جست‌وجوی استاد و پژوهشگر

Mika Ruokonenمشاهده پروفایل

استاد مدعو

• Artificial Intelligence
• Business Strategy
• Digital Transformation
• +۳ مورد دیگر

Mika Ruokonen serves as an Industry Professor at LUT University's Business School, with a new AI-focused industry professorship commencing in August 2025 on the Lahti campus. His role is funded by the PHP Foundation, Padasjoki Savings Bank Foundation, Lahti Industrial Association Foundation, and City of Lahti with a total of 310,000 euros for a three-year part-time position. As the largest donor, the PHP Foundation contributed 150,000 euros to this initiative. Ruokonen specializes in artificial intelligence research, particularly in business applications, collaborating with Professor Paavo Ritala. His doctoral work was completed at LUT in 2008, and he brings extensive business management experience to his academic role. He has gained recognition as an AI expert in Finnish media and internationally through numerous studies and public statements on AI strategies. His research interests center on practical AI implementation in business contexts, with focus areas including generative AI for strategic advantage, industrial AI capabilities development, AI-first business strategies, and the application of AI in European industries. His work bridges academic research with practical business applications, emphasizing how organizations can leverage AI for competitive advantage and operational transformation. Ruokonen's publication record shows a strong focus on the intersection of AI technologies and business strategy, with recent work examining generative AI, metaverse strategies, conversational AI in knowledge industries, and data-driven competitiveness. His research demonstrates a clear trajectory from foundational digital transformation concepts to cutting-edge AI applications across various business functions. His new role involves speaking at AI-related events in Lahti, with the first engagements planned for late 2025. The position aims to build 'broader shoulders for AI research' that is more extensive, faster, and less dependent on individual researchers. Ruokonen emphasizes that his contribution combines academic expertise with practical business skills and contacts, particularly supporting AI development from a management perspective. He has authored significant reports including 'Applying AI in Key European Industries' for the Finnish Innovation Fund Sitra, where he advocates for European investment in AI infrastructure, expertise, models, and data availability. His recommendations include European single market harmonization, affordable computing resources, multilingual large language models, reliable European data spaces, AI workforce training, and talent retention strategies.

• Sustainability Science
• Socio-ecological Systems
• Ecology
• +۱۱ مورد دیگر

Jussi Eronen is a Professor of Socio-ecological Systems at the University of Helsinki , affiliated with the Faculty of Biological and Environmental Sciences and the Ecosystems and Environment Research Programme . He also serves as Vice-Dean for Societal Interaction and maintains an external affiliation with the BIOS Research Unit . His research focuses on three main areas: (1) long-term biotic interaction changes due to human influence, (2) socio-ecological system analysis in Northern Fennoscandia, and (3) policy path-dependencies affecting sustainability transitions. The Past Present Sustainability Research Unit (PAES) he leads employs transdisciplinary approaches combining natural science perspectives with social science collaborations. Recent work examines reindeer herding futures using wild logic scenarios, policy implementation challenges in forest industries, and cultural transmission patterns through string figure analysis. His publications span journals like Journal of Land Use Science , Anthropocene Review , and Ecological Economics , reflecting his integrative approach to sustainability science. Current projects include EU-funded research on regional sustainability pathways (2023-2025) and Academy of Finland initiatives for university profiling (2025-2030). He maintains active roles in scientific networks like the Scientific Consensus on Maintaining Humanity's Life Support Systems .

Nils Gruschkaمشاهده پروفایل

استاد

• Information Security
• Privacy
• Data Protection
• +۵ مورد دیگر

Nils Gruschka is a Professor at the Department of Informatics , University of Oslo, specializing in Information Security and Privacy . He contributes to the Digital Security (SEC) group and the Partnership for Cybersecurity (P4C). His work bridges technical security implementations with regulatory compliance, particularly under GDPR.

• Numerical Analysis
• Machine Learning
• Computational Mathematics
• +۴ مورد دیگر

Elena Toscano is a researcher in the Department of Mathematics and Computer Science at the University of Palermo. She specializes in numerical analysis, machine learning, and computational mathematics, with a focus on mesh-free methods like Smoothed Particle Hydrodynamics (SPH) and applications to physics, engineering, and interdisciplinary fields. Teaching: Numerical Analysis (Master's in Informatics and Mathematics, 2025/2026) Research Areas: Signal/image processing, SPH consistency restoration, genetic algorithms for tomography, and mathematical-literary collaborations (e.g., Oulipo). Her publications span computational physics, machine learning, and mathematical modeling, emphasizing numerical stability and interdisciplinary innovation.

Vijay Narayananمشاهده پروفایل

استاد

• Power Aware Computing
• Computer Architecture
• Embedded Systems
• +۴ مورد دیگر

Vijay Narayanan is the Robert Noll Chair Professor in Computer Science & Engineering and Electrical Engineering at Pennsylvania State University. He co-directs the Microsystems Design Lab and leads research in embedded visual analytics, self-powered processors, and system design using emerging devices. Education: B.E in Computer Science and Engineering (1993) from University of Madras, India Ph.D. in Computer Science and Engineering (1998) from University of South Florida, USA His research spans Power Aware Computing , Computer Architecture , and Embedded Systems , with emphasis on Visual Cortex on Silicon and Self-Powered Processors . Current work includes Non-Volatile Processors and Design Automation under unreliable power conditions via NSF ERC ASSIST. Recent publications focus on GPU architecture (Tensor Cores, ACE), Memory Consistency Verification (QED), and Neural Radiance Fields (Disorf, Distwar) for robotics and rendering. Key collaborations include Tsinghua University and DARPA/SRC LEAST Center . Scientific Awards: IEEE Fellow ACM Fellow He leads the Architecture, Benchmarking and Circuits Thrust in the DARPA/SRC LEAST Center and contributes to NSF ERC ASSIST for self-powered systems. Grants and projects emphasize cross-layer optimizations and hardware-software co-design.

Ravindra Shindeمشاهده پروفایل

پژوهشگر

• Computational Materials Science
• Quantum Chemistry
• Exascale Scientific Computing
• +۵ مورد دیگر

Ravindra Shinde is a Research Scientist at the University of Twente , Netherlands, affiliated with the Computational Chemical Physics group under the Faculty of Science and Technology . He is also the founder of The Science Dev , a tech and research blog. Education : Ph.D. in Physics (2014) and M.Sc. in Physics (2009) from IIT Bombay, India. His research spans Exascale Scientific Computing , Quantum Chemistry , Time-Dependent DFT , and Topological Materials . He specializes in method development for quantum mechanical simulations and code modernization for high-performance computing . Recent publications focus on Exascale Computing challenges , Quantum Monte Carlo accuracy, and machine learning integration in force field modeling. Notable awards include SERB Postdoctoral Fellowship and multiple Best Presentation Awards . Scientific Awards : Best Poster Award, UC Riverside (2019) Best Presentation Awards, SERB 2018 & IISc 2018 National Postdoctoral Fellowship, India (2016-2018) All India GATE Physics Rank 73 (2009)

Lindsey Kuperمشاهده پروفایل

استادیار

• programming languages
• distributed computing
• concurrency
• +۶ مورد دیگر

Lindsey Kuper is an Assistant Professor in the Computer Science and Engineering Department at the Baskin School of Engineering, University of California, Santa Cruz. She received her Ph.D. from Indiana University in 2015 and leads the CASL (Concurrency and Safety Lab) research group, which is part of the larger Languages, Systems, and Data (LSD) Lab. Her research focuses on programming-language-based approaches to building concurrent and distributed software systems that are elegant, correct, and efficient. Key research areas include: Library-level choreographic programming (in Haskell, Rust, and TypeScript) Dependently-typed diagrams for inductive reasoning about concurrent executions Expressing and verifying causal message delivery with refinement types Lindsey's research has been recognized with an NSF CAREER Award, a Stellar Development Foundation Academic Research Grant, a Google Faculty Research Award, and support from Amazon Web Services. Her work on "HasChor: functional choreographic programming for all" received the ICFP 2023 Distinguished Paper Award. She teaches courses in programming languages and distributed systems at UC Santa Cruz, including Foundations of Programming Languages and graduate/undergraduate Distributed Systems. Her undergraduate distributed systems lectures from 2020-2021 have been viewed over 200,000 times on YouTube. Lindsey co-founded the !!Con and !!Con West conferences of ten-minute talks on the joy, excitement, and surprise of computing, and serves on the board of the Exclamation Foundation. She has chaired numerous workshops and served on program committees for major programming languages conferences including PLDI, POPL, ICFP, and OOPSLA. Her current PhD students include Jonathan Castello, Tim Goodwin, Nathan Liittschwager, Patrick Redmond, Gan Shen, and Yan Tong. Recent graduates include Shun Kashiwa (MS, 2024) and Ali Ali (BS, 2024).

Benjamin C. Pierceمشاهده پروفایل

استاد

• Programming Languages
• Type Systems
• Language-Based Security
• +۵ مورد دیگر

Benjamin C. Pierce serves as the Henry Salvatori Professor of Computer and Information Science in the School of Engineering and Applied Science at the University of Pennsylvania. He is a Fellow of the ACM with extensive editorial experience, having served as co-Editor in Chief of the Journal of Functional Programming and Managing Editor for Logical Methods in Computer Science. His research spans programming languages, type systems, language-based security, formal verification, differential privacy, and synchronization technologies. Pierce is renowned for developing foundational frameworks in bidirectional transformations (lenses), property-based testing, and differential privacy verification. His work bridges theoretical computer science with practical implementation, particularly evident in his development of the Unison file synchronizer and the Clowdr virtual conference platform. The trends in his recent publications reveal a sustained focus on verification techniques for privacy-preserving systems, particularly differential privacy, alongside continued innovation in bidirectional data transformations and property-based testing methodologies. His work increasingly integrates formal verification with practical implementation concerns. Fellow of the ACM Pierce has mentored numerous researchers through PLMW (Programming Languages Mentoring Workshop) events and has served on numerous program committees for major conferences including POPL, PLDI, and ICFP. His editorial work has significantly shaped the programming languages research community through his leadership roles in key journals. He leads development of the Unison file synchronizer, a cross-platform tool used worldwide, and co-developed the Clowdr virtual conference platform that gained prominence during the pandemic. His work demonstrates a consistent pattern of creating practical tools grounded in deep theoretical foundations.

• Machine Learning
• Deep Learning
• Software Engineering
• +۷ مورد دیگر

Sebastian Hönel is a postdoctoral researcher at Linnaeus University, affiliated with the Faculty of Technology and the Department of Computer Science and Media Technology. He is an active member of the Data Intensive Software Technologies and Applications (DISTA) research group and currently serves as a co-Principal Investigator in the project "In-line visual inspection using unsupervised learning" focused on manufacturing defect detection using machine learning techniques. Hönel completed his Doctoral Thesis in 2023 titled "Quantifying Process Quality: The Role of Effective Organizational Learning in Software Evolution" and earned his Licentiate Thesis in 2020 on "Efficient Automatic Change Detection in Software Maintenance and Evolutionary Processes," both from Linnaeus University. His educational background demonstrates a strong foundation in software engineering and data analysis. Hönel's research spans software engineering, machine learning, and data science. Initially focusing on applying Machine Learning and Deep Learning to software evolutionary processes and organizational learning, his current work emphasizes unsupervised and zero/few-shot learning techniques for industrial anomaly detection. He has particular expertise in Deep Density Estimation (especially Normalizing Flows) and Representation Learning, with applications in manufacturing quality assessment and software maintenance. His research interests include anomaly detection methodologies, architectural innovations in autoencoders, and methodological considerations for evaluation metrics in machine learning applications. An analysis of his publication record reveals a consistent focus on bridging software engineering with advanced machine learning techniques. His most recent work shows a strategic shift toward industrial applications of unsupervised learning, particularly in manufacturing defect detection, while maintaining his foundational work in software metrics and quality assessment. The publications demonstrate progression from theoretical software metrics to practical applications of deep learning in quality inspection systems. Hönel actively contributes to academic education by teaching (Deep) Machine Learning courses (4DV652, 4DV660, 4DV661) and previously served as a teaching assistant for agile product development courses (1DV508, 4DV611). His role as co-PI on the visual inspection project indicates successful research funding and leadership capabilities. While specific grant details aren't provided in the available information, his position suggests ongoing research support. As part of the DISTA research group, Hönel collaborates extensively with colleagues including Ericsson, Löwe, and Wingkvist on projects that combine software engineering with advanced data analysis techniques. His work environment supports interdisciplinary research at the intersection of computer science, software engineering, and machine learning applications, with particular emphasis on practical implementations in both software development contexts and manufacturing quality control systems.

William C. Garrison IIIمشاهده پروفایل

مدرس

• Computer Science
• Access Control Systems
• Web Privacy
• +۴ مورد دیگر

William C. Garrison III serves as a Lecturer in the Department of Computer Science at the University of Pittsburgh's School of Computing and Information. Holding a PhD in Computer Science from the University of Pittsburgh (2015), his work has been recognized with a runner-up distinction for the ACM SIGSAC Doctoral Dissertation Award. His research focuses on application-aware access control evaluation, web privacy, and technology-induced distracted driving, with a particular emphasis on cybersecurity education for undergraduates. Research Interests: Access control evaluation frameworks Usability in security systems Web privacy mechanisms Cybersecurity education Human-computer interaction in security Distracted driving technology Scientific Awards: ACM SIGSAC Doctoral Dissertation Award Runner-up Mentor-Mentee Evidence-Based Teaching Award (with Adam J. Lee) Innovation in Education Award (with Nicholas L. Farnan) Academic Contributions: Summer Undergraduate Research Awards mentoring Curiosity Grant projects supervision Journal reviewing for IEEE Transactions on Dependable and Secure Computing and ACM Transactions on Privacy and Security Conference reviewing for Privacy Enhancing Technologies Symposium

• Laser Technologies
• Optoelectronics
• Electrical Engineering
• +۴ مورد دیگر

Christina Ivanova Deneva is a lecturer at the Technical University - Gabrovo, specializing in laser technologies and electrical engineering. Her work focuses on laser processing applications for electrical steel used in stator and rotor packages for electric motors, with significant contributions to laser cutting, marking, and welding technologies. Her research interests span Laser Technologies , Optoelectronics , and Materials Processing , with particular emphasis on process optimization for industrial laser applications. She has developed specialized training modules for the Master's Curriculum "Optoelectronics and Laser Technology" and has conducted extensive research on temperature field analysis during laser processing using software tools like Temperaturfeld3D and Mathcad. Analysis of her publication record shows a consistent focus on laser-material interactions, particularly with electrical steel. Her work demonstrates expertise in both theoretical modeling (finite element method) and experimental validation of laser processing parameters. She has also contributed to educational technology through research on interactive teaching methods using interactive boards. Dr. Deneva has participated in multiple research projects including the 2011 "PROCESS OPTIMIZATION LASER MARKING OF STATOR PACKAGES FOR ELECTRIC MOTORS" and two international ERASMUS Summer Schools on "INNOVATIVE LASERTECHNOLOGIES" in 2011 and 2012. Her collaborative work with colleagues like L. Lazov and N. Angelov has resulted in numerous publications in both international conferences and journals. Her teaching activities include developing physics laboratory materials and implementing modern teaching methods with interactive technology. She maintains an active research profile with publications spanning from 2011 to 2013, showing continued engagement in both technical research and educational innovation.

Myra B. Cohenمشاهده پروفایل

استاد

• Software Testing
• Search-Based Software Engineering
• Combinatorial Designs
• +۴ مورد دیگر

Myra B. Cohen is a Professor and the Lanh and Oanh Nguyen Chair in Software Engineering within the Department of Computer Science at Iowa State University's College of Engineering. She previously served as a Susan J. Rosowski Professor at the University of Nebraska-Lincoln and leads the LaVA-OPs Laboratory for Variability-Aware Assurance and Testing of Organic Programs. Her research spans software testing of highly-configurable systems, search-based software engineering, combinatorial design applications, and synergies between software engineering and synthetic biology. She investigates assurance techniques for self-adaptive systems through bio-inspired algorithms and examines software testing representations of natural processes like chemical reaction networks. Her 15 most recent publications demonstrate strong focus on cyber-physical systems (particularly drone safety), biological computing, and configuration-aware testing. These works reveal interdisciplinary trends combining software engineering with synthetic biology, emphasizing real-world applications in autonomous systems and computational biology. NSF CAREER Award AFOSR Young Investigator Award ACM Distinguished Scientist Best Student Paper Award at SPLC 2019 ACM Distinguished Paper Award at ASE 2020 Best Paper Award at GI@ICSE 2021 Professor Cohen advises PhD students Salil Purandare, Md Obaidul Kabir, and Michael Gerten, with research focusing on cyber-physical systems and biological software applications. She leads multiple significant projects including the DOE-funded Dependable, Explainable, Reusable, AI-Driven Computational Biology initiative and blockchain fault tolerance research. Her LaVA-OPs laboratory develops assurance techniques for highly-configurable and self-adaptive programs through bio-inspired algorithms.

Mahmoud Alfadelمشاهده پروفایل

استادیار

• Software Engineering
• Mining Software Repositories
• Empirical Software Engineering
• +۳ مورد دیگر

Mahmoud Alfadel is an Assistant Professor at the University of Calgary, Canada, actively contributing to software engineering research through program committee roles at ASE, ICSE, and ESEC/FSE conferences from 2021-2025. His research centers on Software Ecosystems, Release Engineering, and Empirical Software Engineering, with specific focus on build systems, continuous integration pipelines, dependency management, and software quality metrics in open-source environments. Methodologically, he employs large-scale empirical studies of real-world development practices. Analysis of his 2021-2025 publications reveals consistent investigation into build technology evolution (particularly Bazel), dependency-induced waste in NPM, and testing practices like fuzzing adoption. His work bridges theoretical software engineering concepts with practical industry challenges, often through case studies of major open-source projects like Kubernetes.

Nour Aliمشاهده پروفایل

استاد

• Software Engineering
• Software Architecture
• Adaptive Systems
• +۳ مورد دیگر

Dr. Nour Ali serves as a Professor and Vice-Dean of Education in the College of Engineering, Design and Physical Sciences at Brunel University London, where she co-heads the Brunel Software Engineering Lab. With a PhD in Software Engineering from Universidad Politecnica de Valencia and a Computer Science degree from Bir-Zeit University, she brings extensive international experience from previous positions at University of Brighton, Lero (Irish Software Engineering Research Centre), and Politecnico di Milano. PhD in Software Engineering, Universidad Politecnica de Valencia, Spain Major in Computer Science, Bir-Zeit University, Palestine PG Certificate in Teaching and Learning in Higher Education, University of Brighton Fellow of the Higher Education Academy (HEA) Her research focuses on developing software architecture techniques for distributed, mobile, and adaptive systems, with particular expertise in microservice architecture recovery and visualization. With over 70 publications spanning two decades, her work bridges theoretical architecture principles with practical implementation challenges. Recent research demonstrates a strong focus on microservice architecture recovery tools like MiSAR and analysis of service granularity adaptation. Dr. Ali has made significant contributions to the software engineering community through editorial roles including Deputy Editor in Chief of IET Software, committee memberships for major conferences like ICSE and ASE, and reviewer positions for EPSRC and other funding bodies. Her publications reveal consistent contributions across architecture consistency, microservice systems, and adaptive requirements engineering, with recent work increasingly focusing on practical tool development for architecture recovery. External Examiner, York St John University (2021-2025) Deputy Editor in Chief, IET Software Committee member for ICSE, ASE, EASE, ICSA, MOBILESoft conferences EPSRC Full College Member (2018-present) Reviewer for Dutch Research Council (NWO), UK UNESCO Newton Prize As an educator, Dr. Ali leads CS3100 Software Project Management and contributes to multiple undergraduate and postgraduate courses. Her teaching philosophy integrates research insights with practical software engineering skills, supported by her PG Certificate in Teaching and Learning and HEA Fellowship. She actively supervises PhD students and contributes to curriculum development as Vice-Dean of Education for her college.

Hai Dongمشاهده پروفایل

مدرس ارشد

• Service-Oriented Computing
• Edge Intelligence
• Blockchain
• +۴ مورد دیگر

Dr. Hai Dong is a Senior Lecturer at the School of Computing Technologies, RMIT University in Melbourne, Australia, with promotion to Associate Professor scheduled for 2026. He serves as the Founding Director of the CloudTech-RMIT Green Cryptocurrency Joint Research Laboratory (GreenCryptoLab) and Leader of the Smart Sensing and Services Research Area. Previously, he held research fellow positions at both RMIT University and Curtin University. Dr. Dong is a Senior Member of IEEE and chairs the IEEE Computational Intelligence Society Task Force on Deep Edge Intelligence. Dr. Dong's research spans several cutting-edge domains including Service-Oriented Computing, Edge Intelligence, Blockchain, AI Security, Cyber Security, and Machine Learning. His work bridges theoretical foundations with practical applications, particularly in secure and efficient computing systems. He has developed innovative approaches for smart contract security, edge computing optimization, federated learning, and blockchain applications with a strong focus on sustainability and real-world impact. His publication record demonstrates consistent high-impact contributions across top venues including AAAI, ASE, ICML, TSE, and TSC. Dr. Dong's research shows a clear trajectory toward increasingly sophisticated integration of AI with edge computing and blockchain systems, with growing emphasis on security, privacy, and resource efficiency. Recent work highlights his leadership in addressing emerging challenges in LLM-generated smart contracts and secure federated learning systems. Best Research Paper Award at ICSOC 2016 Best Paper Award at IEEE ICBC 2025 2023 RMIT Award for Research Engagement and Impact - Industry Engagement in Graduate Research Dr. Dong has successfully supervised numerous PhD and Master's students to completion, with many going on to prestigious positions. He has secured over $5 million in research funding as Chief Investigator from sources including ARC, CRC, QNRF, and industry partners like ANZ, CloudTech, and Telstra. His GreenCryptoLab research facility represents a significant industry-academic partnership focused on sustainable blockchain technologies. Dr. Dong maintains active collaborations with researchers worldwide and serves on committees for over 100 international conferences.