جست‌وجوی استاد و پژوهشگر

Alessandro Fogliمشاهده پروفایل

پژوهشگر

• Distributed Systems
• Data Analytics
• Cluster Resource Management
• +۴ مورد دیگر

Alessandro Fogli is a PhD Student at Imperial College London in the Department of Computing, affiliated with the Large-Scale Data & Systems (LSDS) Group . His research focuses on systems support for data analytics in cloud environments, including distributed systems, resource management, and query processing. Education PhD in Computer Science, 2019–Present, Imperial College London MSc in Computer Science, 2015–2017, Roma Tre University BSc in Computer Science, 2012–2015, Roma Tre University His research spans Distributed Systems , Databases , Data Analytics , and Modern Hardware . Recent work examines chiplet-based processor architectures and runtime mapping systems, with applications in performance optimization and hardware-aware query execution. Scientific Contributions Co-developed CHARM (2025), a runtime mapping system for chiplet heterogeneity Published in VLDB (2024) on OLAP processing for chiplet-based CPUs Contributed to HeatWave at Oracle Labs, improving query offloading to in-memory accelerators

Shaked Flurمشاهده پروفایل

پژوهشگر

• Formal Methods
• Computer Architecture
• Programming Languages
• +۳ مورد دیگر

Shaked Flur is a Researcher at the Department of Computer Science and Technology, University of Cambridge. His work focuses on formal methods, instruction-set semantics, and concurrency models in computer architectures. He contributes to the development of formal verification tools and specifications for ISA standards like ARMv8-A, RISC-V, and CHERI-MIPS. His research bridges academic formal models with practical software and hardware design, emphasizing the adoption of rigorous methods in real-world systems. Flur collaborates on projects such as the Sail specification language, enhancing clarity and precision in ISA documentation. His publications address challenges in memory models, concurrency semantics, and automated verification techniques.

• Machine Learning
• Information Retrieval
• Medical Data Analysis
• +۳ مورد دیگر

Ingemar Johansson Cox serves as a Professor within the Machine Learning section at the Department of Computer Science, University of Copenhagen. His research bridges theoretical machine learning foundations with practical applications across medical data analysis, information retrieval, remote sensing, and sustainability initiatives. His research portfolio emphasizes machine learning applications in high-impact domains, particularly medical data analysis (e.g., early detection of gynecological malignancy using online search activity) and sustainability (e.g., reducing AI's carbon footprint). The Machine Learning section actively contributes to the university's SCIENCE AI Centre, focusing on both algorithmic innovation and real-world problem-solving in biological modeling and environmental monitoring. Recent publication trends reveal expanding work in quantum computing applications for biomolecular modeling, sustainable AI frameworks, and cross-cultural NLP systems. His 2024-2025 output demonstrates strong interdisciplinary collaboration, especially in medical informatics and climate-related AI research. Professor Cox operates within the Department of Computer Science's robust research ecosystem, which includes dedicated compute clusters and specialized initiatives like TreeSense for global tree resource monitoring through remote sensing and deep learning. The department's infrastructure supports large-scale machine learning projects requiring significant computational resources.

• Computer Architecture
• Parallel Processing
• FPGA Design
• +۳ مورد دیگر

Frank Hannig is a Professor at the University of Erlangen-Nuremberg, Germany, specializing in computer architecture and high-performance computing. His research focuses on FPGA acceleration, hardware-software co-design, neural network optimization, and embedded systems. He has collaborated extensively with co-authors such as Jürgen Teich and Oliver Reiche, producing over 200 publications since 2001. His work emphasizes domain-specific languages (DSLs) for image processing (e.g., Hipacc) and compiler optimizations for FPGAs. Key contributions include techniques for quantized neural networks on microcontrollers, CGRA toolchain evaluation, and efficient mapping of CNNs onto processor arrays. Hannig also explores energy-efficient architectures and reconfigurable computing for emerging applications like edge AI and automotive systems. Publications span conferences like ASAP, FPL, and ARC, reflecting his interdisciplinary approach to bridging algorithm design and hardware implementation. His research often addresses practical challenges in deploying machine learning models on resource-constrained devices while maintaining performance and energy efficiency.

• Cybersecurity
• Cryptography
• Information Security
• +۷ مورد دیگر

Dr. Viktor Melnyk serves as an Assistant Professor in the Department of Applied Computer Science at the Institute of Mathematics, Informatics and Landscape Architecture within the Faculty of Natural Sciences and Technology at John Paul II Catholic University of Lublin. His academic activities span teaching, research, and extensive student supervision across multiple years. His research interests focus on cybersecurity, cryptography, and FPGA-based systems, with particular expertise in wireless network security (especially IEEE 802.15.4), hardware acceleration, and machine learning applications in electronic design. His work bridges theoretical computer science with practical security implementations, evident in his numerous publications and student thesis topics. Analysis of Dr. Melnyk's recent publications reveals a consistent focus on hardware security implementations, particularly for low-rate wireless networks and reconfigurable computing systems. His research trajectory shows increasing integration of machine learning techniques with traditional security protocols, reflecting broader trends in the field. The publications demonstrate both theoretical depth and practical implementation focus, with many papers addressing specific hardware implementations. Dr. Melnyk has served as an Independent External Expert for evaluating grant proposals in the European COST Open Call competition, indicating professional recognition of his expertise. His contributions to the academic community extend to reviewing numerous scientific articles across various domains including biomedical data processing, cyber-physical systems, and cloud computing. His academic advising is exceptionally active, with documentation of supervising over 100 diploma theses from 2015 through 2025 across both Bachelor's and Master's levels. The thesis topics consistently align with his research interests, covering cybersecurity, cryptography, network security, and hardware implementations. He teaches courses including 'Operating Systems,' 'Network Data Protection Technologies,' and 'Multimedia Systems,' with teaching materials adapted for remote delivery during the pandemic period.

• Verification of Secure Systems
• Software Security
• Web Security
• +۵ مورد دیگر

Pedro Adão is an Assistant Professor at the Department of Computer Science and Engineering (DEI) of the Instituto Superior Técnico (IST) , University of Lisbon . He is affiliated with the SQIG - Security and Quantum Information Group at the Institute of Telecommunications , formerly part of CLC - Logic and Computation Centre . His work bridges formal methods and computational cryptography , focusing on security protocols , software security , and quantum information security . PhD in Mathematics (2006, IST) with thesis "Formal Methods for the Analysis of Security Protocols" Graduated in Applied Mathematics and Computation (2002, IST) with thesis "Electronic Money" His research interests include verification of secure systems, composition of secure systems, mathematical foundations of cryptography, and physical/day-life security. His publications span topics like firewall configuration tools , smart contract verification , quantitative protocol analysis , and computationally sound symbolic cryptography . He has collaborated with institutions such as the University of Pennsylvania, Microsoft Research Cambridge, and INRIA-Microsoft Research Paris. Key teaching contributions include courses in Introduction to Algorithms and Data Structures , Computational Models in Security , and Software Security . He is a member of the SQIG research group and has organized the SQIG Information Security Seminar . Past teaching roles include lecturing at the Catholic University of Portugal and the Air Force Academy.

• Software Engineering
• Model-Driven Engineering
• Digital Twins
• +۳ مورد دیگر

Antoine Beugnard is a Professor in the Computer Science Department at IMT Atlantique. He received his PhD in Computer Science from the University of Rennes 1 (1993) and accreditation to supervise research in 2005. His career spans academia and industry, including roles at ENST-Bretagne, Telecom Bretagne (now IMT Atlantique), and Michael Jackson France. Education: PhD in Computer Science (University of Rennes 1, 1993), Accreditation to Supervise Research (2005) Affiliation: IMT Atlantique, Lab-STICC (UMR 6285), P4S team Beugnard's research focuses on software modeling, particularly digital twins, model federation (via Openflexo/FML), and late-binding semantics in heterogeneous object-oriented languages. He explores interoperability challenges in multi-language systems and advocates for unified semantics to improve component compatibility. Key trends in his publications include model-driven engineering, digital twin architectures, and formal modeling notations. His work bridges theoretical foundations with industrial applications, notably in telecom systems for Orange and multi-level modeling frameworks. Advising and grants highlight his mentorship of 10+ PhD candidates and leadership in projects like Openflexo. He actively contributes to academic discussions on modeling methodologies and software development processes.

Ben Jannمشاهده پروفایل

استاد

• Statistical Methods
• Data Visualization
• Social Inequality
• +۲ مورد دیگر

Ben Jann is a Professor and current Department Head at the University of Bern in the Department of Social Sciences . His methodological expertise spans statistical software development, decomposition analysis, and data visualization. Role: Department Head Institution: University of Bern Department: Department of Social Sciences Research Interests : Jann specializes in creating Stata modules for advanced statistical analysis, including geospatial mapping (geoplot), robust regression (robreg10), and inequality decomposition (oaxaca-blinder methods). His substantive work examines social inequality through economic and sociological lenses, analyzing how living costs and taxation systems impact income distribution in Switzerland. He also investigates educational transitions and gender disparities in STEM occupational choices through longitudinal studies like TREE2. Recent Publications Trends : Jann’s 15 most recent articles (2025-2023) demonstrate his focus on statistical software development for social science applications. Key contributions include methods for marginal odds ratios (2023), two-level model variance decomposition (2025), and list experiment analysis (2025). His empirical work connects statistical methodology to pressing social issues like gender wage gaps (2021) and teacher content knowledge in developing countries (2021).

• Parallel Computing
• Quantum Computing
• Self-Adjusting Computation
• +۴ مورد دیگر

Umut A. Acar is a Professor at the Computer Science Department , Carnegie Mellon University , and an Amazon Scholar. His research focuses on bridging formal methods with systems , algorithms , and AI , aiming to integrate safety and performance in parallel computing. His research spans multiple domains: Quantum Computing : Developing optimization techniques for quantum circuits (e.g., Quartz , Atlas ). Self-Adjusting Computation : Advancing dynamic algorithms and incremental programming frameworks (e.g., Diderot , MPL ). Concurrency & Parallelism : Designing efficient scheduling mechanisms and disentanglement strategies. Recent publications highlight his work on parallel functional programming , quantum simulation , and cache coherence optimization . Notable awards include Best Paper (QCE 2025) , Distinguished Paper (POPL 2024) , and the Intel Award (2022) . He advises PhD students like Pengyu Liu and Mingkuan Xu , and has mentored alumni now at institutions such as NYU , Google , and Inria . His lab collaborates on projects like Diderot (AI/ML) and MPL (parallelism management).

Shafaeat Hossainمشاهده پروفایل

استاد

• Machine Learning
• User Authentication in Smart Devices
• Behavioral Biometrics
• +۱ مورد دیگر

Shafaeat Hossain is a Professor in the Department of Computer Science at Southern Connecticut State University (SCSU) . He holds a Ph.D. in Computational Analysis and Modeling from Louisiana Tech University (2014) and advanced degrees from the University of Dhaka. His research focuses on machine learning , user authentication in smart devices , behavioral biometrics , and multi-biometric verification . B.S. in Computer Science and Engineering, University of Dhaka (2006) M.S. in Computer Science, Louisiana Tech University (2012) Ph.D. in Computational Analysis and Modeling, Louisiana Tech University (2014) His work bridges machine learning with security applications , particularly in touchscreen gesture analysis , continuous authentication , and behavioral biometrics for smartphones. He explores multi-biometric fusion strategies to enhance security and user convenience, while also investigating game theory in social networks and NLP for deep authorship attribution . Recent publications highlight advances in capacitive swipe authentication , zoom gesture analysis , and Wi-Fi indoor positioning . Collaborative studies address sleep apnea diagnosis and smartwatch dynamics in verification systems. SCSU Faculty Scholar Award (2023) SCSU Mid-Level Faculty Research Fellowship (2019) Senior Member, IEEE He has secured grants totaling over $25,000 from SCSU, CSU-AAUP, and UConn for projects on child safety in digital authentication and multi-biometric security enhancement . His scholarship spans IEEE Access , Computers & Security , and top-tier conferences like IEEE IJCNN and SMARTCOMP .

• World Literature
• Comparative Literature
• Ancient Greek and Roman Literature
• +۳ مورد دیگر

Alexander Beecroft is the Jessie Chapman Alcorn Memorial Professor of Foreign Languages at the University of South Carolina, affiliated with the College of Arts and Sciences and the Department of Languages, Literatures and Cultures. His academic career spans roles including Secretary-Treasurer of the American Comparative Literature Association (2011–2019) and Director of the Program in Comparative Literature (2010–2016). Education: Ph.D. in Comparative Literature, Harvard University (2003) B.A. (Honours) in Classics, University of Alberta, Canada (1995) Research Interests: Beecroft specializes in cross-cultural literary studies, focusing on ancient Greek and Roman literature, pre-Tang Chinese literature, and world literature. His work interrogates global literary systems, comparative methodologies, and the intersection of oral traditions with textual canons. Key themes include the role of premodern texts in world literature, the ecology of literary systems, and the dynamics of authorship across cultures. Awards and Honors: Charles A. Ryskamp Research Fellowship (ACLS, 2011–12) Morse Junior Faculty Fellowship (Yale University, 2006–07) University of South Carolina Educational Foundation Research Prize (2015) Teaching and Leadership: Beecroft teaches courses on classical mythology, literary theory, and world literature. He has organized international conferences and panels, including keynotes on global literary history and comparative studies. His administrative roles include committee leadership on research grants and academic policy at the university level. Publications: Beecroft’s monographs include *An Ecology of World Literature* (2015) and *Authorship and Cultural Identity in Early Greece and China* (2010). He contributes to journals such as *Orbis Litterarum*, *Comparative Literature Studies*, and *Journal of World Literature*, with a focus on cross-cultural comparisons and global literary frameworks.

• Advertising
• Marketing
• Consumer Behavior
• +۳ مورد دیگر

Kazue Shimamura is a Professor at Waseda University's Faculty of Commerce, School of Commerce, where she has served since 1993 after joining as Assistant Professor. Holding a Master of Commerce from Waseda University, she has established herself as a leading scholar in advertising research with international recognition through awards and cross-cultural studies. Her academic journey includes: Master of Commerce, Waseda University Graduate School of Commerce (1979-1988) Bachelor of Commerce, Waseda University School of Commerce (1974-1978) Professor Shimamura's research centers on advertising theory, consumer behavior, and branding with distinctive focus on comparative Japan-US studies. Her work examines advertising education systems, experience value in consumer psychology, and regulatory frameworks, revealing critical insights into how cultural contexts shape advertising practices and educational approaches. She pioneered investigations into brand-consumer relationships in automotive sectors and digital media evolution. Analysis of her publication trajectory shows consistent emphasis on advertising education challenges and cross-cultural comparisons, with growing attention to digital transformation and experience-based consumer models since the early 2000s. Her research bridges academic theory and industry practice through extensive collaboration with advertising associations. Her distinguished contributions have earned top industry honors including: Shirakawa Shinobu Award (Tokyo Advertising Association, 2025) Japan Advertising Award Yoshida Award (All Japan Advertising Federation, 2022) Kobayashi Tazaburo Award (Nikkan Kogyo Shimbun, 2015) Japan Association of Advertising Studies Award (2001 and 1998) As principal investigator for the 2016-2019 project on English-language instructional materials development, she advanced international education methodologies. Her University of Texas collaboration (2001-2002) established foundational frameworks for cross-national advertising effectiveness measurement. While specific advisees aren't documented, her graduate-level Advertising Theory courses indicate ongoing mentorship in the Graduate School of Commerce. She maintains active research engagement through Waseda's Research Institute of Business Administration (Concurrent Researcher since 2019) and Global Education Center, driving initiatives in international advertising curriculum development and faculty exchange programs.

Zhi Jinمشاهده پروفایل

استاد

• Requirements Engineering
• Self-Adaptive Systems
• Learning from Source Code
• +۵ مورد دیگر

Zhi Jin is a Professor in the Department of Computer Science and Technology at Peking University, where he has been employed since 2009. Previously, he served as a professor at the Academy of Mathematics and System Sciences, Chinese Academy of Sciences from 1994-2009. He received his BS from Zhejiang University in 1984 and MS/PhD from National University of Defense Technology in 1984 and 1992 respectively. He progressed from assistant professor (1992) to associate professor (1995) to full professor (2001). His research focuses on knowledge engineering and software engineering, with special interests in knowledge graphs, self-adaptive systems, and deep learning applications. Current research directions include Self-Adaptive Software in Human-Cyber-Physical Systems, Crowd-based Requirements Engineering, and Learning from both Natural Language and Programming Language. His work bridges theoretical knowledge engineering with practical software development challenges. His recent publications demonstrate a strong trend toward applying large language models and AI techniques to traditional software engineering problems, particularly in requirements engineering, code generation, and vulnerability detection. The articles span multiple high-impact venues including ASE, ICSE, and RE, with significant focus on aerospace applications and multi-agent collaboration approaches. Scientific honors include: Winner of National Science Fund for Distinguished Young Scholars (2006) Project 973 project lead scientist (2014) Member of Discipline Appraisal Group of the Academic Degree Commission (2015) Multiple ACM Distinguished Paper Awards He serves in numerous editorial roles including Associate Editor for IEEE Transactions on Software Engineering (2018-present) and IEEE Transactions on Reliability (2019-present). He is also an Editorial Board Member for Empirical Software Engineering and Requirements Engineering Journal, and holds leadership positions in the China Computer Federation. His extensive conference service includes PC membership for ICSE, FSE, RE, and other major software engineering venues.

• Edge Computing
• Cloud Computing
• Artificial Intelligence
• +۷ مورد دیگر

Hadi Tabatabaee is an Assistant Professor at the School of Computer Science, University College Dublin (UCD), leading the Sustainable Orchestration in Computing Continuum (SOC² Lab). His research focuses on sustainable orchestration of services across edge-cloud environments, emphasizing energy efficiency, carbon-aware systems, and AI-driven applications like large language models (LLMs). Key roles include Associate Editor for IEEE Access and Management Committee member of COST Action CA22151 (CYPHER). He holds a PhD in Computer Engineering from the University of Isfahan and has held academic positions at Maynooth University, Shahid Beheshti University, and Trinity College Dublin's CONNECT research program. Education: PhD (Computer Engineering, University of Isfahan), MSc (Computer Engineering), with a research visit at TU Delft (2010-2011). Certifications include Epigeum's Research Leadership and Research Integrity courses. Languages: Persian (fluent), Azerbaijani (spoken). Research Interests: Edge-cloud continuum, dynamic service placement, distributed AI workloads, LLM optimization, and sustainable resource management. Recent work includes zero-trust vehicular networks, parallel algorithms for recommender systems, and geospatial event processing. Awards: None explicitly listed, though his contributions include over 20 journal articles in IEEE/Elsevier/Springer venues. Professional Activities: IEEE Senior Member, TPC member for IEEE conferences, and reviewer for multiple journals. Teaching: Coordinates/teaches Cloud Computing, Computer Networks, and Principles of Computer Organization at UCD.

• Biomass Gasification
• Computational Fluid Dynamics
• Combustion Engineering
• +۵ مورد دیگر

Tian Li is an Adjunct Associate Professor at the Department of Energy and Process Engineering, Faculty of Engineering, Norwegian University of Science and Technology (NTNU). Based at the Varmeteknisk building on the Gløshaugen campus, Dr. Li is affiliated with the ComKin Group and has been actively involved in numerous research projects focused on biomass conversion and combustion technologies since 2011. Dr. Li's research primarily focuses on: Biomass gasification and combustion technologies Computational Fluid Dynamics (CFD) modeling of energy conversion processes Multiphase flow and reaction kinetics in thermochemical processes Turbulence modeling in combustion systems Development of simulation tools for bioenergy applications Over the past decade, Dr. Li has led or contributed to multiple significant research projects funded by the Norwegian Research Council and industrial partners, including BioCarbUp, GASPRO, GrateCFD, GAFT, BioCarb+, CenBio, and GasBio. These projects have focused on optimizing biomass conversion processes for sustainable energy production. Dr. Li's publication record shows consistent contributions to high-impact journals in the energy and combustion fields, with a strong emphasis on computational modeling approaches. The research demonstrates expertise in developing and validating models for biomass conversion processes, with applications ranging from industrial-scale biomass furnaces to fundamental particle-level phenomena. Dr. Li has developed significant expertise in various computational tools and programming languages: Software: OpenFOAM, ANSYS Fluent, ANSYS ICEM CFD, Star-CD, MFiX, CHEMKIN, LOGEsoft, LabVIEW Programming: C/C++, Python, Fortran, Matlab Through participation in major research centers like CenBio (Bioenergy Innovation Centre), Dr. Li has contributed to advancing Norway's bioenergy research capabilities and fostering collaboration between academia and industry in the sustainable energy sector.