Siegmar Sommer is a Researcher at the Humboldt University of Berlin , affiliated with the Institute of Computer Science under the Faculty of Mathematics and Natural Sciences . He has worked at the university since 1986 in various technical and scientific roles. Dipl.-Ing. in Computer Engineering (1982) Dr.-Ing. in Computer Science (1986) Postgraduate studies in Higher Education (1990) His research focuses on networking , distributed systems , and network security , with historical contributions to optical information transmission , LAN protocols , and security-relevant systems . His work bridges hardware-software co-design and educational theory in technical disciplines. The 1980s-1990s articles highlight expertise in LAN architecture, optical communication, and security frameworks. Keywords span Networking , Operating Systems , and Education , with subfields like Fiber Optic Networks , CSMA/CD Protocols , and Higher Education Curriculum . He contributed to the Computer Engineering Group and holds a patent for " Bus Access Method for a Local Computer Network " (1986). His teaching legacy includes courses on programming languages (BASIC, PASCAL, PEARL), computer graphics, and modern topics like Wireless Communication Systems and Reliable Distributed Systems . Contact: Email: sommer@informatik.hu-berlin.de Phone: +49 30 2093-41256 Office: Room IV.303, Rudower Chaussee 25, Berlin-Adlershof
Patric Genfer is a researcher in the Faculty of Computer Science specializing in Software Architecture with a focus on microservice systems. His work combines static code analysis , component modeling , and repository mining to address architectural challenges in distributed systems. Active in microservice architecture and code-model consistency Co-developed detector-based abstraction frameworks for architectural evolution Published in top venues like Empirical Software Engineering and ECSA Recent research includes security tactics in microservice APIs and metric visualization for software portfolios . He received two major awards: the Best Paper Award (2021) and Distinguished Open Artifact Award (2024). Collaborates with experts like Uwe Zdun, Cesare Pautasso, and Wilhelm Hasselbring. Scientific Awards: Best Paper Award (2021) Distinguished Open Artifact Award (2024) Participated in international conferences (ECSA 2024, WICSA 2021) and presented work on data exposure prevention and software quality metrics in microservice environments.
Mathias Fischer is Professor for Computer Networks at the University of Hamburg since December 2021, affiliated with the MIN Department of Informatics. He previously served as an assistant professor at Universität Hamburg (2016-2021), University Münster (2015-16), and held postdoctoral positions at the International Computer Science Institute/UC Berkeley (2014-15) and the Center for Advanced Security Research Darmstadt/TU Darmstadt (2012-14). His educational background includes a PhD in Computer Science from TU Ilmenau (2012) and a diploma in Computer Science from the same institution (2008). He also served as Head of Data Literacy Education in IT Support at the University of Hamburg's ISA Center. Professor Fischer's research spans critical areas of modern network infrastructure, with particular emphasis on IT and network security , resilient distributed systems , and network monitoring . His work addresses fundamental challenges in cybersecurity including botnet monitoring, intrusion detection, and critical infrastructure protection. His research group actively investigates P2P networks and develops innovative approaches to network security that balance functionality with privacy preservation. Analysis of his recent publications reveals a strong focus on privacy-enhancing technologies, network security protocols, and resilient distributed systems. His research trajectory shows increasing attention to practical implementations of security solutions for edge computing environments, digital twin networks, and time-sensitive networking applications. The work demonstrates sophisticated integration of cryptographic techniques with network architecture design to address emerging security challenges in distributed systems. Among his notable recognitions are the Claussen-Simon Competition for Universities (2019), the University Prize of the Claussen-Simon Foundation (2019), and an Outstanding Paper Award at ACSAC (2018). Claussen-Simon Competition for Universities (2019) University Prize of the Claussen-Simon Foundation 2019 Outstanding Paper Award at ACSAC (2018) Professor Fischer leads multiple significant research projects including SOVEREIGN (Technologically sovereign security monitoring), RESISTANT (Resilient zero-trust platform for aircraft), and Dynamic situational awareness for rescue teams. His research group comprises numerous doctoral and master's students working on cutting-edge network security challenges. Current projects focus on developing resilient data and AI platforms for crisis situations, security monitoring for critical infrastructures, and innovative home network security solutions. The Computer Networks research group at the University of Hamburg, led by Professor Fischer, maintains active collaborations with industry and academic partners. The group operates specialized laboratories focused on network security testing, intrusion detection systems, and resilient network architectures. Current research directions include QUIC protocol security, federated learning security, and privacy-preserving network analytics, with strong emphasis on practical implementations that address real-world security challenges.
Scott F. Midkiff is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His research focuses on networking, telecommunications, and cybersecurity, with particular emphasis on 5G, O-RAN, edge cloud computing, and interference management in wireless networks. He holds a Ph.D. from Duke University (1985), an M.S.E.E. from Stanford University (1980), and a B.S.E. from Duke University (1979). Midkiff’s work spans theoretical and applied domains, including stochastic optimization for RAN intelligent controllers, network slicing, and wireless control plane design. He has contributed to advancements in interference alignment, MIMO systems, and secure spectrum sharing. His awards include the ORBIE Award and Capital CIO of the Year. Awards: ORBIE Award, Capital CIO of the Year Service: Member at Large, IEEE Committee on Engineering Accreditation Activities; ABET Program Evaluator His research group explores cutting-edge topics like software-defined cellular networks, distributed scheduling in underwater networks, and energy-efficient routing in sensor networks. Midkiff is affiliated with Virginia Tech’s research initiatives in pervasive computing and sustainable wireless systems.
Dr. Sharmin Jahan serves as a tenure-tracked Assistant Professor in the Department of Computer Science at Oklahoma State University since August 2022. Her research centers on dynamic security assurance for autonomous systems (self-adaptive systems) through explainable AI models that interpret uncertain operational environments to enable autonomous security decision-making and compliance maintenance. Her educational background includes a Ph.D. and Master's in Computer Science from the University of Tulsa (2018-2021), and a B.Sc. in Computer Science and Engineering from Bangladesh University of Engineering and Technology (2007-2012). She teaches Introduction to Computer Security (CS 4243/5243) and leads Dr. Jahan's Lab focused on security for autonomous systems. Research interests span Explainable AI in Cyber Security, IoT Security, Self-Protecting Systems, and Micro-service Security. Her work develops frameworks that embed security awareness in dynamic systems, using XAI to interpret environmental uncertainty and maintain security compliance through autonomous adaptation. Current projects explore machine learning models for security analysis and XAI challenges in domain-specific security applications. Recent publications (2025-2020) demonstrate concentrated research on security assurance in self-adaptive systems, particularly for IoT and microservice architectures. Key trends include XAI-driven anomaly detection, security profile extraction from operational data, and risk-adaptive access control. Subfield specializations cover service mesh security, blockchain-based access frameworks, runtime trust evaluation, and autonomous threat containment. Scientific awards include: Principal Investigator for 2023 Arts and Sciences Summer Research Award on XAI-enhanced security awareness in autonomous systems Senior personnel on 2022 NSF RET Grant for Big Data and Machine Learning research experiences She advises M.Sc. student Masrufa Bayesh and teaches graduate/undergraduate security courses. Her lab actively investigates frameworks for security assurance in dynamic environments, with emphasis on IoT and microservice architectures requiring continuous adaptation to environmental changes while maintaining security compliance. Dr. Jahan's research team develops analysis and assessment models to determine security compliance degradation risks and optimal adaptation strategies, enhancing system resiliency through separate analytical frameworks integrated with her PhD-developed assessment methodology.
Shaddi Hasan is an Assistant Professor of Computer Science at Virginia Tech's College of Engineering. His research focuses on building equitable network infrastructure for underserved regions, emphasizing human-centered design through collaborations with users and policymakers. He holds a Ph.D. (2019) from UC Berkeley and a B.S. (2010) from the University of North Carolina at Chapel Hill. Education: Ph.D. in Computer Science, UC Berkeley (2019) M.S. in Computer Science, UC Berkeley (2013) B.S. in Computer Science, UNC Chapel Hill (2010) Research interests span networks, ICTD, HCI, and distributed systems. Key projects include the Magma open-source core network platform (developed at Facebook Connectivity) and CellBricks for modular rural cellular deployment. His work frequently involves real-world deployments in developing regions. Notable awards include the NSDI 2023 Community Award and multiple best paper recognitions. Current projects analyze broadband mapping accuracy and consumer label interpretation, with a focus on policy implications. Advising: Actively mentoring PhD students and undergraduates. Lab: SPIN Lab (Systems, People, Infrastructure, and Networks). Projects include GitHub repositories for Broadband Data Kit and Magma.
Marinko Sarunic is an Adjunct Professor at the School of Engineering Science , Simon Fraser University . He holds a PhD in Biomedical Engineering from Duke University and has been recognized as a Michael Smith Foundation for Health Research Scholar . His research focuses on biomedical imaging , particularly optical coherence tomography (OCT) , microscopy , and low-coherence interferometry , with applications in diabetic retinopathy , Alzheimer’s disease , and age-related macular degeneration . Dr. Sarunic's work spans adaptive optics , deep learning , and sensorless OCT systems , emphasizing clinical translation and open-source software development (e.g., OCTAVA ). His Google Scholar publications highlight multimodal imaging , vascular heterogeneity analysis , and AI-driven diagnostics for retinal diseases. His contributions include the Michael Smith Foundation for Health Research Scholar award. Though not currently teaching courses, his collaborations and leadership in retinal imaging and medical device innovation are pivotal for advancing non-invasive diagnostics in neurodegenerative and diabetic conditions .
Zhen Xie is an Assistant Professor in the Department of Computer Science at Binghamton University (SUNY), serving as Director of the Parallel Computing and Intelligent System (PCIS) Lab. He holds a PhD from the Chinese Academy of Sciences and a BA from Wuhan University of Technology. His research focuses on high-performance computing (HPC), machine learning, and their intersections, particularly optimizing performance for HPC and AI/DL applications across heterogeneous architectures. Research Highlights: Dr. Xie’s work emphasizes system-level performance optimization for ML and HPC, including GPU acceleration, memory optimization, and AI accelerator selection. His team has won the ACM Gordon Bell Special Prize (2022) for their GenSLMs project predicting SARS-CoV-2 evolution. Recent grants include a 2024 gift from OpenAI for AI testbed initiatives. Awards: ACM Gordon Bell Special Prize (2022), Impact Argonne Awards (2023) Lab: PCIS Lab explores middleware for parallel computing, targeting scientific simulations and big data analytics. Collaborations include Argonne National Lab and Lawrence Berkeley National Lab. Teaching: Teaches Distributed Systems (CS 457/557) and oversees independent studies. Previously trained researchers at Argonne’s ATPESC program. Grants & Collaborations: Subcontract with Lawrence Berkeley Lab (HEVI-LOAD), Argonne testbed expeditions, and OpenAI-funded projects. Active in DOE labs like Summit and Aurora supercomputers.
Marie-Hélène Abel is a Professor and Director of the Computer Science Department at the University of Technology of Compiègne (UTC), France. She leads the Heudiasyc laboratory (UMR CNRS 7253) and specializes in decision making, knowledge engineering, knowledge graphs, and multi-agent systems. Her work focuses on collaborative systems, organizational learning, and the integration of social data into decision support frameworks. She has been recognized with prestigious awards, including Senior IEEE membership (2017) and the 2017 K2 Trophy for participatory computing innovations. Her research emphasizes the development of systems like the MEMORAe platform, which supports learning ecosystems through collaborative environments and organizational memory. She collaborates internationally with institutions such as the Pontifical Catholic University of Paraná (Brazil) and industry partners including Thales, Alstom Transport, and PSA. Key projects include crisis simulation systems and ontology-based frameworks for Industry 4.0 collaboration. Abel’s academic contributions span over 50 peer-reviewed articles, with recent works addressing context-aware recommender systems, crisis management simulations, and teacher efficacy in digital education. Her leadership roles include directing research projects, overseeing the Computer Engineering Department, and advancing ethical AI practices through initiatives like the Sorbonne.AI network. Education: HDR (Habilitation à Diriger des Recherches) on 'Contribution of Organizational Memories in a Learning Context' (2007) Administrative Roles: Equality Officer, University Antiracism/Anti-Semitism Officer International Collaborations: Brazil, Egypt, and Tunisia
Krzysztof Czarnecki is a Professor at the University of Waterloo's Department of Electrical and Computer Engineering, with a cross-appointment to the School of Computer Science. He serves as leader of the Waterloo Intelligent Systems Engineering Lab and holds the title of University Research Chair. His research focuses on generative software development, model-driven engineering, and autonomous systems, particularly in automotive cybersecurity and perception safety. Education: Doctorate in Computer Science, Technical University of Ilmenau (1999) Master of Science in Computer Science, Technical University of Ilmenau (1995) Bachelor of Science in Computer Science, California State University (1994) Research Interests: Dr. Czarnecki's work spans generative programming, software product lines, and safety-critical AI for autonomous vehicles. Recent projects address robust perception systems, uncertainty quantification in neural networks, and strategic driving behavior modeling. He co-authored Generative Programming (Addison-Wesley, 2000), a foundational text in the field. Publications Trends: Recent work emphasizes multimodal AI integration (e.g., LEO-MINI), 3D object detection improvements (OV-SCAN), and safety assurance frameworks for autonomous systems. His research bridges theoretical software engineering with applied robotics challenges. Awards: Premier’s Research Excellence Award (2004) British Computing Society’s Upper Canada Award (2008) University Research Chair, University of Waterloo (2023) Teaching & Leadership: Teaches courses like ECE 495 (Autonomous Vehicles) and ECE 651 (Software Engineering Foundations). Oversees WatCAR initiatives and collaborates on industry projects through the NSERC Bank of Nova Scotia Industrial Research Chair (previous). Labs & Teams: Directs the Waterloo Intelligent Systems Engineering Lab, focusing on AI-driven solutions for autonomous systems and safety-critical software. Active in cross-disciplinary collaborations with automotive and robotics partners.
John McNamara is an IBM Master Inventor and Advanced Visiting Research Fellow at the University of Sheffield, holding Honorary Professorships at University College London (UCL) and Sheffield Hallam University. He specializes in interdisciplinary innovation across cybersecurity, transportation systems, and artificial intelligence, leveraging technologies like Cloud and Watson for Tech for Good initiatives. His roles include IBM Technical Specialist, IBM Thought Leader, and Open Group Distinguished Technical Specialist, with industry expertise spanning defense, finance, and healthcare sectors. Education: BSc (Hons) in Information Systems from the University of Hull. Research focuses on patentable inventions addressing complex event processing, automated systems optimization, and regulatory compliance. Key innovations include intelligent fuel management systems, automated style-checking frameworks, and goal-directed simulation tools for business processes. His work bridges academic research with real-world industry applications. Awards: IBM Master Inventor IBM Thought Leader Technical Specialist Open Group Distinguished Technical Specialist Collaborates with IBM UK University Programs to develop socially impactful technologies. Active in creating solutions for disease control, banking systems, and defense applications through cross-disciplinary partnerships.
Kristopher Micinski is an Assistant Professor in the Electrical Engineering and Computer Science Department at Syracuse University. His research focuses on scalable program analysis, static analysis, and formal methods applied to computer security and privacy. He holds a PhD in Computer Science from the University of Maryland and a BS in Computer Engineering from Michigan State University. Education: PhD, Computer Science, University of Maryland at College Park BS, Computer Engineering, Michigan State University Research Interests: His work bridges theory and application of program analyses, emphasizing scalable static analysis frameworks, Datalog optimization for distributed systems, and security applications. Recent efforts include GPU-accelerated Datalog engines and large-scale malware analysis pipelines like Assemblage. Grants & Projects: NSF PPoSS Large: $1M grant for declarative analytics DARPA V-SPELLS: $400K for legacy software optimization Assemblage: $350K DoD grant for malware classification Teaching: He teaches undergraduate and graduate courses on programming languages (CIS352) and formal methods (CIS700), with materials publicly available on YouTube.
Hoda Maleki is an Assistant Professor in the Department of Computer & Cyber Sciences at Augusta University's School of Computer and Cyber Sciences. She holds a Ph.D. (2019) and an M.S. in Computer and Information Sciences from the University of Connecticut. Her research focuses on cybersecurity, blockchain technology, digital forensics, and secure access control systems. She has contributed to frameworks like ForensiBlock, exploring blockchain for data provenance and auditability, and has published extensively on topics including machine learning in healthcare cybersecurity and multi-dimensional encryption techniques. Dr. Maleki serves on Augusta University committees including the Faculty Affair Committee and the MS Cybersecurity degree development workgroup. She advises the Women in Cybersecurity Club and the VIVID team. Her professional service includes roles as a grant proposal reviewer for NSF and CICI-NSF, and committee membership for conferences like CCSW'24 and IPDPS. Her recent work emphasizes integrating blockchain with AI for secure systems, such as DLACB (Deep Learning-Based Access Control using Blockchain) and ForensiBlock. Awards include the 2023 Faculty Inclusive Excellence Initiative and 2022 Faculty Recruitment and Retention honors. She teaches advanced courses on cybersecurity topics like secure pollbook systems and cryptographic protocols.
Dr. Chunming Qiao is a SUNY Distinguished Professor and Chair of the Department of Computer Science and Engineering at the University at Buffalo (SUNY) , leading the Lab for Advanced Network Design, Evaluation and Research (LANDR) since 1993. His work spans cyber-physical systems , optical networks , and Internet of Things (IoT) , with a focus on safety, reliability, and protocol design. Education: PhD in Computer Science from the University of Pittsburgh (1993) BS in Computer Science and Engineering from the University of Science and Technology of China (1985) Dr. Qiao’s research interests combine theoretical and applied network design, including autonomous vehicles , quantum computing , and cloud services . He pioneered optical burst switching (OBS) and iCAR systems for wireless convergence, cited in BusinessWeek and Wireless Europe . His recent publications emphasize quantum networking , federated learning , and autonomous driving security , with projects on entanglement routing , edge inference optimization , and LiDAR adversarial attacks . Articles span IEEE and ACM venues , and include best paper awards . Scientific Awards: TC-CSR Distinguished Technical Achievement Award (2015) SUNY Chancellor's Award for Excellence (2013) IEEE Fellow (2009) UB Exceptional Scholar-Sustained Achievement Award (2005) Dr. Qiao has secured over two dozen NSF grants and collaborations with Google , Cisco , and NEC Labs . His 7 US patents and consulting experience highlight his industry impact, while his editorial roles and conference leadership underscore academic influence. He actively contributes to multi-disciplinary research through the New York State Center of Excellence in Bioinformatics and Life Sciences and CEDAR , advancing high-performance computing and document analysis .
Samir Ouchani is a Research Director at the CESI LINEACT laboratory (Aix-en-Provence, France), affiliated with the CESI Engineering School. He holds a PhD in Computer Science from Concordia University (2013) and an HDR (Accreditation to Supervise Research) from CNAM Paris (2022). His research focuses on securing cyber-physical systems (CPS) through formal methods, blockchain, and AI-driven approaches. Key roles include leading projects on resilient CPS architectures, IoT security, and federated learning in industrial contexts. Education: 2022: HDR in Security and Reliability of Smart CPS (CNAM Paris) 2013: PhD in Computer Science (Concordia University, Montreal) 2006: Master in Computer Science (Lorraine University, France) 1997: Engineering Degree in Computer Science (Djillali Liabess University, Algeria) Research Interests: His work emphasizes secure CPS design, including cryptographic protocols for IoT, formal verification frameworks, and AI applications for intrusion detection. He explores blockchain for smart cities, federated learning in distributed systems, and resilience engineering for autonomous vehicles. Recent projects include developing PUF-based authentication protocols and digital twin architectures for resource-constrained systems. Advising & Collaborations: Supervised PhD theses on IoT security (Fahem Zerrouki), smart city formal verification (Walid Miloud Dahmane), and federated learning in industrial CPS (Souhila Bedra Guendouzi). Collaborates with institutions like Blida University (Algeria) and HESAM University. Active in conferences such as CRISIS, ICFNDS, and IEEE WETICE. Labs & Teams: Leads the Engineering and Numerical Tools research team at CESI LINEACT, focusing on model-based design, CPS simulation, and cybersecurity tool development. Engaged in EU-funded projects on Industry 4.0 and smart infrastructure security.
