Find Academic Supervisors

Iryna YevseyevaView profile

Associate Professor

• Cyber Security
• Operational Research
• Multi-Criteria Decision Analysis
• +7 more

Iryna Yevseyeva is an Associate Professor in Computer Science at De Montfort University, affiliated with the Faculty of Computing, Engineering and Media and the School of Computer Science and Informatics. She leads the Cyber Security subject group and serves as Deputy Director of the Cyber Technology Institute. Her academic journey includes research roles at Newcastle University, the University of Leiden, Polytechnic Institute of Leiria, INESC Porto, and the University of Algarve. PhD in Multicriteria Decision Aiding, University of Jyväskylä, Finland Postdoctoral experience in the Netherlands, Portugal, and the UK Fellow of the Higher Education Academy (FHEA) Her research focuses on the application of operational research methods—particularly multi-criteria decision analysis and multiobjective optimization—to critical challenges in cyber security, including risk assessment, investment decisions, threat intelligence, and human behavior. She integrates decision science with cybersecurity to develop practical, data-driven frameworks for security governance and incident response. The recent publications highlight a strong trajectory in applying advanced computational and optimization techniques to cybersecurity problems. Themes include evolutionary optimization for privacy metrics, gamified training for incident response, human error modeling (IS-CHEC), and portfolio optimization in both drug discovery and security controls. The interdisciplinary nature spans computer science, operational research, behavioral psychology, and healthcare informatics. DMU Commercialisation Award (2018) Academy of Finland Grant (2008) Erasmus Mundus Grant (2008) Iryna has supervised 4 PhD students to completion and currently co-supervises 5 others. She has led over 10 research projects and secured more than 10 small grants as Principal Investigator, along with industrial grants from Innovate UK and Airbus. Her academic service is extensive, including guest editing for Springer journals, organizing international workshops (LeGO 2018, EMO 2023 track), and peer reviewing for top-tier journals and funding councils like EPSRC, MRC, and Horizon2020. She is actively involved in the Cyber Technology Institute and leads research within the Multi-Criteria Decision Making and optimization domain. Her collaborations span Brazil (Unijuí), Finland, the Netherlands, and Portugal, reflecting a globally connected research profile.

Noah RhodesView profile

Research Fellow

• Power Grid Optimization
• Mathematical Optimization
• Energy Security
• +2 more

Noah Rhodes is a CNLS Postdoctoral Associate at Los Alamos National Laboratory's Center for Nonlinear Studies (CNLS), working within the Theoretical Division (T-Division). His research focuses on mathematical optimization applications for power grid challenges, particularly infrastructure flexibility and wildfire risk mitigation. Office contact: TA-3, Building 1690, Room 123; email: nrhodes@lanl.gov. Educational background includes: B.S. in Electrical Engineering, University of Wisconsin-Madison (2019) Ph.D. Minor in Energy Analysis and Policy, University of Wisconsin-Madison (2022) Ph.D. in Electrical Engineering, University of Wisconsin-Madison (2024) Rhodes' research centers on enhancing power grid resilience through optimization techniques, with emphasis on reducing infrastructure needs and managing wildfire-related outages. His work bridges theoretical mathematics with practical energy security challenges, developing frameworks for public safety power shutoffs and grid restoration under extreme conditions. His 2021-2025 publications reveal a trajectory from foundational grid restoration algorithms toward integrated environmental considerations. Recent work combines carbon intensity analysis with grid operations while advancing open-source tools (PowerModelsRestoration.jl, ElectricityEmissions.jl) for academic and utility applications. Key trends include stochastic optimization for emergency response and topology-aware power flow formulations. No scientific awards are listed in the provided materials. No student advisement or grant information is documented in the source text. Rhodes operates within CNLS—a hub for nonlinear science research at LANL—which fosters interdisciplinary collaboration on complex systems. His work interfaces with T-Division's theoretical frameworks while addressing real-world energy infrastructure vulnerabilities through computational modeling and optimization.

Graham JohnsonView profile

Researcher

• Interactive and high-performance web visualization
• Immersive visualization environments
• Information visualization
• +3 more

Graham Johnson is a Researcher at the National Renewable Energy Laboratory (NREL), affiliated with the Computational Science Center and the Data, Analysis, and Visualization Group . His work focuses on designing high-performance visualization tools for energy systems and decision-making processes. Primary research areas include interactive web visualization, immersive environments, and real-time visual analytics. Formerly at The Aerospace Corporation (2017–2020), he transitioned to NREL to develop advanced visualization pipelines and collaborative tools. His recent publications highlight innovations in energy scenario modeling, contour visualization alternatives, and situational awareness applications. Articles emphasize Computer Science , Energy Systems , and Human-Computer Interaction themes. Education includes dual Masters in Applied Mathematics and Aeronautical & Astronautical Engineering from Purdue University, along with a Bachelor's in the latter field.

Peter PopovView profile

Researcher

• Software Reliability
• System Dependability
• Software Fault-Tolerance
• +5 more

Peter Popov is a Reader at the Centre for Software Reliability (CSR) , City St George's, University of London , where he has been employed since 1997. He specializes in software dependability , fault tolerance , and stochastic modeling of critical infrastructures. Before his current position, he was an Associate Professor at the Bulgarian Academy of Sciences (1990-1997) and a Research Fellow at City St George's. Peter's academic journey began with a PhD in Computer Science from the Kiev National University of Technologies and Design (1989), following his BEng in Computer Engineering from the National Technical University of Ukraine (KPI, 1982). He has worked as a visiting scientist at renowned institutions including the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign , LAAS-CNRS in Toulouse, and Duke University . His research interests span Software reliability assessment System dependability Software fault-tolerance Performance evaluation Interdependencies of critical infrastructures He has contributed extensively to projects such as ReSIST , IRRIIS , DISPO , and AFTER , focusing on the dependability of composite systems and critical infrastructure resilience. Key publication trends reveal expertise in Stochastic modeling of autonomous vehicle safety Software diversity for fault tolerance Interdependency analysis in critical systems Bayesian reliability assessment Performance evaluation of distributed protocols Security implications in cyber-physical systems Peter has supervised several PhD students , including those researching autonomous vehicle resilience , safety assurance with ML components , and adaptable web services . His professional activities include serving on program committees for ISSRE , SAFECOMP , and EDCC conferences, as well as editorial contributions to CEUR Workshop Proceedings . He is proficient in Bulgarian , English , and Russian , with peer-review capabilities in all three languages.

Kizito SalakoView profile

Lecturer

• Software reliability
• Bayesian statistics
• Probability theory
• +7 more

Dr. Kizito Salako is a Lecturer in the Department of Computer Science at City, University of London (now merged with St George's). He is an applied mathematician and software developer at the Centre for Software Reliability, specializing in software reliability assessment using advanced statistical methods. Dr. Salako holds a first-class double honors degree in Mathematics and Statistics from the University of Lagos, a Master of Advanced Study in Mathematics from the University of Cambridge (where he was both a Shell Centenary Scholar and a Commonwealth Scholar), and a PhD in Computer Science from City, University of London. His research focuses on applying probability theory, Bayesian statistics, geometry and machine learning techniques to simulate, assess and forecast the failure behavior of software-based systems. He specializes in conservative Bayesian approaches for dependability assessment, particularly for safety-critical systems. His work has significant applications in autonomous vehicle safety and critical infrastructure protection. Dr. Salako's publications reveal a strong focus on developing statistical techniques that support conservative dependability claims for safety-critical systems, with particular attention to the challenges of assessing reliability when software systems evolve or when operational testing data may be limited. His recent work has increasingly focused on autonomous vehicle safety assessment. He has contributed to numerous research projects including DISIEM (EU Horizon-2020), CEDRICS (EPSRC), AFTER (EU FP7), DIDERO-PC (EPSRC), PIA-FARA (Technology Strategy Board), and others related to critical infrastructure interdependency analysis and cyber security. Dr. Salako is experienced in building simulations of complex systems using C++ and was instrumental in developing the PIA-FARA simulation engine for analyzing probabilistic, functional and process relationships in large-scale interdependent complex critical infrastructure.

• Database Systems
• Natural Language Processing
• Data Mining
• +4 more

Hongrae Lee is a researcher specializing in database systems, natural language processing, and data mining. His work bridges structured data management with language models, focusing on tasks like natural language to SQL translation, similarity joins, and efficient data processing. His research interests include: Database query optimization and similarity search Language model applications for text generation and hallucination correction Web data curation and structured data ecosystems Cloud storage optimization and distributed systems Hongrae Lee's recent publications (2022-2023) highlight trends in large language models (LLMs) for dialogue applications, attributed text generation, and acronym disambiguation with weak supervision. Earlier work (2016-2007) established foundational techniques in database scalability, LSH-based similarity estimation, and geographical data thinning. He has collaborated extensively with researchers at institutions like Google, Seoul National University, and University of British Columbia on projects such as WebTables, LaMDA, and Google Fusion Tables. His contributions span both theoretical advancements (e.g., variance-aware query optimization) and practical systems (e.g., CloudRAMSort, T5-based disambiguation).

Jörn Müller-QuadeView profile

Professor

• Cryptography
• IT Security
• Cybersecurity
• +6 more

Professor Jörn Müller-Quade is a leading expert in cryptography and IT security at the Karlsruhe Institute of Technology (KIT). He serves as Director of the KASTEL — Institute for Information Security and Reliability at KIT and heads the Cryptography and Security research group. Müller-Quade is also the head of the "IT Security, Privacy, Law and Ethics" working group at the Learning Systems Platform initiated by the Federal Ministry of Education and Research. His work focuses on developing secure systems that can withstand intelligent attackers through rigorous mathematical models and cryptographic methods. Professor Müller-Quade's research spans multiple critical areas of modern digital security. His primary interests include cryptography, secure multi-party computations, privacy-preserving analytics, and the intersection of artificial intelligence with security systems. He investigates how to develop security properties that can be mathematically proven, particularly against intelligent adversaries who constantly develop new attack methods. His work on cryptographic voting procedures demonstrates how seemingly contradictory requirements like ballot secrecy and verifiable counting can be simultaneously achieved. Müller-Quade also explores how AI systems change IT security landscapes, creating both new vulnerabilities and potential defense mechanisms. Analysis of Professor Müller-Quade's publications reveals consistent focus on practical security applications with societal impact. His work spans election security, patient data protection, surveillance debates, and industrial espionage prevention. A recurring theme is the need for security systems that remain robust against previously unknown attacks. His publications show increasing attention to AI's dual role in security - both as a tool for attackers and defenders. The evolution of his work demonstrates growing emphasis on European digital sovereignty and the need for mandatory cybersecurity standards. Professor Müller-Quade's notable achievements include: Receiving the German IT Security Award in 2008 for his "Bingo Voting" system Initiating and directing KASTEL, which evolved from a competence center to a permanent institute at KIT Contributing to influential white papers on AI security and medical applications of AI Providing expert testimony on critical security issues to policymakers As Director of KASTEL — Institute for Information Security and Reliability, Müller-Quade leads a major interdisciplinary research effort that brings together cryptographers, IT security experts, software engineers, lawyers, and network specialists. The institute focuses on "Engineering Secure Systems" for economically and socially relevant fields including energy, mobility, and production. Müller-Quade emphasizes the importance of evaluating security in a comprehensive manner, noting that security engineering should ideally encompass all aspects of a system. His team works closely with existing infrastructures to develop practical security solutions that address real-world challenges.

• Parallel Computer architectures
• High Performance Computing
• Multi-/Manycore architectures
• +5 more

PD Dr. Josef Weidendorfer is a qualified private lecturer at Technische Universität München (TUM) and leads the Future Computing Group at the Leibniz Computing Centre (LRZ). He holds a dual affiliation with TUM's Department of Informatics, Chair of Computer Architecture and Parallel Systems (Prof. Schulz), and the Leibniz Rechenzentrum der Bayerischen Akademie der Wissenschaften. His work focuses on developing smooth migration strategies for future HPC systems and evaluating novel technologies to improve system-level and workload analysis tools. Weidendorfer's research interests encompass Parallel Computer Architectures, High Performance Computing, Multi-/Manycore architectures, GPGPU, Performance analysis and optimization, Cache Simulation, Virtual Machines, and dynamic code generation. He is particularly interested in strategies for improving computational efficiency across various hardware structures, including specialized accelerator hardware for HPC codes. He regularly organizes the UCHPC workshop (since 2010 with Euro-Par) about unconventional hardware for HPC computing and is co-organizer of the PSTI workshop series. His recent publications reveal a strong focus on HPC system optimization, with particular emphasis on load balancing techniques, cache partitioning, application malleability, and performance monitoring. The research trajectory shows increasing attention to practical implementation challenges in modern heterogeneous computing environments, especially regarding GPU utilization, resource partitioning under power constraints, and phase-aware system monitoring. Weidendorfer maintains the open-source tools Callgrind/KCachegrind for cache simulation and has supervised numerous student projects across bachelor's, master's, and guided research programs. He teaches courses including Virtualization Techniques, Parallel Programming Systems, and Advanced Computer Architecture, demonstrating strong commitment to both research and education in computer architecture and parallel systems. As principal investigator for multiple large-scale projects including EU Project SEANERGYS (2025-2028) and BMBF Project ScalNext (2022-2025), he leads significant research initiatives focused on future computing technologies and HPC system development.

Michael EkstrandView profile

Assistant Professor

• Recommender systems
• Information retrieval
• Algorithmic fairness
• +5 more

Michael Ekstrand is an Assistant Professor in the Department of Information Science at Drexel University's College of Computing & Informatics, where he leads the INERTIA Laboratory (Impact, Novation, Effectiveness, and Responsibility of Technology for Information Access). His research blends information retrieval, human-computer interaction, and machine learning to ensure AI-powered information access systems (e.g., recommender systems) promote equity and societal well-being. Previously, he co-led the People and Information Research Team (PIReT) at Boise State University. Education : PhD in Computer Science (University of Minnesota, 2014), BS in Computer Engineering (Iowa State University). Research Focus : Ekstrand's work centers on fairness-aware algorithms, social impact quantification, and ethical AI deployment. Key themes include: Algorithmic bias mitigation in recommender systems User behavior modeling in information access Cross-disciplinary approaches to AI ethics Evaluation methodologies for equitable systems Publication Trends : His recent articles (2020-2025) demonstrate a strong focus on algorithmic fairness, particularly gender bias in information systems, statistical evaluation rigor, and user behavior analysis. Over 50% of his latest works directly address fairness metrics or bias mitigation strategies. Advising & Grants : Actively mentors PhD students (e.g., Samira Vaez Barenji, Sushobhan Parajuli) and has supervised 11+ graduate researchers. Secured NSF CAREER funding for projects on recommender systems' societal impact. Leadership : Maintains LensKit (open-source recommender toolkit), holds roles in ACM RecSys/FAccT conferences, and directs the INERTIA lab focusing on responsible information access technologies.

John Stouby PerssonView profile

Associate Professor

• Information Systems
• Agile Software Development
• Pragmatism
• +7 more

John Stouby Persson is an Associate Professor in the Department of Computer Science at Aalborg University's Technical Faculty of IT and Design, specializing in Human-Centered Computing. His research focuses on practical problems experienced by software engineers, interaction designers, and IT professionals, with particular interest in agile development, user experience integration, and digitalization challenges. His research interests span information systems, agile software development, pragmatism, action research, digitalization, IT project management, and big data analytics. Persson approaches research as a collaborative practice of understanding and solving problems in organizing and leading system development, working with both public and private organizations. He has been particularly concerned with how information systems and digitalization are shaped by globalization, sustainability, value complexity and pragmatism. His recent publications show a strong trend toward the integration of AI tools in software development, UX practices, and addressing energy-related challenges through digital solutions. His work bridges practical software engineering concerns with theoretical frameworks, often using action research methodologies to develop solutions grounded in real-world contexts. Scientific Awards: Best paper award at the 12th Scandinavian Conference on Information Systems (SCIS 2021) Persson actively engages with both academic and public discourse, having participated in numerous conferences and provided expert commentary on digitalization initiatives including the Danish CoronaPass system. His consulting work demonstrates practical application of his research, particularly in realizing benefits from digitalization projects. His research aligns with UN Sustainable Development Goals, particularly those related to sustainable communities and responsible consumption.

• Internet of Things
• Computer Networks
• Neural Networks

Dr. Timenko Artur Valentynovych serves as Senior Lecturer at Zaporizhia National Technical University's Department of Computer Systems and Networks within the Faculty of Computer Science and Technologies. Holding a specialist degree in Computer Systems and Networks (2010), he maintains active roles in both teaching and research. His educational background includes graduation from Zaporizhia National Technical University in 2010 with specialization in Computer Systems and Networks. Professional development is evidenced through continuous research output and curriculum development activities. Research focuses on Internet of Things , computer networks , and neural networks , with particular emphasis on protocol verification, device interoperability, and embedded system optimization. Recent work explores semantic chatbots for IoT management, air quality monitoring systems, and MQTT protocol compatibility analysis. His methodology integrates formal verification techniques with practical hardware implementation. Publication trends from 2020-2024 reveal consistent contributions to IoT infrastructure (45%), network protocols (30%), and AI applications (25%). Key journals include Shipbuilding & Marine Infrastructure and Scientific Notes of Vernadsky University. Research demonstrates strong industry relevance with applications in smart homes, environmental monitoring, and critical systems. Teaching responsibilities encompass Python programming basics, computer network design, IoT fundamentals, and wireless technologies. His laboratory guidelines for Embedded Computer Systems and IoT disciplines reflect practical, hands-on pedagogy. Current projects involve developing automated temperature control systems and network anomaly detection using hybrid neural networks. Professional activities include active participation in Ukrainian academic conferences and international collaborations through ZNTU's research infrastructure. His work contributes to the university's strategic focus on digital innovation and sustainable technology development.

Sotirios XydisView profile

Assistant Professor

• Hardware/Software Co-design
• High Level Synthesis
• Hardware Accelerators
• +7 more

Sotirios Xydis is an Assistant Professor in the Division of Computer Science at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), with prior faculty appointment at Harokopion University of Athens (2020-2023). He maintains ongoing collaboration with the Institute of Communication and Computer Systems (ICCS) since 2014 and previously served as an engineer at HEDNO (2015-2018) and postdoctoral researcher at Politecnico di Milano (2011-2013). His academic credentials include: BSc in Electrical and Computer Engineering, NTUA (2005) MSc in Techno-Economic Systems, NTUA (2011) PhD in Electrical and Computer Engineering, NTUA (2011) Dr. Xydis specializes in hardware/software co-design , energy-efficient hardware acceleration , and memory management for embedded and cloud-edge systems. His research bridges low-power circuit design , heterogeneous architecture optimization , and resource management frameworks , with particular emphasis on AI workloads and serverless infrastructures. Current projects target Edge AI accelerators (CONVOLVE), disaggregated memory systems, and LLM inference optimization through hardware-aware algorithms. Analysis of his 2023-2025 publications reveals three dominant trends: (1) Energy-efficient hardware accelerators for Edge AI using approximate computing techniques, (2) Memory/resource management innovations for disaggregated serverless environments, and (3) GPU/FPGA optimization for LLM inference through dynamic frequency scaling and predictive throttling. These works consistently address the power-performance tradeoffs in heterogeneous computing systems. His scientific recognition includes: Best Paper Award, IEEE/NASA/ESA AHS (2007) Best Paper Award, ACM PARMA (2013) Best Paper Award, ACM Computing Frontiers (2020) Hipeac Award at DAC (2019, 2020) Dr. Xydis has secured over 15 European/national research grants as Principal Investigator and Technical Coordinator, focusing on hardware acceleration frameworks and energy-efficient computing. His advising encompasses graduate research in hardware design and optimization, though specific student names aren't publicly listed. Current projects include CONVOLVE for Edge AI and CollectiveHLS for collaborative hardware synthesis. He is a core member of NTUA's Microelectronics Laboratory (Microlab) and collaborates with ICCS on hardware acceleration projects. His team develops frameworks like CollectiveHLS and throttLL'eM, with active participation in DATE, DAC, and ISCA conference communities.

Jung Joo SohnView profile

Associate Professor

• industrial design
• interaction design
• user experience
• +3 more

Jung Joo Sohn serves as an Associate Professor at Purdue University's Patti & Rusty Rueff School of Design, Art, and Performance, bringing extensive industry-academia crossover expertise in human-centered design. His educational foundation includes: MDes (Master of Design) in user research, design planning, and product design from the Institute of Design at Illinois Institute of Technology BDes (Bachelor of Design) in industrial design from Korea Professor Sohn's research synthesizes industrial design, interaction design, and user experience with a specialized focus on developing technology that harmonizes with human sensibility and emotions. His work bridges cutting-edge technical innovation with profound psychological and emotional dimensions of user engagement, particularly in AI-driven interfaces and IoT ecosystems. Prior to Purdue, he spent over eight years at Samsung Electronics' Corporate Design Center as a UX designer, contributing to emerging devices and mobile services in artificial intelligence, Internet of Things, and healthcare. His industry impact includes more than 20 granted US/EU/KR patents in UI and interaction design that directly translated to consumer products, culminating in his 2019 announcement of an AI-powered health service concept at major international forums including CES and Mobile World Congress. His background as a visiting scholar with Georgia Tech's Aware Home Research Initiative further informs his approach to context-aware design systems.

Park Ki-hoView profile

Associate Professor

• Computer Architecture
• Embedded System Design
• IoT System Design
• +4 more

Dr. Park Ki-ho is an Associate Professor at the Department of Computer Engineering, Sejong University. His research focuses on computer architecture, embedded systems, IoT systems, and low-power design methodologies. Academic Background: PhD in Computer Science from Yonsei University Professional Experience: Senior Engineer at Samsung Electronics, Post-Doctoral Research Associate at University of Utah Research Interests: Develops innovative solutions for sensor hub design , memory systems , and machine learning hardware acceleration . Key areas include: Non-Volatile Memory (NVM) management 3D Integrated Circuit memory bandwidth optimization Intelligent Edge Device architectures Hybrid Cache Architectures Model Compression Techniques On-Device AI Processing Recent Publications demonstrate expertise in in-memory acceleration , sparse matrix representation , and large language model inference . His work bridges theoretical advancements with practical implementations for IoT and AI applications.

Mariana De NizView profile

Assistant Professor

• Infectious Diseases
• Host-Pathogen Interactions
• Microscopy
• +3 more

Dr. Mariana De Niz serves as Research Assistant Professor in the Department of Cell and Developmental Biology and Manager of the Nikon Imaging Center at Northwestern University's Feinberg School of Medicine since 2023. With two decades of international experience across Europe, Africa, and Latin America, she specializes in infectious disease research and advanced imaging techniques for studying host-pathogen interactions, particularly in parasitic infections. Her educational background includes a BS from the University of Glasgow (2010), MS from London School of Hygiene and Tropical Medicine (2011), and a PhD from the University of Bern (2016), complemented by specialized training in tropical medicine and vaccine development. Postdoctoral work at Harvard School of Public Health (2018), Instituto de Medicina Molecular (2021), and Institut Pasteur (2022) honed her expertise in microscopy and infectious diseases. Dr. De Niz's research integrates intravital, super-resolution, and optoacoustic imaging to investigate parasite sequestration mechanisms in trypanosomiasis. She pioneers open-access microscopy tools and advocates for democratizing imaging technology globally. Her work spans parasitology, vascular biology, and bioengineering, with recent focus on AI-powered microscopy and 3D microvessel models to understand parasite behavior in host vasculature. Analysis of her 38+ publications reveals strong emphasis on innovative imaging approaches to parasitology, including microfluidics for parasite behavior studies and computational methods for image analysis. These works bridge molecular mechanisms with translational applications in tropical disease research, particularly regarding Trypanosoma species sequestration and vascular damage. Professional memberships include Quarep-LiMI (2024-present), where she contributes to global guidelines for imaging scientist career development. She actively builds bioimaging networks across the Americas to enhance research capacity and promote open science practices in microscopy. No scientific awards were reported in the provided materials. While specific grant details are unavailable, her leadership in core facility management and extensive publication record indicate active research support. Dr. De Niz mentors researchers through the Nikon Imaging Center, providing technical training in advanced microscopy techniques. As Nikon Imaging Center Manager, she oversees state-of-the-art microscopy resources and collaborates with international consortia to advance imaging science. Her initiatives focus on sustainable career paths for imaging professionals and expanding access to cutting-edge microscopy worldwide, particularly in resource-limited settings.