جست‌وجوی استاد و پژوهشگر

Michael Welzlمشاهده پروفایل

استاد

• Network Congestion Control
• Internet Transport Protocols
• Recursive Networking Architecture (RINA)
• +۷ مورد دیگر

Michael Welzl is a Full Professor in the Networks and Distributed Systems group at the Department of Informatics , University of Oslo. He is also involved with Netflix from March to September 2025 at a varying percentage. Research Interests: Network congestion control, transport protocols, recursive networking (RINA), multipath TCP, data center networking, and machine learning applications in networking. Scientific Awards: 2024: Outstanding paper award, Usenix NSDI 2024: Community award, Usenix NSDI 2018: Best of workshop presentation award 2017: Best Paper Award, IFIP NETWORKING 2016: Best Paper Award, IEEE IMCEC 2014: Best Paper Award, ACM SIGCOMM CSWS 2007: University of Innsbruck Recognition Award 2004: GI/ITG KuVS Award 2003: NATWI-Award for Young Researchers Ph.D. Students: Wen Cai (ongoing: Internet sustainability) Jie Bian (ongoing: NLP in IETF) Kristjon Ciko (defended 2022: RINA architecture) Runa Barik (defended 2020: Middlebox impact) Safiqul Islam (defended 2017: Congestion control coupling) Humaira Ijaz (defended 2016: P2P peer selection) Sven Hessler (external: Congestion control on UDP) Simone Ferlin (defended 2017: Multipath TCP) Recent Publications focus on energy-efficient networking, protocol design, machine learning for networking, and internet architecture. Key topics include TCP packet loss prediction, in-network performance enhancements, and edge AI challenges.

Gidon Ernstمشاهده پروفایل

استادیار

• Formal Methods
• Software Verification
• Software Testing
• +۵ مورد دیگر

Gidon Ernst is a Junior Professor (Assistant Professor) for Software Verification at the Department of Computer Science, LMU Munich, where he leads research in the Software and Computational Systems Lab. His work focuses on formal methods for software engineering, with particular emphasis on verification, testing, and security analysis of complex systems. His research interests span formal methods for software engineering, software testing, interactive and automated proofs, hybrid systems, and falsification. Ernst's work addresses challenges in relational proofs for substitution principle, software testing with Legion (a tool combining concolic execution and fuzzing), concurrent information flow security with SecCSL and SecC, and falsification of temporal logic requirements for hybrid systems. His approach often combines theoretical foundations with practical tool development. Ernst's publication record shows a strong focus on verification of security properties, particularly information flow security in concurrent systems, and falsification of hybrid systems. His recent work has advanced techniques for adaptive probabilistic search in falsification, compositional vulnerability detection, and contract-based software specification. He actively contributes to the verification community through competitions like VerifyThis and ARCH. Best Master Lecture 2022 in Computer Science (awarded by Gruppe Aktiver Fachschaftika) Ernst has supervised PhD student Dongge Liu on software fuzzing with machine learning (2018-2022), co-supervised with Toby Murray and Ben Rubinstein from the University of Melbourne. His teaching includes courses on formal specification and verification, methods in software engineering, and various seminars on software quality assurance and deductive verification. He has also served on numerous program committees and organized major verification events including SPIN 2025 and the VerifyThis challenge series. Ernst maintains active collaborations with researchers worldwide, particularly in the areas of hybrid systems verification (with Ichiro Hasuo, Sean Sedwards, and Zhenya Zhang) and information flow security (with Toby Murray). His work bridges theoretical computer science with practical software engineering challenges, developing tools that have seen adoption in both academic and industrial settings.

Santosh Pandeمشاهده پروفایل

استاد

• Compiler Analysis
• Software Optimization
• Hardware Security
• +۶ مورد دیگر

Santosh Pande is a Professor and Associate Chair for Graduate Studies at the School of Computer Science , Georgia Institute of Technology. He is affiliated with the Center for Experimental Research in Computer Systems (CERCS) and the Online Master of Science Computer Science (OMSCS) program. His research focuses on compiler analysis and optimizations, particularly in enhancing software properties through static and dynamic analysis. Key areas include hardware security (e.g., side-channel attacks on secure processors), real-time systems (converting interactive software behavior into quantifiable metrics), and parallel computing (optimizing SAT solvers and GPU scheduling). His work bridges compiler design with security, embedded systems, and machine learning, supported by grants from NSF, ONR, DARPA, and industry. Research Highlights: Side-channel attack mitigation on XOM secure processors Framework for soft real-time software analysis Compiler-guided security defenses (e.g., Pythia, Decker) High-performance RF emulation architectures His publications emphasize compiler-driven security, real-time computing, and algorithmic optimization. Over 100+ papers and open-source tools reflect his commitment to advancing compiler theory and practice. Current projects apply these techniques to machine learning algorithms, enhancing their efficiency and security.

• Computational Chemistry
• Molecular Modeling
• Force Field Development
• +۳ مورد دیگر

Toon Verstraelen is an Associate Professor at Ghent University, Belgium, specializing in computational chemistry and molecular modeling. His research focuses on the development of force-field models, atoms-in-molecules schemes, and polarizable force fields, with additional expertise in scientific software development. Verstraelen's research interests span across computational chemistry, with particular emphasis on: Force-field model development for accurate molecular simulations Atoms-in-molecules partitioning schemes for charge analysis Polarizable force fields that capture electronic response properties Machine learning potentials for materials science applications Software development for quantum chemistry and molecular modeling Analysis of Verstraelen's recent publications (2022-2024) reveals a strong focus on advancing computational methods in chemistry. His work demonstrates growing integration of machine learning techniques with traditional quantum chemistry approaches, particularly in developing more accurate force fields and potentials. Key research areas include metal-organic frameworks, zeolites, and reactive systems, with applications spanning materials science, catalysis, and environmental chemistry. His publications show consistent contributions to methodological advancements in computational chemistry, with increasing emphasis on software tools that make these methods accessible to the broader scientific community. Verstraelen maintains active research collaborations with institutions worldwide, including McMaster University (Canada), KU Leuven and VUB (Belgium), Eindhoven University of Technology (Netherlands), Pennsylvania State University (USA), and Université de Lille (France). His work has resulted in numerous software contributions to the computational chemistry community, including HORTON, Yaff, QuickFF, and other tools that facilitate molecular modeling and simulation.

Jasper Fuchsمشاهده پروفایل

مدرس

• Forest Economics
• Climate Change Impacts
• Bioeconomic Modeling
• +۲ مورد دیگر

Jasper Fuchs is Lecturer at ETH Zurich's Department of Environmental Systems Science, where he researches climate impacts on forest ecosystems and sustainable resource management. He holds a PhD in Forest Sciences from the University of Göttingen (2024), an MSc in Forest Sciences (2018), and a BSc in Forest Sciences (2016) from the same institution. His research integrates economic and ecological approaches to address: Climate-adaptive forest management strategies Bioeconomic modeling of silvicultural systems Optimization of tree species portfolios under disturbance risks Development of R-based tools for forest decision-making Recent publications demonstrate strong focus on: Multifunctional forest management under climate change Economic valuation of biodiversity-ecosystem tradeoffs Advanced 3D modeling for treatment optimization Risk quantification in forest economics Awards and honors include: Gerhard Speidel Award for outstanding forest economics research (2024) Sayn-Wittgenstein Forestry Award (2019) German National Academic Foundation membership (2016) He supervises graduate theses on forest conversion economics, bark beetle management, and diversification strategies. Current projects include EU COST Action CA22141 on ecosystem service decision support systems and FunPotential (Biodiversa) on functional diversity for forest resilience.

• Transportation and Freight Services
• Artificial Intelligence and Image Processing
• Automotive Engineering
• +۳ مورد دیگر

Felix Feng is a Research Fellow and Manager of the Intelligent Infrastructure and Transport Systems (IITS) Laboratory at Imperial College London's Department of Civil and Environmental Engineering. His work focuses on developing configurable automotive system models for autonomous vehicle safety validation and simulating interactions with road users. He holds a PhD in Mechanical Engineering (University of Bath, 2019), an MSc in Mechatronics (University of Bath, 2014), and a BEng in Mechatronics (Tongji University, 2013). Education: PhD in Mechanical Engineering, University of Bath (2015–2019) MSc in Mechatronics Engineering, University of Bath (2013–2014) BEng in Mechatronics Engineering, Tongji University (2009–2013) His research interests span autonomous vehicles , artificial intelligence , transportation systems , and control systems . Notable projects include driver model development using machine learning and safety validation frameworks for autonomous systems. His recent work explores multimodal traffic prediction, digital twin simulations, and reinforcement learning applications in urban logistics. Publications highlight advancements in traffic risk modeling, GNSS fault detection, and smart infrastructure solutions. Felix’s contributions address challenges in autonomous vehicle interaction safety, urban mobility optimization, and resilient air traffic networks. His IITS Lab at Imperial focuses on translating cutting-edge research into practical tools for safer, smarter transportation ecosystems.

Adam Piggottمشاهده پروفایل

دانشیار

• Geometric Group Theory
• Groups presented by rewriting systems
• Automorphism groups of groups
• +۴ مورد دیگر

Adam Piggott is an Associate Professor and First-year Coordinator at the Mathematical Sciences Institute (MSI) of The Australian National University (ANU). He holds a D.Phil. in Mathematics from the University of Oxford and has extensive experience in teaching undergraduate mathematics within liberal arts frameworks, having worked in the USA for 13 years before returning to Australia in 2018. His research focuses on geometric group theory, rewriting systems, and automorphism groups of groups, with notable contributions to geodetic groups and algorithmic group theory. Affiliations: First-year Coordinator (ANU), Former positions at University of Queensland and Bucknell University Education: B.Math (Honours First Class), B.CompSci – University of Wollongong D.Phil. Mathematics – University of Oxford (2005) Research Interests: Adam specializes in geometric group theory, particularly exploring groups defined by rewriting systems and automorphism groups. His work bridges algebraic structures with geometric and computational methods, with recent focus on geodetic properties of groups and graphs. He also investigates interdisciplinary education initiatives, such as assessment frameworks and programming education in STEM contexts. Recent Research Trends: His publications span foundational group theory (geodetic graphs, rewriting systems) and educational innovations (authentic assessment, programming pedagogy). Collaborations include projects on PSPACE complexity in group detection and interdisciplinary science course impacts. Grants/Projects: Geodetic groups: foundational problems in algebra and computer science (2021–2024) Teaching Contributions: Leads first-year mathematics coordination at ANU, emphasizing equitable assessment practices and student belonging through initiatives like GPAM grading and formative assessment strategies. Labs/Teams: Engaged with ANU’s MSI research community, contributing to collaborative projects in algebraic structures and educational technology.

• Robotics in Gastronomy
• Educational Spaces Design
• Vocational Education Didactics
• +۴ مورد دیگر

Prof. Birgit Peuker is a Professor of Nutrition and Home Economics at the European University Flensburg, serving as Dean of Studies for Faculty I. She holds a PhD from TU Dresden (summa cum laude) and has over 15 years in vocational education research. Her work focuses on integrating digitalization, robotics, and AI into gastronomy and home economics education, emphasizing interprofessional collaboration and sustainable practices. Education : 2001–2008: Diploma in Vocational Education, TU Dresden (specializing in Food Science and Ethics) 2015: PhD, TU Dresden ("The Teaching Kitchen as a Space for Career Orientation") Research Interests : Robotics in hospitality, educational space design (7 dimensions framework), cultural competency in home economics, and consumer literacy for vulnerable learners. Key projects include the BiLEV initiative on agricultural education and the Interreg GERDA sustainability project. Publications : Over 30 peer-reviewed articles and books, including works on AI-driven gastronomy, interprofessional care, and innovative educational spaces. Notable publications include Forschendes Lernen in der Universität (2023) and Grundbildung in der Lebenswelt verankern (2022). Grants & Awards : Lead researcher in EU-funded projects (e.g., FRESH, GERDA). Awarded summa cum laude for doctoral work. Active in academic governance roles including Senate committees and the German Home Economics Society. Labs & Initiatives : Directs the CREST research center's education projects. Co-convenes the Summer School for Nutrition Education, fostering cross-university collaboration in didactics.

Selvi Karaمشاهده پروفایل

استادیار

• Commutative Algebra
• Algebraic Combinatorics
• Graph Theory
• +۳ مورد دیگر

Selvi Kara is an Assistant Professor of Mathematics at Bryn Mawr College. Her research focuses on Commutative Algebra and Algebraic Combinatorics, with particular emphasis on algebraic structures such as edge ideals, toric rings, and graph-theoretic applications. She holds a PhD in Mathematics and has contributed to advancements in algebraic invariants, combinatorial optimization, and computational algebra. Her work bridges abstract algebra with applied domains like remote sensing for agricultural pest monitoring. She has developed software tools such as the MorseResolutions package for Macaulay2, enhancing computational methods in algebraic geometry. Kara’s research also explores interdisciplinary topics including Stirling permutations, flow-firing dynamics, and rigid Gorenstein varieties derived from directed graphs. Publications span theoretical contributions (e.g., minimal cellular resolutions, multi-Rees algebras) and applied studies (e.g., satellite imagery analysis for crop monitoring). Her research demonstrates a strong focus on algebraic combinatorics with both pure and applied dimensions. Advising and grants: No specific advisees or grants listed in available records. Active participation in collaborative research projects such as LEAPS-MPS initiatives. Engaged in educational outreach through Bryn Mawr’s graduate programs. Labs/Teams: Collaborates with interdisciplinary teams in algebraic geometry, computational mathematics, and applied remote sensing research.

Anthony Kleerekoperمشاهده پروفایل

مدرس ارشد

• Databases
• Data Science
• Machine Learning
• +۵ مورد دیگر

Dr Anthony Kleerekoper is a Senior Lecturer in the Department of Computing and Mathematics at Manchester Metropolitan University, where he specializes in databases and data science education. As Pathway Lead for the Data Analyst path in the Digital Technology Specialist Degree Apprentice programme, he focuses on developing innovative teaching methodologies and automated assessment tools for SQL and database systems. Developed an automated assessment tool used across multiple university units Research interests span database pedagogy, machine learning, and agricultural technology Active in performance modeling and wireless sensor networks research His publications demonstrate expertise in distributed computing, signal processing, and educational technology. Notable works include: Deep learning performance models for distributed environments (2024) Automated SQL assessment frameworks (2024) UAV-based crop disease detection using hyperspectral imagery (2022) Longitudinal athlete performance analysis (2020-2021)

• Computer Science
• Electrical Engineering
• Artificial Intelligence
• +۶ مورد دیگر

Łukasz Sturgulewski is a researcher affiliated with the Institute of Applied Computer Science at the Lodz University of Technology , under the Faculty of Electrical, Electronic, Computer and Control Engineering. His work spans computer science, electrical engineering, and network security, with a focus on wireless communication systems, medical data platform design, and network traffic analysis. Research Areas: Wireless localization (Bluetooth/Wi-Fi), self-configuring networks, medical data systems, and machine learning for pattern recognition. Publications: Contributions to real-time GPS tracking, ad-hoc network modeling, and network behavior analysis using distance-based decision rules. Software Expertise: Utilized simulation tools like OMNeT++ and GNS3 for network testing and validation.

• Artificial Intelligence (AI)
• Human–Computer Interaction (HCI/HMI)
• Computer Vision
• +۴ مورد دیگر

Prof. Dr. Julius Schöning is a Professor at the Faculty of Engineering and Computer Science at Osnabrück University of Applied Sciences, associated with the Computer Vision Group and the Institute of Cognitive Science. He holds a Master of Science in Intelligent Embedded Microsystems from Albert-Ludwigs-Universität Freiburg and a Bachelor of Engineering in Mechatronics from DHBW Stuttgart. His research focuses on AI-in-the-Loop systems, Human-Computer Interaction (HCI), and Computer Vision applications in agriculture and autonomous systems. Key research areas include AI compliance for agricultural robotics, explainable AI (XAI), and safety protocols for autonomous vehicles. Recent publications address obstacle detection via haptic vests, AI compliance frameworks for farms, and quantum NLP. Current projects include developing compliant AI tools for developers and exploring operational domains for agricultural autonomous systems. Prof. Schöning has held roles as a System Architect at ZF Friedrichshafen AG and Research Assistant at Universität Osnabrück. He advises on AI safety and compliance, and collaborates with industry partners like CLAAS. His work bridges technical innovation with legal and ethical considerations, particularly in automated systems.

• Computational Chemistry
• Medicinal Chemistry
• Computer-Aided Drug Design
• +۴ مورد دیگر

Donald B. Boyd, Ph.D., serves as Research Professor of Chemistry at Indiana University - Purdue University Indianapolis (IUPUI) within the School of Science. His academic journey began in 1982 when he joined as Adjunct Professor while concurrently working as a Senior Research Scientist at Eli Lilly and Company, where he spent 25 years in computer-aided drug design. He was promoted to Research Professor in 1994, establishing himself as a leading figure in computational chemistry with over 100 refereed publications and significant editorial contributions. Dr. Boyd earned his B.S. from The Pennsylvania State University (1963), followed by an A.M. (1965) and Ph.D. (1968) from Harvard University, with NIH Postdoctoral training at Cornell University (1967-68). His research focuses on computational chemistry and medicinal chemistry, particularly the relationship between molecular structure and properties, with applications in pharmaceutical development. He pioneered computer-aided drug design methodologies that address the economic challenges of modern drug discovery, leveraging genomic insights for targeted therapeutic development. His publication record reveals consistent contributions to computational drug design, molecular modeling, and the historical evolution of computational chemistry. Early work centered on molecular simulations of drug-receptor interactions (1990s), evolving toward Alzheimer's disease therapeutics, HIV inhibitors, and pharmaceutical stress testing in recent years. The research demonstrates increasing integration of cheminformatics, machine learning, and industrial applications throughout his career. Spirit of Philanthropy Award from IUPUI (1996) Woodward Lecturer, Pennsylvania State University College of Medicine (2013) Sloan-C Award for Online Education (2012) Stanley C. Israel Regional Award (2011) James Flack Norris Award for Teaching Chemistry (2008) Multiple Prestigious External Award Recognition (PEAR) honors Dr. Boyd has advised numerous graduate students who now hold positions at major pharmaceutical companies and research institutions worldwide. His editorial leadership includes founding the Reviews in Computational Chemistry book series (18 volumes, 1990-2002) and serving as Editor of the Journal of Molecular Graphics and Modelling (1998-2001), where he increased submissions from 5 to 90 annually. He conceived the biennial Gordon Research Conferences on Computational Chemistry (1986-present) and the ACS Symposium on Emerging Technologies in Computational Chemistry. Through his Central Indiana Computational Chemistry Christmas Luncheons and leadership in professional organizations including the American Chemical Society's Division of Computers in Chemistry, Dr. Boyd has fostered collaborative research communities while maintaining active industry consultation roles with pharmaceutical and chemical companies.

Gerd Petterssonمشاهده پروفایل

مدرس

• Education Technology
• Special Needs Education
• Rural Education
• +۳ مورد دیگر

Gerd Pettersson is a Lecturer at the Department of Education, Umeå University, specializing in educational technology and special needs education. Her research focuses on improving educational access and quality in rural settings through innovative approaches to remote teaching and collaborative practices. Pettersson is affiliated with the Umeå Center for Disability Research, contributing to interdisciplinary work on inclusive education systems. Her research explores the intersection of technology, special education, and rural schooling contexts, with emphasis on: Developing effective remote consultation models for special educators Enhancing digital competence among rural teachers Creating flexible educational frameworks for diverse learners Promoting Nordic collaboration in educational research Analysis of Pettersson's recent publications reveals consistent themes in Scandinavian educational innovation, particularly examining how digital tools facilitate special needs support in remote areas. Her work demonstrates evolving methodological approaches from case studies to systematic reviews, maintaining focus on practical applications for rural schools. Pettersson contributes to several research teams investigating educational accessibility. She participates in the Nordic learning network 'Gemensamma Vägar' (Common Paths), focused on practice-based research to address educational disparities in rural communities.

Arif S. Malikمشاهده پروفایل

استاد

• Computational Mechanics
• Uncertainty Analysis
• Reliability-Based Design Optimization
• +۷ مورد دیگر

Dr. Arif S. Malik is a Professor in the Department of Mechanical Engineering at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. His research focuses on computational mechanics, uncertainty analysis, and advanced manufacturing processes including additive manufacturing, laser peening, and metal rolling. He holds a PhD, MS, and BS in Mechanical and Electrical Engineering from Wright State University. His major awards include the NSF CAREER Award (2015) and AFRL Summer Faculty Fellowship (2010-2015). Research interests span reliability-based design optimization, fluid-structure interaction in micro air vehicles, and probabilistic modeling in manufacturing. Recent work emphasizes residual stress analysis in additive manufacturing, hybrid WAAM machining, and thermomechanical modeling in advanced processes. Publications highlight contributions to laser impact welding, cold rolling dynamics, and smart grid optimization. His lab website and Google Scholar profile document over 100 peer-reviewed articles since 2001. Current projects include NSF-funded research on tool-path design optimization for additive and machined parts.