جست‌وجوی استاد و پژوهشگر

Muhammed Kotanمشاهده پروفایل

استادیار

• Artificial Intelligence
• Computer Software
• Image Processing
• +۱۳ مورد دیگر

Muhammed Kotan is an Assistant Professor at the Department of Information Systems Engineering , Sakarya University , where he has served since 2022. His academic career includes roles as a Research Assistant (2011–2022) at Sakarya University and Afyon Kocatepe University. He holds a PhD in Computer and Information Engineering (2020), an MSc in Computer and Information Engineering (2014), and a BSc in Computer Engineering (2011) from Sakarya University. Research Interests : Artificial Intelligence, Computer Software, Image Processing, Machine Learning, Computer Vision, Medical Imaging, Energy Efficiency Optimization, Natural Language Processing, Sentiment Analysis, Feature Selection, 3D Reconstruction, Industrial Machine Detection, Optimization Algorithms, Real-Time Systems, User Reviews Analysis, E-Commerce Analytics. Key Contributions : Developed hybrid methods for 3D reconstruction and industrial machine defect detection, optimized tow train routing in manufacturing, and applied Marine Predators Algorithm for mental health screening. Scientific Recognition : Awarded the Eğitim Öğretimde Üstün Başarı Ödülü by Sakarya University (2024). Served as editor for the Sakarya University Journal of Computer and Information Sciences (2023–2024) and peer reviewer for journals like Signal, Image and Video Processing and Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi . Advising : Co-advisor for TÜBİTAK projects (2022–2024) and supervised student research on topics like cosmetic product recognition, natural language processing, and sentiment analysis. Designed courses in Digital Image Processing, Text Mining, and Advanced Information Systems.

Sascha Weberمشاهده پروفایل

پژوهشگر

• 3D Eye Tracking
• Eye Movement Algorithms
• Visual Attention Analysis
• +۳ مورد دیگر

Sascha Weber is a researcher affiliated with the Institute of Psychology III at Dresden University of Technology. He specializes in engineering psychology and cognitive ergonomics, focusing on advanced eye-tracking technologies in both real-world and virtual environments. Current research emphasizes algorithms for determining eye movements in 3D space. Develops applications for visual attention analysis using stereoscopic visualization systems. Collaborates on projects like FAIR and COGAIN, integrating eye-tracking with augmented reality and communication technologies. His work bridges cognitive science with technological innovation, particularly in virtual and augmented reality systems. Key projects include FSGazeTrack for driving simulators and 3D software prototypes for strabismus treatment. Selected Collaborations: FAIR: Hands-free augmented reality applications with TU-Dresden, Interactive Minds GmbH, and others COGAIN: European Commission-funded network for gaze interaction communication

• Educational Technologies
• Instructional Design
• Virtual Reality in Education
• +۵ مورد دیگر

Dr. Kadir Yücel KAYA serves as an Assistant Professor in the Department of Educational Sciences at Kastamonu University's Faculty of Education, Turkey, a position held since 2019 after progressing from Research Assistant roles at Kastamonu University (2017-2019) and Middle East Technical University (2009-2017). His academic trajectory spans multiple institutions and disciplines within educational technology. His educational background includes: PhD in Computer and Instructional Technologies Education, Middle East Technical University (2018) Bachelor's in Computer Education and Educational Technologies, Middle East Technical University (2009-2018) Bachelor's in Computer Education and Educational Technologies, Dokuz Eylül University (2005-2009) Bachelor's in Sociology (Open Education), Istanbul University (2020) KAYA's research centers on educational technology integration, with particular emphasis on immersive learning environments. His work explores virtual reality applications for climate change education, serious games for pedagogical enhancement, and artificial intelligence implementations in academic settings. He investigates motivational aspects of digital video creation and examines historical educational movements like Turkey's Village Institutes through technological lenses. Analysis of his 2021-2025 publications reveals a pronounced shift toward immersive technologies (VR/metaverse) in environmental education, alongside sustained focus on open educational resources and digital competence frameworks. His scholarship increasingly addresses climate change pedagogy through technological mediation while maintaining foundational work in programming education and MOOC ecosystems. While no major scientific awards are documented, KAYA actively contributes to academic service through TÜBİTAK-funded research on climate change-oriented virtual reality design (2024). He has taught diverse courses including Serious Games, Digital Competence, and AI Applications in Education, though he has not supervised graduate students to date. His collaborative network centers around S. Tısoğlu-Kaya and K. Çağıltay, with significant contributions to national instructional technology discourse. Current academic service includes Erasmus University Coordinator Assistant duties (2023-present) following previous Erasmus Faculty Coordinator responsibilities (2020-2023).

Alexandra Jahnمشاهده پروفایل

دانشیار

• Climate Modeling
• Cryosphere
• Oceanography
• +۶ مورد دیگر

Alexandra Jahn is an Associate Professor in the Department of Atmospheric and Oceanic Sciences at the University of Colorado Boulder. She leads the Polar & Paleoclimate Modeling Group, focusing on Arctic climate dynamics, paleoclimate modeling, and climate model evaluation. PhD from McGill University (2010) Dipl. from Free University of Berlin (2004) Exchange Student at University of Washington (2001) Her research integrates climate modeling and observational data to study polar regions, emphasizing Arctic sea ice variability, ocean circulation changes during glacial periods, and isotope modeling. Current projects examine natural vs. forced climate trends in the Arctic, commercial shipping accessibility projections, and paleoceanographic transitions during deglaciation. Recent publications analyze Arctic sea ice dynamics under different emission scenarios, paleoceanographic changes during glacial periods, and model-data comparison improvements. Her work reveals trends in CMIP6 forcing uncertainties, Arctic freshwater dynamics, and North Pacific deep water formation during warm periods. Alexander von Humboldt Fellowship (2022) NSF CAREER Award (2019) NCAR Postdoctoral Fellowship (2012) German National Academic Foundation Fellowships (2001, 2006) Alexandra mentors graduate students and postdocs in climate modeling, oceanography, and Arctic research. She teaches courses in climate science, physical oceanography, numerical methods, and scientific writing. Her lab connects climate models with paleo records to understand past and future climate changes.

Ricardo Henaoمشاهده پروفایل

دانشیار

• Machine Learning
• Biostatistics
• Precision Medicine
• +۷ مورد دیگر

Ricardo Henao is an Associate Professor of Biostatistics & Bioinformatics, Associate Professor in Surgery, and Assistant Professor in the Department of Electrical and Computer Engineering at Duke University. He is also a core member of the Duke Clinical Research Institute, the Duke Center for Applied Genomics and Precision Medicine, and the Duke Center for Statistical Genetics and Genomics. Education: Ph.D., Technical University of Denmark, 2011 Research Interests: Henao’s research integrates advanced machine learning with high-impact clinical and biological questions. His work spans infectious-disease diagnostics (including rapid host-response assays for bacterial vs viral infection), cardiovascular genomics and risk prediction, precision-medicine toolkits for transplant recipients, ophthalmic AI for retinal and cardiac imaging, and fairness-aware AI to ensure equitable healthcare delivery across demographic groups. Publications Trend: Across >317 peer-reviewed publications (2013–2025), a clear trajectory emerges from foundational statistical methodology to large-scale translational implementations. Recent 2025 papers emphasize automated harmonization of electronic health records, fairness-constrained predictive models for stroke risk, computer-vision systems for point-of-care echocardiography, and deep-learning segmentation of pulmonary vasculature—demonstrating a fusion of NLP, computer vision, and survival modeling to solve real clinical problems. Scientific Awards & Honors: While the supplied text does not list specific named awards, Henao’s funding portfolio serves as a proxy for recognition: he is PI or multi-PI on >34 active grants totaling tens of millions of dollars from NIH, NHLBI, NIAID, NSF, DoD, and private foundations such as Brigham and Women’s Hospital and the Henry M. Jackson Foundation. Advising & Grants: Henao mentors trainees at the intersection of data science and medicine. Current grant titles illustrate the breadth of mentee opportunities: PREEMPT: Prospective Randomized Evaluation and Management of Premature Atherosclerosis (NIH, 2025–2032) Machine Learning Guided Precision Genetic Testing for Monogenic Cardiovascular Disorders (NHLBI, 2024–2028) Synthesizing immunoinformatics and genetic epidemiology for malaria immunity signatures (NIAID, 2023–2028) NSF CC* Integration-Large: Scaling scientific workloads on distributed commodity GPUs (NSF, 2025–2027) Improving quality of life in SLE via stratified personalized health planning (DoD, 2022–2026) Multidisciplinary study of biological disparities in NASH progression (DoD, 2020–2025) Rapid point-of-care host gene-expression test for pre-symptomatic viral infection (DoD, 2021–2024) Clinical and molecular epidemiology of high-risk coronary plaque (NIH, 2019–2024) Labs & Teams: Henao leads the Division of Translational Biomedical Informatics within the Department of Biostatistics & Bioinformatics and participates in Duke’s Bass Connections and Data+ programs, embedding graduate and undergraduate students in interdisciplinary teams that span genomics, cardiology, surgery, and global health.

Alfredo Camara Casadoمشاهده پروفایل

مدرس ارشد

• Structural Engineering
• Earthquake Engineering
• Bridge Engineering
• +۵ مورد دیگر

Alfredo Camara Casado is a Senior Lecturer (Profesor Titular de Universidad) at the Polytechnic University of Madrid, affiliated with the Department of Continuous Mechanics and Structural Theory. His research focuses on structural dynamics, seismic analysis, and wind-vehicle-bridge interactions, with a particular emphasis on multi-hazard scenarios involving earthquakes, wind, and live loads. He holds a Doctor of Engineering degree and is a member of the Computational Mechanics Group and the Ignacio da Riva University Institute of Microgravity (IDR). His work addresses innovative methods for bridge design, analysis of cable-stayed bridges under seismic and wind loads, and vibration control using tuned mass dampers and rocking isolation techniques. His recent publications highlight trends in asymmetric bridge dynamics (2024), spatial ground motion variability in cable-stayed bridges (2024), skew wind effects on traffic safety (2023), and advanced modeling of rocking piers (2022). Key subfields include earthquake engineering, wind-vehicle interactions, computational mechanics, and structural stability. As a Senior Lecturer, he contributes to teaching and research in structural engineering. His collaborations span institutions like ETH Zurich and Tongji University, focusing on seismic resilience, renewable energy structures, and computational modeling. Current projects involve dynamics of slender bridges, soil-structure interaction, and aerodynamic damping.

• Computational Structural Biology
• Drug Discovery
• Molecular Docking
• +۵ مورد دیگر

Robert C. Rizzo is a Professor in the Department of Pharmacological Sciences at Stony Brook University, specializing in Computational Structural Biology. With an extensive publication record spanning over two decades and significant citation metrics (6979 total citations, h-index of 36), his research has made substantial contributions to the field of computational drug discovery. Dr. Rizzo's research interests center on computational methods for drug discovery, particularly the development and application of the DOCK software platform for molecular docking and structure-based drug design. His work spans multiple therapeutic areas including cancer (particularly prostate cancer), viral infections (HIV, Ebola, Zika, SARS-CoV-2), and other conditions where computational approaches can identify novel therapeutic targets and compounds. His expertise encompasses protein-ligand interactions, virtual screening, de novo drug design, and the development of algorithms for molecular modeling. Analysis of his recent publications reveals a strong focus on advancing computational methodologies for drug discovery, with particular emphasis on the DOCK software platform. His work demonstrates consistent innovation in molecular docking algorithms, scoring functions, and structure-based design approaches applied to diverse biological targets. The research shows a progression from fundamental method development to application against specific disease targets, particularly in oncology and infectious diseases. Dr. Rizzo has received significant recognition in his field as evidenced by his substantial citation record, though specific awards are not detailed in the available information. His work has contributed to advancing computational approaches in drug discovery, with applications across multiple therapeutic areas. His research program involves substantial computational work, likely supported by grants from major funding agencies in computational biology and drug discovery. While specific grant information isn't provided, the scope and continuity of his publication record suggest sustained research funding.

• Educational Psychology
• School Improvement
• Evidence-Based Education
• +۵ مورد دیگر

Dr. Anabel Bach is a Researcher in the Department of Education and Psychology at Free University of Berlin, affiliated with the Institute of School Pedagogy and School Improvement Research . Since 2015, she has focused on evidence-based educational governance, teacher training, and collaborative learning mechanisms. Diploma in Psychology (2011) and Doctorate in Education and Psychology (2018), both from Free University of Berlin Her research examines school improvement strategies , evaluation policies , and teacher collaboration . Key projects include K2teach (video-based learning), SteBis (governance), and StABil (evaluation practices). Recent publications analyze collaborative online learning , problem-based learning questionnaires , and data-driven school policies . She has presented internationally on low-stakes testing and school-based staff development . Her work integrates educational psychology , organizational theory , and policy analysis to enhance teacher competencies and school effectiveness. Dr. Bach's methodological expertise includes survey development , questionnaire validation , and empirical educational research . She has contributed to technical reports for the StABil project and collaborated with institutions like Humboldt University Berlin.

Marth Labمشاهده پروفایل

استاد

• Computational Genomics
• Rare-Disease Diagnostics
• Precision Oncology
• +۷ مورد دیگر

The Marth Laboratory at the University of Utah Medical School is a leading computational genomics group focused on rare-disease diagnostics, precision oncology, and somatic mosaicism discovery. Affiliated with the Utah Center for Genetic Discovery and Department of Human Genetics , the lab develops tools like gene.iobio and RUFUS for variant analysis and clinical interpretation. Research Interests: Developing reference-free k-mer variant detection algorithms Machine learning for phenotype-driven patient matching in rare diseases Precision oncology through tumor omics integration Somatic mosaicism mapping across human tissues Interactive genomic visualization tools for clinical use Software Highlights: gene.iobio - Real-time variant annotation clin.iobio - Clinical variant review RUFUS - De novo variant calling superseeker - Tumor clone reconstruction

Marika Kieferovaمشاهده پروفایل

مدرس ارشد

• Quantum Computing
• Quantum Algorithms
• Quantum Simulation
• +۳ مورد دیگر

Marika Kieferova is a Senior Lecturer at the School of Computer Science, University of Technology Sydney (UTS), and a researcher at the UTS Centre for Quantum Software and Information (QSI). She previously held a postdoctoral position at UTS and earned her PhD in Physics and Astronomy from the University of Waterloo (2019) with a cotutelle from Macquarie University. Research Interests Her work spans quantum computing, quantum simulation, and quantum information theory. Key areas include developing quantum algorithms for Hamiltonian simulation, error mitigation strategies, and entanglement-induced optimization challenges in quantum neural networks. She explores non-Abelian anyon braiding, engineered dissipation for correlated states, and bound states of interacting photons in superconducting qubit arrays. Article Trends Her recent publications focus on quantum dynamics in many-body systems, error suppression techniques, and algorithmic advancements. Topics include phase transitions in random circuits, superdiffusive quantum transport, and randomized multi-product formulas for efficient simulation. These works highlight her contributions to quantum chemistry, topological quantum computing, and NISQ-era applications. Scientific Awards QIP Best Poster Award (2020) IQC Achievement Award (2019) Grants and Leadership She leads the QB-suite grant for quantum algorithm design (2024-2027) and contributes to defense quantum optimization projects (2021-2024). She serves as an associate editor for Quantum Science and Technology and participates in peer review for Physical Review A.

Albert A. Smith-Penzelمشاهده پروفایل

پژوهشگر

• Biomolecular Dynamics
• NMR Spectroscopy
• Molecular Dynamics Simulation
• +۳ مورد دیگر

Dr. Albert A. Smith-Penzel is a Principal Investigator at the Institute for Medical Physics and Biophysics , University of Leipzig Medical Faculty . He leads a DFG-funded project titled "Disentangling dynamics in biomolecules with experiment and simulation" since 2021, following his 2019-2020 Research Associate position at the same institution. B.Sc. in Physics, University of Mount Union (2007) Ph.D. in Chemistry, Massachusetts Institute of Technology (2012) Postdoctoral Researcher at ETH-Zürich (2012-2018) His research focuses on biomolecular dynamics characterization through advanced NMR relaxation techniques combined with molecular dynamics simulations. He pioneered detector analysis methods for correlating experimental and computational dynamics data, addressing challenges in motion amplitude quantification across multiple timescales. Recent publications highlight his work on: Dynamic landscapes of bio-membranes Energy landscapes of GPCRs Model-free analysis of protein fibrils Software development for NMR analysis (INFOS, DIFRATE) He actively develops open-source tools for dynamics analysis and contributes to understanding how distributed motions influence macromolecular function.

• Programming Languages
• Operating Systems
• Artificial Intelligence
• +۳ مورد دیگر

Christopher League is an Associate Professor of Computer Science at Long Island University. His research focuses on programming languages, operating systems, and artificial intelligence, with specialties in compilers, type theory, and computer security. His educational background includes: B.S. from Johns Hopkins University M.S. from University of Maryland, College Park Ph.D. from Yale University Professor League is dedicated to making software development more secure, convenient, and fun. He collects programming languages, studies next-generation features, and helps students comprehend the foundations of computing. His research spans a wide range of topics in computer science, including Programming Languages , Operating Systems , and Artificial Intelligence . He has a particular interest in the theoretical aspects of programming such as type theory and compilers , as well as practical applications in computer security . His recent publications reflect a diverse set of interests, from AI education and XML data compression to staged computation and type systems in object-oriented programming. The work shows a consistent theme of improving software development through language design and security. His awards include: Award for Teaching Excellence from the University of Maryland (1996) IBM Outstanding Undergraduate Award from Johns Hopkins University (1995) Information about Professor League's current advisees and research grants is not provided in the available text. Professor League contributes to various free and open-source software projects and is an active member of professional societies including ACM (SIGPLAN and SIGCSE) and IEEE Computer Society.

Rafał Próchniakمشاهده پروفایل

پژوهشگر

• Peer Production
• Property Rights
• Intellectual Property
• +۴ مورد دیگر

Rafał Próchniak is an academic researcher focused on digital economies, legal frameworks for technology, and peer production models. His work bridges economics, law, and sociology in the context of information societies. Specializes in peer production, intellectual property rights, and software licensing Supervision interests: Evolution of copyright, networked information economies, collaborative governance Notable Research Themes: Impact of free software on societal development Comparative analysis of digital governance (Poland vs. Germany) Critique of copyright law in the digital age Intersection of market structures and decentralized production Publications: 5 works (2004-2007) analyzing e-commerce regulation, e-government development, and intellectual property reform.

• Milk production
• Fertility in cows
• Reproduction in dairy cattle
• +۲ مورد دیگر

Prof. Dr. Wolfgang Heuwieser is a faculty member at the Free University of Berlin , specializing in Veterinary Medicine with a focus on Milk production, Fertility in cows, and Reproduction . He works at the Veterinary Clinic for Reproduction , where his research and clinical practice address critical aspects of dairy cattle health and reproductive efficiency. His research interests include Bovine Reproductive Health , Dairy Cow Fertility , and Animal Health Management . Heuwieser's work integrates advanced technologies such as automated activity monitoring , point-of-care diagnostics , and computer vision systems to optimize reproductive outcomes and general wellness in dairy cattle. Recent publications highlight his expertise in Hormonal Treatments , Heat Stress Impact , and Calving Management . His studies span 2017 to 2025 , reflecting ongoing contributions to veterinary science and dairy farming practices. Heuwieser can be contacted via email at w.heuwieser@fu-berlin.de for collaborations, expert consultations, or further information about his research projects.

Pavlos Petoumenosمشاهده پروفایل

استادیار

• Compiler Optimization
• Runtime Systems
• Energy Efficient Computing
• +۶ مورد دیگر

Pavlos Petoumenos is a Lecturer (Assistant Professor) in the Department of Computer Science at the University of Manchester and a Research Fellow of the Royal Academy of Engineering. He leads research within the Advanced Processor Technology (APT) group, focusing on compiler optimization and energy-efficient computing. Previously, he worked as a Research Associate and Senior Researcher at the University of Edinburgh under Hugh Leather. His research centers on compilers, runtime systems, and development tools designed to help programmers write fast, energy-efficient programs with minimal effort. With electronic systems consuming 10% of global electricity (projected to reach 20% by 2030), his work addresses the critical challenge of bridging the complexity gap between programmers and modern energy-efficient hardware. Key research areas include compiler optimization, machine learning applications in compilation, code size reduction, and quantum-classical programming integration. His recent publications reveal strong trends in applying machine learning to compiler optimization, particularly through active learning techniques and deep learning models. The research spans multiple domains including function merging, branch fusion, loop transformations, and energy profiling, with significant contributions to quantum programming language design. His work consistently targets real-world applications in multicore processors and interactive mobile environments. Award highlights include: Best Paper Award at CGO 2019 Distinguished Paper Award at ISSTA 2018 Best Paper Award at PACT 2017 Best Paper Award at CGO 2017 Best Paper Award at IISWC 2014 Royal Academy of Engineering Research Fellowship Petoumenos actively contributes to the research community through mentoring PhD students, organizing the biennial International Workshop on Code Optimisation for Multi and Many-Cores (COSMIC), and co-hosting the Compucast podcast where he serves as chief editor. His collaborations span multiple institutions including the University of Edinburgh, University of Lancaster, and University of St Andrews. He has secured significant research impact through tools like BenchPress and F3M that address practical challenges in compiler design and optimization. He leads the Advanced Processor Technology group and contributes to the Compucast podcast, which features interviews with computer science researchers, academic and industry news, and technical discussions. The podcast represents a collaboration between multiple UK universities and serves as an important outreach platform for computer science research.