جست‌وجوی استاد و پژوهشگر

Spiridon Penevمشاهده پروفایل

استاد

• Wavelet Methods in Non-Parametric Curve Estimation
• Edgeworth Expansions and Saddlepoint Approximation Methods
• Structural Equation Models
• +۴ مورد دیگر

Professor Spiridon Penev is a faculty member at the School of Mathematics & Statistics , University of New South Wales (UNSW), Sydney. After completing his PhD in Mathematical Statistics at Humboldt University, Berlin, he worked at Technical University of Sofia (Bulgaria) for 10 years, becoming Associate Professor in 1991. He joined UNSW in 1992, progressing from Lecturer to Professor in 2019. His teaching focuses on Statistical Inference , Multivariate Analysis , Longitudinal Data Analysis , and related advanced courses. Research Interests: Wavelet Methods in Non-Parametric Curve Estimation, Edgeworth Expansions, Saddlepoint Approximation, Structural Equation Models, Inference in Semiparametric Models, and Stochastic Risk Modelling. Article Trends: His work spans from foundational wavelet methods (pre-2010) to modern applications in climate model ensembles , portfolio optimization , marine engineering , and machine learning . Keywords include Statistics, Finance, Climate Science, Structural Health Monitoring, and Optimization. Awards: DAAD Award, Elected Member of the International Statistical Institute (ISI). Grants: Led ARC Discovery Project (2016–2018), ARC Linkage Project (2018–2022), and industry collaborations like SCA water quality analysis (2014–2019). Location: School of Mathematics and Statistics, UNSW Sydney, Room 1038, The Red Centre.

Guillaume Puelمشاهده پروفایل

استاد

• Mechanical Engineering
• Materials Science
• Inverse Problems
• +۶ مورد دیگر

Guillaume Puel is a Professor at Universite Paris-Saclay and a researcher at the Laboratory Paris-Saclay Mechanics (LMPS). His work focuses on inverse problems, parameter identification, and homogenization techniques in structural dynamics and mechanical engineering. His research bridges computational modeling with experimental validation, particularly in railway noise, vibro-acoustic coupling, and fatigue simulation of materials. He employs multi-scale methods, adaptive meshing, and regularization to solve transient nonlinear models with contact phenomena. Recent publications highlight trends in medium-frequency computing platforms (e.g., pyTVRC), time homogenization for fatigue analysis, and Trefftz methods for railway noise prediction. His collaborations include Denis Aubry, Andrea Barbarulo, and Nhat Quang Ta. Labs and teams: LMPS laboratory at Universite Paris-Saclay, where he contributes to advanced mechanical modeling and railway engineering applications.

J. Michael Davisمشاهده پروفایل

دانشیار

• Aircraft Powerplant Technology
• Aviation Maintenance
• Aviation Fuels
• +۳ مورد دیگر

Dr. J. Michael Davis serves as Associate Professor of Aeronautical Engineering Technology and Associate Head for Undergraduate Affairs in Purdue University's School of Aviation and Transportation Technology. He directs test cell operations for the federally-funded National Test Facility for Fuels and Propulsion (NaTeF) and holds dual leadership roles as Co-Chair and FAA Liaison for the Part 147 Aviation Maintenance Curriculum. His research focuses on experimental development and testing of alternative aviation fuels for piston and turbine engine applications, conducted through cross-departmental collaborations at Purdue. This work directly informs his teaching in aircraft powerplant systems, aviation maintenance practices, and sustainable fuel technologies, addressing critical industry needs in business aviation sustainability. Dr. Davis maintains extensive industry certifications including FAA Airframe & Powerplant (A&P), FAA Private Pilot license, Project Management Professional (PMP), and 6 Sigma Green Belt, which bridge academic theory with practical aviation technology applications. As NaTeF test cell operations director, he manages federal infrastructure for propulsion research while shaping national aviation maintenance standards through the Part 147 curriculum. His leadership in the Competency-Based Experiential Learning Program demonstrates commitment to industry-aligned technician training in business aviation sectors.

Manoj S. Patankarمشاهده پروفایل

استاد

• Aviation Technology
• Aviation Safety
• Human Factors in Aviation
• +۸ مورد دیگر

Manoj S. Patankar is a Professor at Purdue University’s Purdue Polytechnic Institute and serves as the Director of the Center for Research and Education in Advanced Transportation Ecosystems (CREATE). Previously, he held leadership roles as department chair, dean, and provost at Saint Louis University. His work focuses on aviation technology, safety, and workforce development, integrating insights from psychology, education, and management. Bachelor’s degree in Aeronautics from Saint Louis University M.S. in Aviation Safety from the University of Central Missouri MBA from Georgetown University Ph.D. in Education from Nova Southeastern University Ph.D. in Management from the University of Sheffield (U.K.) Institute for Educational Management from Harvard University Patankar’s research explores aviation safety through interdisciplinary approaches, emphasizing AI, AR/VR technologies in aviation maintenance and FAA-funded workforce development programs. He also investigates fuel economy optimization, greenhouse gas emissions reduction, and engine longevity improvements. Fellow of the Royal Aeronautical Society (FRAeS) Multiple research awards As principal investigator, Patankar has managed over $6 million in federal grants from agencies like the FAA and NSF, alongside industry funding from FlexJet. His projects include high-tech learn-by-doing programs for aviation educators and living-learning labs for technician apprenticeships. Patankar leads CREATE, a multidisciplinary research center fostering collaboration between academia, industry (e.g., FlexJet), and federal agencies. He holds certifications as a private pilot, aircraft mechanic, and FCC General Radiotelephone Operator, with academic experience across seven countries.

Ronald Kantermanمشاهده پروفایل

استاد مدعو

• Fire Science
• Emergency Management
• Fire Prevention
• +۳ مورد دیگر

Ronald Kanterman serves as Adjunct Faculty in Fire Science and Professional Studies within the Henry C. Lee College of Criminal Justice and Forensic Sciences at the University of New Haven. With 47 years of fire service experience, he currently holds the position of Executive Inspector for the FDNY Bureau of Fire Prevention while teaching at the university. His research interests span multiple critical areas of fire science and emergency management. Kanterman specializes in fire prevention strategies , occupational safety and health protocols for firefighters, and hazardous materials response . His work emphasizes practical applications in fire service administration and emergency management systems, with particular focus on leadership development and organizational resilience within fire departments. His scholarly output demonstrates consistent contribution to fire service literature, with publications spanning fire officer safety, hazardous materials response, and fire service leadership. The articles reveal a strong emphasis on practical applications with theoretical underpinnings in fire science, showing evolution from technical firefighting procedures toward broader organizational and leadership concerns in later publications. Over 180 published works in fire service literature Regular contributor to Fire Engineering magazine and Fireengineering.com Author of multiple textbooks including "Fire Officer's Guide to Occupational Safety and Health" (2019) Kanterman has taught for 32 years at various two and four-year colleges at undergraduate and graduate levels, including serving as an Adjunct Instructor at the National Fire Academy. He has been instrumental in fire service education through his long-standing involvement with the Fire Department Instructors Conference (FDIC), where he has taught for 25 years and served on the Educational Advisory Committee. Beyond academia, he volunteers with the National Fallen Firefighters Foundation and serves as an Instructor for the Local Assistance State Teams program.

Ji-Hye Paikمشاهده پروفایل

دانشیار

• Cancer Biology
• Epigenetics
• Transcriptional Regulation
• +۸ مورد دیگر

Ji-Hye Paik is an Associate Professor in the Department of Pathology and Laboratory Medicine at Weill Cornell Medicine, with a primary affiliation in the Graduate School of Medical Sciences. Her research is centered on transcriptional and epigenetic regulation in cancer and aging, particularly through FOXO transcription factors and the alternative lengthening of telomeres (ALT) pathway. Her research focuses on understanding how lineage-specific transcription factors like FOXO1 regulate cell fate in cancer and aging. The Paik Lab investigates molecular mechanisms of B-cell lymphoma progression, telomere maintenance in ALT-positive cancers, and the role of FOXO in mammalian aging. Using genetically engineered mouse models and molecular screening approaches, the lab identifies therapeutic vulnerabilities in these processes. The recent publications highlight a shift toward translational relevance, exploring how FOXO1 drives lymphoma survival and how longevity genes protect neural stem cells. These works span cancer biology, stem cell regulation, and stress response mechanisms. The Irma T. Hirschl Career Scientist Award The Sidney Kimmel Scholar Award Ellison Medical Foundation New Scholar Award Claudia Adams Barr award for Innovative Basic Cancer Research KOSEF Research Excellence Award Damon Runyon Cancer Research Foundation Postdoctoral Fellowship American Association for Cancer Research Scholar-in-training Award Dr. Paik has secured significant recognition and funding through highly competitive awards, indicating strong grant support. She mentors students through the Cell & Developmental Biology PhD program and contributes to over 70 peer-reviewed publications. While specific advisees are not listed, her lab is actively engaged in training and discovery. The Paik Lab operates at the interface of cancer genetics and epigenetics, utilizing advanced mouse models and molecular screens. The lab is structured around two major research arms: one exploring FOXO-driven lymphomagenesis and the other investigating ALT mechanisms in telomere maintenance.

• Wave Energy
• Marine Renewable Energy
• Electrical Engineering
• +۳ مورد دیگر

Jan Sundberg is a Professor of Electrical Engineering at Uppsala University, specializing in ecological aspects within the Department of Electrical Engineering at The Ångström Laboratory. His research spans two distinct but equally significant fields: wave energy technology and marine renewable energy systems, and earlier work in avian ecology focusing on yellowhammers. His research interests center on the intersection of electrical engineering and environmental science, with particular focus on wave energy conversion systems, ecological impact assessment of marine renewable energy installations, and underwater acoustic monitoring techniques. Sundberg has made significant contributions to understanding how wave energy converters interact with marine ecosystems, including fish behavior, marine mammal responses, and benthic community development around energy infrastructure. Analysis of Sundberg's publication record reveals a clear evolution of research focus. Beginning with ornithological studies in the 1990s examining yellowhammer mating behaviors and plumage coloration, his work transitioned toward renewable energy research in the early 2000s. Since 2005, his publications have predominantly focused on wave energy technology, with particular emphasis on environmental monitoring using sonar systems, ecological impacts of marine energy installations, and operational characteristics of wave energy converters. His most recent work (2020-2023) demonstrates sophisticated approaches to monitoring marine life interactions with renewable energy infrastructure using advanced sonar technologies. Sundberg has been actively involved with the Lysekil Research Site in Sweden, a key facility for wave energy research where he has contributed to numerous studies examining noise emissions, ecological impacts, and operational characteristics of wave energy converters. His work often involves interdisciplinary collaboration with marine biologists, environmental scientists, and engineering specialists.

Mary Beckerleمشاهده پروفایل

استاد

• Cell Biology
• Cancer Biology
• Molecular Biology
• +۴ مورد دیگر

Mary Beckerle is a Distinguished Professor of Biology and CEO & Director of the Huntsman Cancer Institute at the University of Utah. Her research focuses on cell adhesion, motility, and mechanobiology, with implications in cancer and respiratory diseases. She holds an adjunct appointment in the Department of Oncological Sciences and participates in the Sarcoma Center and Molecular Biology Graduate Program. Ph.D. from University of Colorado, Boulder Research Interests Beckerle's work investigates how cells integrate mechanical and biochemical signals to regulate adhesion, migration, and cytoskeletal dynamics. Key areas include Ewing sarcoma pathogenesis, integrin signaling, and actin stress response mechanisms. Publication Trends Her recent publications emphasize mechanosensitive pathways, tumor progression in sarcomas, and cytoskeletal regulation. Collaborative studies span molecular modeling, clinical implications in asthma, and epigenetic therapies for cancer. Labs & Affiliations She leads the Beckerle Lab, which operated from 1986 to 2022, and maintains affiliations with multiple programs at the University of Utah and Huntsman Cancer Institute.

• Entropy Estimation
• Theory of Stochastic Orders
• Estimation in Restricted Parametric Space
• +۱ مورد دیگر

Neeraj Misra is a Professor in the Department of Mathematics & Statistics at the Indian Institute of Technology Kanpur (IIT Kanpur), where he has held faculty positions since 1996. He earned his PhD (1991) and M.Sc. (1985) in Statistics from IIT Kanpur, and a B.Sc. from Kanpur University (1982). His research focuses on theoretical statistics and applied probability. Research Interests: His work spans entropy estimation, stochastic ordering theory, estimation under parameter restrictions, and ranking/selection methodologies, with applications in reliability engineering and molecular sciences. Key themes include: Development of nonparametric entropy estimators Stochastic comparisons for system reliability Optimization in statistical decision theory Inference for restricted parameter spaces Publication Trends: His recent articles (2003–2015) demonstrate a consistent focus on reliability modeling, stochastic ordering, and entropy estimation. Works frequently involve gamma distributions, redundancy allocation in engineering systems, mixture models, and multivariate circular distributions, blending theoretical rigor with practical applications. Awards & Honors: Jacob Wolfowitz Award (2003) for theoretical advances C. L. Chandna Mathematics Award (2003) for research/teaching excellence All India Rank #2 in Mathematics (National Entrance Exam, 1985) Outstanding Teaching Recognition at IIT Kanpur He has held visiting positions at West Virginia University, Marquette University (USA), and KU Leuven (Belgium).

Kalyanmoy Debمشاهده پروفایل

استاد

• Multi-Objective Optimization
• Evolutionary Algorithms
• Genetic Algorithms
• +۵ مورد دیگر

Kalyanmoy Deb is a Professor at the Department of Electrical and Computer Engineering, Michigan State University. Previously affiliated with Indian Institute of Technology Kanpur and Indian Institute of Technology Madras, he is a leading researcher in evolutionary algorithms and multi-objective optimization. Research Focus : Multi-Objective Optimization, Genetic Algorithms, Constraint Handling, Machine Learning-assisted Optimization Key Contributions : Development of NSGA (Non-dominated Sorting Genetic Algorithm) series, hybridization of machine learning with evolutionary algorithms, fidelity evaluation techniques Scientific Accomplishments : With over 347 publications and 19,618 citations, his work on NSGA algorithms has become foundational in evolutionary computation. His recent research explores mixed-fidelity evaluations, innovized knowledge extraction, and neural architecture search.

Kevin Nolanمشاهده پروفایل

پژوهشگر

• Fluid Dynamics
• Aerosol Transmission
• Medical Engineering
• +۵ مورد دیگر

Dr Kevin Nolan is a Researcher at the UCD School of Mechanical and Materials Engineering , University College Dublin, specializing in fluid dynamics , aerosol transmission , and medical engineering . His work spans surgical safety , renewable energy systems , and microfluidic technologies , with a focus on real-world applications like infection control and wind turbine aerodynamics . Recent research includes modeling surgical smoke leakage , developing standards for face coverings , and analyzing wind turbine blade erosion using advanced fluid dynamic techniques. Collaborations with Mater Hospital , Cisco Systems , and NUI Galway highlight the interdisciplinary impact of his work. Key contributions: Schlieren optical technique for visualizing airflow, European standard development for community face coverings Current projects involve IoT-based air quality monitoring , 3D facial mapping for mask design , and reducing dead spots in air purification Publications address gas leaks in laparoscopy , reusable cloth mask efficacy , and flow friction dynamics , with a strong emphasis on computational fluid dynamics (CFD) and practical mitigation strategies across medical and engineering domains.

• Risk Management
• Economic Statistics
• Reliability Engineering
• +۵ مورد دیگر

Professor Jake Ansell is a faculty member at the University of Edinburgh Business School, specializing in Risk Management. He holds a PhD in Reliability from Keele University, an MSc in Statistics from Newcastle University, and a BSc from the University of Leicester. Director, Credit Research Centre Co-founder, Edinburgh Strategic Resilience Initiative Member, Royal Statistical Society His research spans financial risk modeling, statistical methods in credit scoring, tourism analytics, and strategic asset management. Key themes include: Economic statistics and indices Financial wellbeing frameworks Quantitative tourism flow management Reliability engineering Recent publications focus on credit scoring interpretability (2023), asset maintenance optimization (2022), and social media impacts on tourism (2024). Current projects include ESRC-funded IoT tourism management in rural destinations. Active collaborations include: Principal Investigator for ESRC IAA Transient Visitor Levy project (2025) Co-investigator for financial capability research (2022-2024)

Vanda Dimitriouمشاهده پروفایل

مدرس ارشد

• Building Performance Modelling
• Energy Efficiency in Construction
• Sustainable Design Strategies
• +۴ مورد دیگر

Dr. Vanda Dimitriou is a Senior Lecturer specializing in Digital Engineering and Building Performance at an unspecified university. She serves as Ethics Lead and Deputy Lead for Architectural Engineering programs. Her research focuses on building performance modelling, digital technologies in construction, and sustainable design strategies, particularly integrating Building Information Modelling (BIM), energy simulation, and computational methods. She leads projects on thermal model calibration, BIM interoperability, and digital twins for sustainable built environments, collaborating closely with industry and government bodies. Her research interests include dynamic thermal modelling using real-world data, BIM energy modelling at building and district scales, and retrofit solutions for residential and commercial buildings. She has supervised multiple PhD students in areas like HVAC digital twins, grey-box modelling, and net-zero retrofitting. Her recent projects include the Design4Energy FP7 EU project and the EPSRC-funded REFIT initiative, demonstrating expertise in interdisciplinary energy research. Dr. Dimitriou’s work emphasizes data-driven approaches to building energy systems, including smart metering and sensor integration. She has pioneered decision support tools for retrofitting and authored numerous publications on energy efficiency and thermal modelling techniques.

• Predictive Maintenance
• Machine Learning
• Fault Detection
• +۵ مورد دیگر

Dr. Lilach Goren Huber is a Senior Lecturer and R&D Projects Leader at the ZHAW School of Engineering, specializing in predictive maintenance and data-driven solutions for industrial systems. She leads multiple projects focusing on AI applications in anomaly detection (e.g., wind turbines, solar power plants), physics-informed machine learning for sensor error correction, and fault prognostics under data scarcity. Her work bridges academic research with industrial implementation, emphasizing scalable deep learning frameworks for commercial fleets and energy infrastructure. Research interests include predictive maintenance strategies, machine learning for industrial IoT, and hybrid prognostics combining domain knowledge with AI. She has published extensively in journals like International Journal of Prognostics and Health Management and Journal of Big Data , with a focus on renewable energy systems, SCADA data analysis, and cross-domain transfer learning. Current Projects: Physics-informed ML for elastomer sensors, end-to-end fault prognostics for power grids, and hybrid prognostics research. Past Contributions: Developed decision support systems for laser cutting machines, optimized hydroelectric maintenance schedules, and created risk-based frameworks for Swiss national road safety equipment. She actively contributes to the Expert Group Smart Maintenance and serves as a project leader in the ZHAW-PARC initiative. Her work addresses technical challenges like data contamination, sensor calibration errors, and real-world implementation barriers in industrial AI adoption.

Mahmoud Sayed Mahmoud Eidمشاهده پروفایل

پژوهشگر ارشد

• Data-driven fault diagnosis
• Electric power trains
• Electromagnetic modeling
• +۱ مورد دیگر

Mahmoud Sayed Mahmoud Eid is a PhD Research Fellow in Engineering Sciences at the University of Agder. His research focuses on fault diagnosis in electric powertrains using AI-driven methods. He holds a B.S. in Mechatronics Engineering from Helwan University (2013) and an M.S. in Advanced Mechanical and Robotics Engineering from Ritsumeikan University, Japan (2019). Research Focus: Develops computational models for early fault detection in electric motors and inverters under noisy operational conditions. His methodologies integrate electromagnetic theory with machine learning for industrial applications in transportation and energy systems. Publications: His 6 most recent articles (2022-2025) focus on AI-enhanced diagnostics for power electronics and motor systems, demonstrating consistent innovation in signal processing and classifier design for industrial reliability.