جست‌وجوی استاد و پژوهشگر

• Particle physics
• Quantum field theory
• Renormalization
• +۳ مورد دیگر

Dr. Vytautas Dūdėnas is a Researcher at the Institute of Theoretical Physics and Astronomy (ITPA) within the Faculty of Physics at Vilnius University. His primary research focuses on particle physics theory and phenomenology, with specific expertise in quantum field theory, renormalization techniques, and beyond standard model physics. His work bridges theoretical frameworks with experimental applications in laser physics and optics. Dr. Dūdėnas' research interests span particle physics theory, quantum field theory, renormalization methods, and beyond standard model physics. His recent publications demonstrate a significant focus on laser-matter interactions, nonlinear optics, and advanced optical techniques. His work explores fundamental aspects of particle interactions while applying these principles to cutting-edge optical technologies and material processing techniques. The consistent theme across his research is the investigation of fundamental physical phenomena through both theoretical frameworks and experimental applications. Analysis of his recent publications reveals a strong emphasis on Bessel beams, supercontinuum generation, femtosecond laser processing of materials, and advanced optical techniques. His work demonstrates expertise in both theoretical physics concepts and their practical applications in photonics and materials science. The interdisciplinary nature of his research connects fundamental particle physics with applied optical technologies. Dr. Dūdėnas teaches advanced physics courses including Quantum Field Theory II and Mechanics, contributing to the education of future physicists at Vilnius University. His ORCID profile (0000-0001-9405-9959) provides access to his complete publication record, while his research outputs are extensively documented on INSPIRE-HEP.

• Semiconductor physics
• Materials science
• Carrier recombination
• +۳ مورد دیگر

Dr. Vytautas Grivickas is a Senior Researcher at the Institute of Photonics and Nanotechnology (IPN), Vilnius University, specializing in semiconductor physics and materials science. His research focuses on carrier recombination, transport phenomena, and optical properties of wide bandgap semiconductors including Si, SiC, diamond, AlN, and Ga2O3. Expertise in radiation defect evolution in semiconductors Develops contactless characterization techniques for radiation sensors Active in medical dosimetry systems development Research Highlights: His work analyzes free carrier absorption spectra (e.g., in 4H-SiC), investigates carrier dynamics in layered chalcogenides, and explores electron-hole separation mechanisms. Collaborative studies appear in journals like Scientific Reports and Applied Physics Letters . Project Leadership: Contributes to the UWBG-LEAP project (Ultra-Wide Bandgap Laser) under European Regional Development Fund. Scientific Contributions: Demonstrates expertise in semiconductor material characterization and laser-induced modifications, with over 15 recent publications in supercontinuum generation, Bessel beam applications, and femtosecond laser micromachining.

Robert S. Keyserمشاهده پروفایل

استاد

• Industrial Engineering
• Lean Manufacturing
• Work Measurement
• +۵ مورد دیگر

Dr. Robert S. Keyser is a Professor in the Department of Industrial Engineering Technology at Kennesaw State University's College of Engineering and Engineering Technology. With expertise spanning industrial engineering, lean manufacturing, and human factors, Dr. Keyser applies engineering principles to diverse fields including healthcare systems, manufacturing, and higher education. His interdisciplinary approach bridges traditional engineering with practical applications in real-world settings. Dr. Keyser's educational background includes: PhD in Industrial Engineering (Manufacturing Systems concentration) from the University of Tennessee (2008) MS in Statistics from the University of Tennessee (2005) MBA in Management from East Tennessee State University (1992) BS in Statistics from the University of Tennessee (1988) His research interests focus on applying industrial engineering tools such as Lean manufacturing, work measurement, human factors, and reliability analysis across multiple sectors. Dr. Keyser has developed particular expertise in healthcare systems engineering, where he applies process improvement methodologies to address challenges in blood donation, fluoride varnish application, and pandemic response in educational settings. His work often involves interdisciplinary collaboration with colleagues from health sciences, statistics, and computer science. Dr. Keyser's recent publications demonstrate a strong focus on healthcare applications, blood donation systems, and pandemic response in higher education. His research shows a consistent pattern of applying industrial engineering principles to solve complex problems in diverse settings, with increasing emphasis on technology integration and data-driven decision making. The breadth of his work spans traditional manufacturing contexts to innovative applications in healthcare and education. Dr. Keyser has received significant research funding including: NIH R15 grant ($426,490) for removing barriers to fluoride varnish application in primary care Virtual Reality Blood Donor Experience grant ($5,000) ALG Textbook Transformation grant ($16,200) for creating no-cost work measurement textbooks Georgia Affordable Learning Grant ($11,800) for developing no-cost learning materials As an educator, Dr. Keyser teaches a wide range of courses including Work Measurement and Ergonomics, Operations Research, Systems Simulation, and Human Factors Engineering. He has developed several OER (Open Educational Resource) textbooks to reduce costs for students. His teaching philosophy emphasizes practical application of engineering principles to real-world problems, often incorporating case studies from his research projects. Dr. Keyser is an active member of the Institute of Industrial and Systems Engineers (IISE) and collaborates extensively with colleagues both within Kennesaw State University and at other institutions, particularly on healthcare-related engineering projects.

• Computer Vision
• Robotics
• Medical Robotics
• +۶ مورد دیگر

Takeo Kanade is the U.A. and Helen Whitaker University Professor of Robotics and Computer Science at Carnegie Mellon University (CMU). He serves as director of the Quality of Life Technology Engineering Research Center and previously led the Robotics Institute (1992-2001). His work spans computer vision, robotics, and multimedia technology, emphasizing mathematical modeling of vision processes and system development. Education: Doctoral degree in Electrical Engineering from Kyoto University (1974) Kanade's research focuses on foundational computer vision (factorization methods, multi-baseline stereo, facial recognition), virtualized reality systems for immersive media applications, and robotics innovations in medical surgery (HipNav) and autonomous helicopters. He pioneered computational sensors integrating VLSI technology. Recent publications emphasize 3D vision, pose estimation, and real-time facial alignment, reflecting his work in social motion capture and scene-specific object recognition. His projects include Informedia (NSF/ARPA/NASA-funded digital video libraries) and EyeVision for immersive sports broadcasting. Scientific Awards: Kyoto Prize (2016), Benjamin Franklin Medal, Bower Prize, IEEE Pioneer Award, ACM/AAAI Allen Newell Award, Joseph Engelberger Award He advises past PhD and Master's students like Omead Amidi, Vladimir Brajovic, and Richard LaBarca. He founded the Digital Human Research Center and leads the Human Sensing Lab at CMU.

• Machine Learning
• Evolutionary Algorithms
• Swarm Intelligence
• +۵ مورد دیگر

Mehdi Neshat is a Visiting Scholar at the Data Science Institute within the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS). He holds a PhD in Engineering from the University of Adelaide (2016-2020) and has extensive experience as a research data scientist specializing in computational optimization methods applied to complex engineering and healthcare problems. His educational background includes: PhD in Engineering, University of Adelaide (2016-2020) Neshat's research focuses on developing and applying advanced computational methods to solve real-world challenges. He specializes in evolutionary algorithms, swarm intelligence, and machine learning techniques for optimizing renewable energy systems, particularly wave and wind energy converters. His work extends to healthcare applications including genomic analysis and medical diagnostics, as well as structural engineering optimization and smart building energy management. His interdisciplinary approach bridges theoretical algorithm development with practical implementation across multiple domains, demonstrating exceptional versatility in computational problem-solving. Analysis of his recent publications reveals a strong trend toward sophisticated ensemble methods and hybrid optimization approaches that combine multiple algorithms to overcome limitations of single-method approaches. His research shows increasing sophistication in handling multi-objective optimization problems, particularly in renewable energy systems where trade-offs between power output, system stability, and cost must be balanced. The geographical focus of his energy research centers on Australian coastal regions, with practical applications for wave and wind farm deployment. Neshat has received significant recognition for his research contributions: Back-to-back Best Paper Prizes at the GECCO conference (2019 and 2020), a CORE A-ranked international optimization and machine learning conference His collaborative research spans multiple institutions and disciplines. Previously, he served as a Postdoctoral Research Associate with the Genomic analysis team at the Australian Centre for Precision Health, Cancer Research Institute, University of South Australia, and as a Senior Research Fellow at the Center for Artificial Intelligence Research and Optimization, Torrens University Australia. His work demonstrates consistent engagement with multidisciplinary teams across engineering, computer science, and healthcare domains, with a strong emphasis on practical implementation of theoretical methods. At UTS, Neshat contributes to the Data Science Institute's research agenda, focusing on applying advanced computational methods to complex real-world problems where traditional analytical approaches fall short. His current work continues to expand the boundaries of optimization techniques for renewable energy systems while exploring new applications in healthcare analytics and structural engineering.

Ramya Korlakai Vinayakمشاهده پروفایل

استادیار

• Machine Learning
• Statistical Inference
• Crowdsourcing
• +۳ مورد دیگر

Ramya Korlakai Vinayak is the Dugald C. Jackson Assistant Professor in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison's College of Engineering. Her research bridges theoretical machine learning with human-centered AI applications. Education: Postdoctoral Researcher, Paul G. Allen School of Computer Science and Engineering, University of Washington Ph.D. and M.S. in Electrical Engineering, California Institute of Technology (Caltech) B.Tech. in Electrical Engineering, Indian Institute of Technology Madras (IIT M) Research Focus: Her work centers on machine learning foundations with emphasis on statistical inference, crowdsourcing, and human-AI collaboration. Key themes include modeling heterogeneous human preferences, developing robust out-of-distribution detection systems, and creating culturally-aware generative models. She pioneers methods for pluralistic alignment where AI systems accommodate diverse human values through ideal point modeling and adaptive feedback mechanisms. Publication Trends: Recent publications (2023-2025) reveal three converging trajectories: (1) Human-in-the-loop frameworks for reducing false positives in safety-critical systems, (2) Metric learning innovations using limited preference data, and (3) Critical examinations of cultural limitations in generative AI. Her work consistently addresses real-world challenges like cognitive overload in crowdsourcing and biases in face generation systems. Research Infrastructure: She leads an active research group with a dedicated lab website (https://ramyakv.github.io/) focusing on developing theoretically-grounded yet practically-deployable AI systems that respect human plurality.

Jérémie Bourdonمشاهده پروفایل

استاد

• Bioinformatics
• Probabilistic modeling
• Systems biology
• +۵ مورد دیگر

Professor Jérémie Bourdon is a Full Professor of Computer Science at the University of Nantes, Faculty of Science and Technology, where he serves as Vice-Dean in charge of Research, Innovation and International Relations since 2018. He is affiliated with LS2N (Laboratory of Digital Sciences of Nantes, UMR 6004) and heads the ComBi research group (Combinatorics and Bioinformatics) since January 2014. His research focuses on the application of probabilistic methods in bioinformatics, particularly in systems biology. Professor Bourdon's work spans from Number Theory to Systems Biology with a common thread of developing and using probabilistic tools. His main research activities include dynamical analysis of algorithms and systems biology modeling, where he has developed the transition event graph model to integrate quantitative and qualitative biological data. Professor Bourdon's recent publications demonstrate consistent output in high-impact journals including Nature Communications, PLOS Computational Biology, and BMC Systems Biology, with research trends showing increasing focus on metabolic network analysis, multi-omics data integration, and constraint-based modeling approaches. Academic Editor for PLOS One Co-chair of CMSB 2015 international conference Member of Biogenouest scientific council (2004-2017) Co-scientific responsible for BiRD bioinformatics platform Professor Bourdon has secured significant research funding including the 1.4M€ GRIOTE project and participation in multiple ANR/CNRS projects. He has supervised 9 PhD students, typically through co-direction arrangements, reflecting his collaborative research approach. His ComBi group consists of 12 members including professors, assistant professors, PhD students, post-docs, and engineers, working on diverse topics in bioinformatics and computational biology. The ComBi research group, led by Professor Bourdon since 2014, focuses on combinatorics and bioinformatics with activities centered around comparative genomics and systems biology. The group provides a collaborative environment for interdisciplinary research at the intersection of computer science and biology, with strong connections to biological research teams and access to computational resources through the BiRD platform.

• Laser Technology
• Optics
• Biophotonics
• +۴ مورد دیگر

Prof. Maria Dienerowitz is a Professor at Ernst Abbe University of Applied Sciences Jena specializing in laser technology and biophotonics. She teaches core courses including Laser Technology, Quantum Optics, and Vacuum Technology across Bachelor's and Master's programs while leading three major research initiatives: BioLOC (Carl-Zeiss-Stiftung-funded Lab-on-a-Chip system for molecular dynamics), OPTO (historical spectacle lens analysis with the German Optical Museum), and TOOLS (DFG-funded tailored optics for life sciences). Her research centers on advanced optical manipulation techniques including the ABEL trap for single-molecule studies without surface binding and holographic optical tweezers for nanoparticle control. Key focus areas encompass real-time enzyme kinetics of molecular motors like F-ATP synthase, single-molecule FRET dynamics , and nanoparticle characterization in biological contexts. This work bridges fundamental physics with biomedical applications through innovations in trapping methodology and optical instrumentation. Analysis of her 15 most recent publications reveals strong continuity in optical trapping methodologies with increasing biomedical applications since 2020. Her work demonstrates consistent contributions to single-molecule biophysics (particularly molecular motor studies), nanoparticle manipulation , and optical instrumentation development , with growing emphasis on life science interfaces evident in her Carl-Zeiss-Stiftung and DFG-funded projects. Prof. Dienerowitz currently oversees a research team comprising scientific staff members working across the BioLOC, OPTO, and TOOLS projects, including Dr. Jakub Malohlava (TOOLS), Maryam Shahrezaei (BioLoc), and Frederic Braun (TOOLS). Her laboratory infrastructure supports optical trap development, nanoparticle characterization, and molecular dynamics studies through equipment funded by the Carl-Zeiss-Stiftung and German Research Foundation.

Thomas Sloanمشاهده پروفایل

دانشیار

• Operations Management
• Sustainable Operations
• Supply Chain Sustainability
• +۵ مورد دیگر

Thomas Sloan serves as an Associate Professor in the Operations and Information Systems Department at the University of Massachusetts Lowell's Manning School of Business. He coordinates the M.S. Business Analytics program and teaches courses including Global Supply Chain Management and Introduction to Business Analytics. His research bridges operations management with sustainability challenges across multiple industries. Education: Ph.D. in Management Science, University of California Berkeley M.S. in Operations Research, University of California Berkeley B.B.A. in Operations Management, University of Texas at Austin Sloan's research integrates environmental considerations into traditional operations frameworks, with significant contributions to sustainable supply chains, medical device reprocessing, and green equipment maintenance. His work demonstrates consistent focus on balancing economic, environmental, and safety factors across diverse operational contexts. Recent publications examine pandemic-era supply chain disruptions and multi-criteria decision approaches for industrial solvent selection. Scientific Recognition: Teaching Excellence Award (2013) from UMass Lowell Operations and Information Systems Department Exceeding Excellence Teaching Award (2009) from UMass Lowell Student Government Association Sloan actively contributes to educational innovation through technology implementation projects including the UML Echo360 Lecture Program and ForClass Application pilot studies. His professional service spans university committees (NEASC Reaccreditation, Climate Action Plan), department leadership roles, and professional societies including INFORMS, POMS, DSI, and APICS where he serves as faculty advisor for the OIS Club. His research grants focus on enhancing student engagement in supply chain management education through digital tools.