace innovation.

Ery Arias-Castroمشاهده پروفایل

استاد

• High-dimensional Statistics
• Machine Learning
• Spatial Statistics
• +۲ مورد دیگر

Professor specializing in statistical theory and methods at UC San Diego, with joint appointment in Data Science Institute. Research bridges mathematical statistics and machine learning applications in spatial analysis, image processing, and high-dimensional inference. Authored 'Principles of Statistical Analysis' textbook and develops R-based educational resources. Funded by NSF and ONR for work on minimax hypothesis testing and geometric data analysis.

Dimitris N. Politisمشاهده پروفایل

استاد

• Time Series Analysis
• Nonparametric Statistics
• Bootstrap Methods
• +۶ مورد دیگر

Dimitris N. Politis is a Distinguished Professor in the Department of Mathematics and the Halicioglu Data Science Institute at the University of California, San Diego. He holds the prestigious Halicioglu Data Science Institute Chancellor's Endowed Chair II position and has been affiliated with UCSD since 1997, progressing from Associate Professor to his current distinguished position. His educational background includes a Ph.D. in Statistics from Stanford University (1990), along with multiple master's degrees in Statistics, Mathematics, and Computer and Systems Engineering from Stanford and Rensselaer Polytechnic Institute. Professor Politis's research focuses on advanced statistical methodologies, with particular expertise in: Time Series and Random Fields analysis Computer-Intensive Methods in Statistics Resampling and Subsampling for Dependent Observations Spatial Statistics and Point Processes Nonparametric Spectral and Probability Density Estimation Model-free Prediction and Regression Information Theory and Signal Processing Econometric Analysis of Financial Time Series His scholarly output includes over 100 journal papers and several influential books, most notably "SUBSAMPLING" (1999), "MODEL-FREE PREDICTION AND REGRESSION" (2015), and "TIME SERIES: A FIRST COURSE WITH BOOTSTRAP STARTER" (2020), which has become a key educational resource in the field. Professor Politis has received numerous prestigious awards and honors: Guggenheim Fellowship (2011) Fellow of the American Statistical Association (2011) Fellow of the Institute of Mathematical Statistics (2004) Distinguished Author Award from the Journal of Time Series Analysis (2020) Econometric Theory Multa Scripsit Award (2013) Tjalling C. Koopmans Econometric Theory Prize (2012) He has been principal investigator on numerous NSF and NIH grants, including current funding for "Computer-intensive methods for dependent and complex data" (NSF DMS 24-13718, 2024). Professor Politis has held significant leadership roles, including serving as Chair of the Faculty Council of the Halicioglu Data Science Institute (2019-2023) and Associate Director (Founding) of the Institute (2018-2024). As a co-founder of the International Society for NonParametric Statistics, Professor Politis has made substantial contributions to the organization of major conferences and workshops in his field, including the First Conference of the International Society for NonParametric Statistics in 2012. His editorial work includes serving as Co-Editor of the Journal of Time Series Analysis since 2013 and Senior Editor for the ACM/IMS Journal of Data Science since 2022.

Quefeng Liمشاهده پروفایل

دانشیار

• High-dimensional statistics
• Biomedical research
• Omics data integration
• +۵ مورد دیگر

Dr. Quefeng Li is an Associate Professor in the Department of Biostatistics at the University of North Carolina at Chapel Hill (UNC-Chapel Hill), part of the Gillings School of Global Public Health. He earned his Ph.D. in Statistics from the University of Wisconsin-Madison (2013) and completed a postdoctoral fellowship at Princeton University (2013–2015). His research focuses on high-dimensional statistics and its applications in biomedical and neuroimaging data analysis, emphasizing robust methodologies and integrative data analysis techniques. Dr. Li's work has contributed to advancements in variable selection, data integration, and statistical methods for complex biomedical datasets. He has held editorial roles at journals like Biometrics and Biostatistics , and serves on multiple professional committees. His research has been supported by grants from the NIH, including R01AG073259 and R01CA282648, and he collaborates extensively with clinical researchers across disciplines. His research interests span high-dimensional statistics, neuroimaging analysis, and robust statistical methods. Notable contributions include developing the ARTdeConv algorithm for cell-type deconvolution and the glmmPen package for penalized generalized linear mixed models. He has advised numerous PhD students, many of whom now work in industry and academia. Awardees include the Gillings Research Excellence Award (2023), Junior Faculty Development Award (2018), and University Research Council Award (2016). His work bridges theoretical statistics with practical biomedical applications, addressing challenges in data heterogeneity and reproducibility.

Stephen Duffyمشاهده پروفایل

استاد

• Cancer Screening
• Epidemiology
• Biostatistics
• +۷ مورد دیگر

Professor Stephen Duffy is a leading academic in cancer screening and statistical research at Queen Mary University of London (QMUL), affiliated with the Wolfson Institute of Population Health. He has conducted pivotal work in randomized trials of cancer screening programs, including foundational studies like the Swedish Two-County Trial (basis for UK breast screening) and the UK Lung Screening Trial. His current role as Director of the Policy Research Unit in Cancer Awareness, Screening and Early Diagnosis since 2010 involves collaboration across seven institutions to advance early cancer detection strategies. Trained at the University of Edinburgh and Imperial College London, his expertise spans biostatistics, epidemiology, and public health. His research focuses on improving screening efficacy through innovations such as AI-driven risk assessment, optimizing screening intervals, and addressing barriers to participation. He also explores the societal impact of screening, including cost-effectiveness and socio-economic disparities in program outcomes. Professor Duffy’s scientific contributions include twice receiving the Alexander Margulis Prize for Scientific Excellence from the Radiological Society of North America. His work integrates behavioral science to enhance screening uptake and examines the role of social media in cancer awareness. Additionally, he investigates the ecological and genomic implications of invasive species and zoonotic diseases, reflecting his interdisciplinary approach to health challenges. His grants and leadership roles highlight extensive collaborations, such as the NIHR School for Primary Care Research and the Department of Health-funded Policy Research Unit. He leads efforts to refine colorectal and lung cancer screening protocols while advocating for equitable access to healthcare interventions. His team’s work on artificial intelligence and symptom-driven diagnostics underscores a commitment to transforming cancer care through evidence-based practices.

Rajendran Parthibanمشاهده پروفایل

استاد

• Optical Networks
• Visible Light Communication
• Vehicular Communication
• +۴ مورد دیگر

Professor Rajendran Parthiban is a Professor and Deputy Dean (Education) in the Department of Electrical and Computer Systems Engineering at Monash University. He holds a PhD and Bachelor of Engineering from the University of Melbourne (Australia). His academic leadership roles include Deputy Head of School (Education) and leadership in photonics and communications research groups. He has extensive teaching experience, achieving top evaluations in five undergraduate and one postgraduate subjects. Education: PhD in Electrical and Electronic Engineering, University of Melbourne (2004) Bachelor of Engineering (First Class Honours), University of Melbourne (1997) Research Interests: Focuses on optical networks, visible light communications (VLC), vehicular communication, and educational technologies like VR/AR integration. His work addresses challenges such as energy-efficient optical architectures, high-speed VLC systems, and technology-enhanced learning frameworks. Recent projects include developing traffic management frameworks and green vehicle routing strategies. Grants & Funding: Secured over RM2 million in external grants, including projects on Li-Fi systems, AR/VR in engineering education, and green vehicular networks. Notable grants include collaborations with the Australian Digital & Telecom Pty Ltd and Monash-Warwick Alliance. Awards: Pro-Vice Chancellor’s Award for Excellence in Research (2011, 2012) Pro-Vice Chancellor’s Award for Excellence in Teaching (2007–2010) Australian Learning and Teaching Council Citation (2008) Supervision: Guided eight PhD and one Master’s students, with ongoing supervision in areas like credit risk forecasting, vehicular networks, and seamless learning frameworks. Professional Activities: Senior member of IEEE, with affiliations to IEEE Communications Society, Photonics Society, and multiple engineering organizations. Active in research groups and international collaborations.