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Alfredo PerezView profile

Associate Professor

• Computer Science
• Artificial Intelligence
• Cybersecurity
• +4 more

Alfredo Perez, Ph.D., is an Associate Professor and Graduate Program Chair for MS CS Education in the College of Information Science & Technology at the University of Nebraska at Omaha. He holds a doctorate and M.Sc. in Computer Science from the University of South Florida (2011, 2009) and a B.Sc. in Systems Engineering from Universidad del Norte, Barranquilla (2006). Education: Ph.D., Computer Science & Engineering, University of South Florida (2011) M.Sc., Computer Science & Engineering, University of South Florida (2009) B.Sc., Systems Engineering, Universidad del Norte, Barranquilla (2006) Dr. Perez's research focuses on privacy, mobile/ubiquitous computing, and computer science education. His recent work explores blockchain security, IoT privacy frameworks, and machine learning for malware detection. He also investigates formal modeling techniques for secure systems and wearables' facial privacy solutions. His publications reveal trends in privacy-preserving IoT architectures , blockchain applications , machine learning security , and formal verification methods . Research spans from technical implementations to societal impacts of privacy technologies. Scientific Recognition: IEEE Senior Member Member, U.S. National Academy of Inventors Dr. Perez has served on technical committees for journals/conferences like Elsevier Computer Communications and reviewed grants for the National Science Foundation. His teaching expertise covers computer programming, machine learning, and CS teacher education.

• 6G Communications
• Software Defined Networking
• Machine Learning
• +5 more

Matthew Robinson is a Research Fellow at the University of Hertfordshire within the Department of Engineering and Technology, School of Physics, Engineering & Computer Science. His work focuses on next-generation communication systems and security applications, primarily through European and commercially funded projects including those with the European Space Agency (ESA), Horizon 2020, and industry partners like Global Invacom and Meazon. Education: MEng in Digital Communications and Electronics, University of Hertfordshire (2010-2014) Research Interests: Robinson specializes in 6G communications infrastructure with emphases on Software Defined Networking (SDN) , Machine Learning for sensor systems, Software Defined Radio (SDR) , and Satellite Communication for video broadcasting. His fingerprint analysis reveals strong activity in Connected Vehicles (80%), Software Defined Networking (80%), Machine Learning (50%), and Heterogeneous Transport Networks (40%). Projects demonstrate practical applications in energy disaggregation, vehicle sensor reliability, and secure smart metering. Research Trends: Recent publications (2021-2025) show a strategic pivot from video broadcasting systems toward cybersecurity applications for connected infrastructure. His work increasingly integrates unsupervised machine learning with hardware-software co-design, particularly for real-time threat detection in smart grids and autonomous vehicles, while maintaining satellite communication expertise. Awards: GB Patent GB2612705A: "Improvements to video data distribution networks" Projects & Grants: Robinson has contributed to four major initiatives: (1) SAT>IP WiFi Live Mobile TV (ESA-funded, with BBC R&D/Global Invacom), (2) EDIoT (H2020-funded, with Meazon), (3) AutoTrust (ESA-funded, with RL Automotive/Surrey), and (4) CPU/GPU Satellite Modem (ESA-funded). These projects secured substantial European funding and yielded patents, conference papers, and deployable systems for video broadcasting, energy monitoring, and vehicle sensor networks. Laboratory Affiliation: Works within the Networks and Security Research Centre, leveraging facilities for Software Defined Radio experimentation, satellite communication testing, and machine learning validation for IoT systems.

Michael E. CotterellView profile

Senior Lecturer

• Computer Science Education
• Active Learning
• Big Data Analytics
• +3 more

Michael E. Cotterell is a Senior Lecturer of Computer Science and Undergraduate Coordinator at the University of Georgia's School of Computing. He holds a B.S. (2011) and Ph.D. (2017) in Computer Science from UGA. His roles include directing the Computer Science Undergraduate Assistant (CSUA) and UGAHacks experiential learning programs. He chairs the Undergraduate Program & Curriculum Committee and serves on UGA’s University Council. Dr. Cotterell’s teaching career began in 2012 with Software Development courses, transitioning to full-time instructor in 2015. He has won multiple teaching awards, including the Teaching Excellence in Computer Science Award (2018, 2020) and was promoted to Senior Lecturer in 2021. He has also served as a UGA Online Learning Fellow, Writing Fellow, and Teaching Academy Fellow. His research interests span computational education, active learning methodologies, and technical fields like big data analytics, ontology-based semantics, and energy informatics. His work bridges pedagogical innovation with applied computational science. Dr. Cotterell’s publications focus on improving educational practices, predictive analytics, and interdisciplinary applications of computer science. His most recent work emphasizes student sentiment analysis in active learning environments and scalable energy systems modeling. Awards include the 2016 Outstanding Faculty Teaching Award and multiple fellowships recognizing his contributions to pedagogy and online education. He oversees undergraduate program development and coordinates experiential learning initiatives, emphasizing hands-on learning through hackathons and assistantship programs.

Andrea BenigniView profile

Professor

• Energy Systems
• Power Grids
• Simulation Tools
• +5 more

Prof. Andrea Benigni is a Professor and Director at the Research Center Jülich GmbH, leading the Energy System Technology (ICE-1) department within the Institute of Climate and Energy Systems (ICE). His work focuses on advanced simulation tools for multi-energy systems, power grid optimization, and real-time control solutions. Key research areas include: Multi-energy system integration (power, gas, thermal) High-performance simulation frameworks (e.g., GasNetSim, HeatNetSim) Quantum computing applications for grid partitioning Hydrogen blending in gas networks Hardware-in-the-loop testing for control architectures PMU-based fault detection and grid resilience Benigni has pioneered open-source tools like HeatNetSim and contributed to FIWARE-based ICT platforms for building/district-level energy systems. His recent work emphasizes digital twin applications for pseudo-measurement generation and parallel simulation techniques leveraging GPUs and FPGAs. Notable achievements include: Development of MGRIT-based parallel-in-time electromagnetic simulations Optimization methods for battery sizing in multi-vector systems Quantitative analysis of high PV penetration impacts in African grids Current projects involve: Hydrogen integration strategies for Southern Italy gas networks DC microgrid communication protocols via low-frequency injection Cloud-based multi-agent systems for grid flexibility management

Uwe BreitenbücherView profile

Professor

• Cloud Computing
• IT Systems Management
• Internet of Things
• +3 more

Prof. Dr. Uwe Breitenbücher is a Professor of System Architecture at Reutlingen University's Faculty of Informatics. He holds a Diplom in Computer Science (2011) and a PhD (2016) from the University of Stuttgart. His research focuses on cloud computing, IT systems management, IoT, blockchain, and pattern languages for software architecture. He also leads educational initiatives in software engineering pedagogy, including gamified e-learning platforms like IT-REX and Gamify-IT. Education: Diplom-Informatiker (2011), University of Stuttgart Dr. rer. nat. (2016), University of Stuttgart His research interests emphasize practical deployment solutions for distributed systems, including cross-component issue management, blockchain interoperability, and cloud orchestration using TOSCA standards. He actively develops tools like Variability4TOSCA and Dromi to address challenges in deployment variability and microservice architecture. His recent articles highlight trends in cross-chain smart contract invocations, gamified education systems, and orchestration of heterogeneous deployment technologies. He has contributed to over 50 peer-reviewed publications since 2018, focusing on cloud automation, blockchain integration, and software engineering education. He chairs the Bachelor's Examination Board for Digital Business and collaborates with industry on projects like the 5G-PreCiSe initiative. His work bridges academic research with practical deployment challenges in modern distributed systems.

• Software Engineering
• Machine Learning
• API Testing
• +4 more

Michael Maire is a researcher at the University of Chicago focusing on the intersection of software engineering and machine learning, specifically addressing challenges in integrating and testing machine learning APIs within software systems. His research spans Software Engineering and Machine Learning with concentrated expertise in API Testing, Software Integration, Automated Testing, Cloud Computing, and Software Reliability. He investigates practical methodologies for ensuring correct implementation and robust performance of machine learning services in real-world software environments, emphasizing error prevention and system correctness. Analysis of his publication trajectory reveals consistent emphasis on machine learning API reliability, evolving from empirical studies of API usage patterns (2021) to automated testing frameworks (2022) and ultimately run-time failure prevention systems (2023). This progression demonstrates growing technical sophistication in addressing integration vulnerabilities, with increasing focus on proactive error mitigation in cloud-based ML deployments. Scientific Awards: No awards or honors were documented in the source materials. Advising and Grants: Available information does not specify doctoral advisees, research grants, or funded projects.

Zilong YeView profile

Associate Professor

• Computer Networking
• Network Function Virtualization
• Software-Defined Networking
• +6 more

Zilong Ye is an Associate Professor in the Department of Computer Science at California State University, Los Angeles, within the College of Engineering, Computer Science, and Technology. He holds a Ph.D. in Computer Science from University at Buffalo, SUNY (2015), an M.S. from Shanghai Jiao Tong University (2010), and a B.S. from Shandong University (2007). Ph.D., Computer Science, University at Buffalo, SUNY M.S., Computer Science, Shanghai Jiao Tong University B.S., Computer Science, Shandong University His research focuses on computer networking, with emphasis on Network Function Virtualization, Software-Defined Networking, Fog Computing, and Optical Networking. He has pioneered work in distributed fiber optic sensing and infrastructure-as-a-sensor systems, addressing challenges in sensor placement, network survivability, and concurrent sensing capabilities. Publications from 2013-2024 span optical networking, IoT security, and cloud optimization, with recent work on UAV-based mobile edge computing and fiber optic sensing. Awards include Best Paper (ICC 2021) and Best Demo (ACM ICN 2016). TPC co-chair for ACM Mobihoc workshop on MobileHealth (2018) Organized international symposia on 5G technologies and SDN/NFV Journal reviewer for IEEE Transactions on Network and Service Management, Mobile Computing, and others Patents include distributed fiber optic sensor placement systems and methods for information-centric networks. Teaching includes advanced courses in computer networks and operating systems.

• Computer Science
• Sensor Networks
• Robotics
• +5 more

Ákos Lédeczi is a prolific researcher with significant contributions to computer science, sensor networks, robotics, and K-12 education. His work spans hardware-software co-design, wireless localization, and accessible programming environments. Co-developed NetsBlox and DeepForge for novice-friendly distributed computing. Created PinPtr high-precision GPS cloud service and inTrack mobile node tracking systems. Pioneered Browser-based robotics simulation and smartphone IoT education for K-12 students. Explored RF interferometry , Doppler shift tracking , and acoustic shooter localization in urban environments. Contributed to medical capsule robot design and security co-design for embedded systems. His recent focus includes project-based AI curricula for female high school students and collaborative visual programming environments . While specific university affiliations aren't detailed here, his collaborations with Péter Völgyesi, Miklós Maróti, and others highlight his role in advancing distributed and sensor network research.

Zhen Ming JiangView profile

Associate Professor

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +5 more

Zhen Ming (Jack) Jiang is an Associate Professor and York Research Chair (Tier II) in Software Engineering for Foundation Model-Powered Systems at the Department of Electrical Engineering & Computer Science, York University, Canada. He earned his Ph.D. (2013) from Queen's University and MMath/BMath degrees from the University of Waterloo. Research Focus: Software Engineering for AI, Performance Engineering, Logging Practices, and Software Visualizations. Education: Ph.D. in Computer Science, Queen's University MMath in Computer Science, University of Waterloo BMath in Computer Science, University of Waterloo His research explores engineering rigor in AI-powered applications, performance optimization in foundation model-driven systems, and efficiency improvements in large-scale software. Recent work analyzes logging practices, code cloning in blockchain, and AIOps models. He has received prestigious awards including the NSERC Discovery Accelerator Supplements (2020) and multiple Best Paper Awards at ICST, ICSE, and MSR. He served on program committees for ICSE, ICSME, and ICPE, and reviewed for top journals like IEEE Transactions on Software Engineering.

• Big Data Analytics
• Distributed Machine Learning
• Wireless Communication
• +3 more

Shadi Khalifa is an Adjunct Assistant Professor with expertise in Big Data Analytics , Distributed Machine Learning , and Wireless Communication . His work bridges Cloud Computing and Data Mining with practical applications in MapReduce , Analytics-as-a-Service , and LTE Systems . Research Trends : Analysis of Shadi Khalifa’s publications reveals a focus on distributed computing and big data optimization . Key themes include inter-cell interference coordination in wireless networks, smart big data frameworks , and cloud-based analytics . His work emphasizes scalability, efficiency, and integration of machine learning with infrastructure.

• Global Navigation Satellite Systems
• GNSS Signal Processing
• Satellite Navigation Receivers
• +5 more

Fabio Dovis is a Full Professor at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, and a member of the Interdepartmental Center PIC4SeR (PoliTO Interdepartmental Center for Service Robotics). His career spans multiple decades with significant contributions to Global Navigation Satellite Systems (GNSS) research and applications. Dr. Dovis serves on the Steering Committee of the Institute of Navigation (2021-2023) and is an Editorial Board member of GPS SOLUTIONS since 2017. His research focuses on satellite navigation technologies with applications spanning from environmental monitoring to space exploration. He leads the Navigation, Signal Analysis and Simulation (NavSAS) Research Group, which is actively developing innovative GNSS solutions. His research portfolio includes satellite navigation receiver design, GNSS for environmental and atmospheric monitoring, GNSS positioning security, and applications in service robotics and precision agriculture. His work bridges theoretical advancements with practical implementations across diverse domains, from terrestrial navigation systems to lunar exploration. Dr. Dovis has supervised numerous PhD students working on cutting-edge GNSS research, with current students focusing on areas such as lunar navigation, GNSS interference monitoring, and robust positioning solutions for challenging environments. His research spans multiple EU-funded projects including EMERITUS (2022-2025), LuGRE (2021-2025), and ROOT (2020-2022). Steering Committee member - Institute Of Navigation, USA (2021-2023) Editorial Board member - GPS SOLUTIONS (2017-) Program chair - International Conference on Localization and GNSS 2013 He has contributed to numerous patents in GNSS technology and serves as Scientific Director for multiple research initiatives including the NODES program under the PNRR framework. His recent publications demonstrate a strong focus on advancing GNSS capabilities for space exploration, particularly for lunar missions, as well as addressing critical challenges in GNSS security and reliability.

Andrea ArcuriView profile

Professor

• Automated Software Testing
• Search-based Software Engineering
• Enterprise Software Development
• +7 more

Professor Andrea Arcuri is a leading academic in software engineering at Kristiania University College (formerly Westerdals), Oslo, where he has been a full-time Professor since October 2016 and leads the AISE (Automated Intelligent Software Engineering) lab. Additionally, he holds a part-time Adjunct Professor position at Oslo Metropolitan University (OsloMet) since 2020. His research interests revolve around Automated Software Testing and Search-based Software Engineering , with a focus on tools like EvoMaster (for system-level testing) and EvoSuite (for Java unit testing). His work integrates testing, security, and development practices for enterprise systems, particularly using SpringBoot , Kotlin , and Docker technologies. He has contributed to open-source educational materials on enterprise development, testing, and security, including courses PG5100 and PG6100 at Kristiania University College. His publications emphasize practical applications, such as cloud deployment, microservice architectures, and secure coding practices. Notable awards include: ACM SIGSOFT Impact Paper Award (2023) ICST 10-Year Most Influential Paper (2022) ICSE 10-Year Most Influential Paper (2021) Best Paper Awards at SSBSE (2017, 2015) IEEE Software Award (2017) ACM Distinguished Paper Awards (ASE 2015, ISSTA 2010) Best PhD Paper at SBST (2008) Professor Arcuri supervises PhD candidates and postdocs in automated testing and software quality, while actively serving on program committees for top journals and conferences. He advocates for hands-on learning through his open-source educational repository, which emphasizes Docker integration and practical examples for enterprise systems.

Stefan LankesView profile

Researcher

• Operating Systems
• System Software
• High-Performance Computing
• +4 more

Dr. rer. nat. Stefan Lankes is an academic researcher at the Chair of Automation of Complex Power Systems, RWTH Aachen University's Faculty of Electrical Engineering and Information Technology. His work focuses on operating systems, high-performance computing (HPC), cloud computing, and lightweight virtualization techniques for embedded and real-time systems. Stefan holds a PhD in Electrical Engineering (2003) for his dissertation on real-time distributed platforms. His career spans roles from Scientific Assistant (1998-2004) to Academic Director (since 2019), with key contributions to HPC infrastructure and simulation environments. Research highlights include Rust-based OS development ( HermitCore unikernel ), GPU virtualization in distributed systems, and energy-efficient embedded computing paradigms. He pioneered the FlippedOS digital teaching platform using virtual workstations for operating systems education. Scientific awards include the 2016 Digital Teaching Fellowship and the 2021 RWTH Lecturer distinction. His publications cover topics from NUMA memory management to real-time CORBA protocols, with recent works addressing unikernel security and CUDA virtualization. Stefan leads simulation infrastructure and HPC virtualization projects, with affiliations to the E.ON Energy Research Center and involvement in European workshops like Euro-Par. His work bridges system software innovation with practical applications in energy systems and supercomputing.

• Biomedical Informatics
• Machine Learning
• Data Mining
• +5 more

Dr. Yanqing Ji is a Professor in the Department of Electrical and Computer Engineering at Gonzaga University, specializing in biomedical informatics and high-performance computing. He serves as an editor for the Journal of Digital Signal Processing and a reviewer for 23 international journals. Education: Ph.D. in Computer Engineering, Wayne State University M.Sc. in Physical Electronics, University of Science & Technology of China B.E. in Industrial Automation, Qingdao University Dr. Ji's research focuses on biomedical association mining, adverse drug reaction detection, and parallel/cloud computing applications in healthcare. His work integrates machine learning, fuzzy logic, and multi-agent systems to enhance drug safety surveillance and biomedical literature search. His publications emphasize scalable MapReduce solutions for biomedical text mining, temporal association mining for drug interactions, and intelligent agent systems for pharmacovigilance. These span prestigious conferences like IEEE BIBM, ITNG, and NAFIPS, alongside journals such as BMC Bioinformatics and IEEE Transactions on Knowledge and Data Engineering . Scientific awards include NIH R21, AHRQ R18 grants, and NSF-funded projects (IGERT 9987598, MRI 9977815, ITR 0081696). He has led system design for distributed healthcare applications and optimized decision models using genetic algorithms.

Nura AbubakarView profile

Lecturer

• Cloud Computing
• Distributed Simulation
• Agent-Based Modelling

Nura Abubakar is an Associate Lecturer in Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences, with over 20 years of experience in software engineering and systems management. Her work bridges industry expertise with academic research in cloud computing and distributed simulation. Education: International Diploma in ICT Advanced Diploma in ICT BSc Computing and Software Engineering MSc Software Engineering PhD Computer Science Research Interests: She focuses on cloud-based distributed simulation (CBDS), agent-based modeling, and scalable cloud architectures. Her pioneering work on the Distributed Simulation Cloud Architecture for Experimentation (DICE) demonstrates how cloud computing can enable cost-effective, high-performance simulation systems. Teaching Activities: Dr. Abubakar teaches modules in Cybersecurity, Network Computing, Business Analysis and Process Modelling, and Network and Operating Systems. Professional Affiliations: The Council for the Regulation of Engineering in Nigeria (COREN) Nigeria Computer Society (NCS) Computer Professionals Association of Nigeria (CPN) Institute of Software Practitioners of Nigeria (ISPON) Academia in Information Technology (AIT) Association for Computing Machinery (ACM) Association for Information Systems (AIS) Institute of Electrical and Electronic Engineers (IEEE) The Society for Digital Information and Wireless Communications (SDIWC) The Operational Research Society (ORS), London British Computer Society (BCS), London The Institute of Leadership & Management (I'm), London