Find Academic Supervisors

• Concurrency and Parallelism
• Real-time Systems
• Distributed Systems
• +6 more

Lukasz (Luke) Ziarek serves as Associate Dean for Academic Affairs and Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo's School of Engineering and Applied Sciences. His work bridges theoretical computer science with practical systems engineering, focusing on real-time capabilities in distributed environments and safety-critical applications. His educational foundation includes a PhD in Computer Science from Purdue University (2011) and a BS in Computer Science from the University of Chicago (2003). Ziarek's research centers on formal verification of distributed protocols , real-time systems engineering , and mobile/embedded computing . He pioneers session type theory for IoT security, develops real-time variants of Android (RTDroid) and Standard ML (RTML), and investigates UAV software reliability. His work consistently addresses the tension between theoretical guarantees and practical system constraints in concurrency, timing, and security. Recent publications (2022-2025) reveal three dominant trajectories: formal methods for rate-based session types in IoT protocols, performance analysis of visual SLAM systems for robotics, and security vulnerabilities in embedded platforms like ARM TrustZone. These threads converge on ensuring correctness and timeliness in resource-constrained distributed systems. His scientific accolades include the IEEE Region One Technological Innovation Award (2023) and NSF CAREER Award (2018), reflecting dual excellence in research and education. IEEE Region One Technological Innovation (Academic) Award, 2023 President Emeritus and Mrs. Meyerson Award for Distinguished Undergraduate Teaching and Mentoring, 2022 NSF CAREER Award, 2018 SEAS Early Career Teacher of the Year, 2016 Halstead Award for Outstanding Research in Software Engineering, 2009 Intel Fellowship, 2008 GAANN Fellowship, 2004 Ziarek directs significant research initiatives including a $900K NSF UAV infrastructure project (as PI) and a $1.7M MRI grant for connected vehicle testing. His funding portfolio spans real-time systems, compiler design, and pocket-scale data management, emphasizing collaborative, interdisciplinary approaches to software reliability. CRI:CI-New UAV Infrastructure ($900K, PI 31%) NSF CAREER: Real-time Object-Oriented Systems ($500K, PI 100%) MRI: iCAVE2 Vehicle Testing ($1.7M, co-PI 14%) III: Just-in-Time Data Structures ($499K, co-PI 50%) II-EN: MLton Compiler Research ($606K, PI 63%) He leads an open-source ecosystem including RTDroid (real-time Android), Multi-MLton (parallel SML compiler), and BlueSeal (Android security analyzer), fostering community-driven advances in systems software.

• Cloud orchestration at the level of applications
• Cloud native application development
• Edge-fog-cloud systems management
• +7 more

Professor Tamas Kiss is a distinguished academic at the University of Westminster, serving as Professor of Distributed Computing at the School of Computer Science and Engineering. He holds dual leadership roles as Director of the Research Centre for Parallel Computing and Director of Research and Knowledge Exchange at his School. Since 2020, he has been Editor in Chief of the Journal of Grid Computing published by Springer Nature. His research focuses on cloud orchestration at the application level, cloud native application development, and edge-fog-cloud systems management. He has developed significant solutions including the MiCADO cloud orchestrator for microservices-based applications, the CloudSME and CloudiFacturing platforms for manufacturing companies, and the PITHIA e-Science Centre for space physics research. These innovations have been adopted by over 100 companies, generating substantial economic impact. Professor Kiss has secured over £65 million in research funding and led more than 20 European and UK-funded projects. His publication record includes over 150 scientific papers in top journals and conferences. Current major projects include STEP-UP (UKRI EPSRC), Swarmchestrate, ARCAFF, HARPOCRATES, and PITHIA-NRF. His research outputs demonstrate a clear progression from foundational grid computing work to current focus on cloud-edge continuum orchestration and industry 4.0 applications. The most recent publications (2023-2025) emphasize decentralized application frameworks, privacy-preserving machine learning at the edge, and interoperable data analytics for digital twin manufacturing. Professor Kiss actively supervises doctoral researchers working on cutting-edge topics including swarm-based orchestration, federated learning in resource-constrained environments, and NFC implementation in industrial IoT systems. His leadership extends to directing the Centre for Parallel Computing, which focuses on cloud computing, distributed computing, high performance computing, and cloud-based simulation for manufacturing.

Daniel StrüberView profile

Associate Professor

• Model-Driven Engineering
• AI Engineering
• Software Quality Assurance
• +12 more

Daniel Strüber is an Associate Professor in Software Engineering at the joint Interaction Design and Software Engineering Division of Chalmers University of Technology and the University of Gothenburg, Sweden. He is also affiliated with the Department of Software Science at Radboud University Nijmegen, Netherlands. His research focuses on model-driven engineering, AI engineering, and variability management to enhance software quality, security, and collaborative development across domains like robotics and web systems. Education : Diplom (M.Sc. equivalent) in Computer Science from Philipps University Marburg (2011, with distinction), Ph.D. (summa cum laude) from Philipps University Marburg (2016). His research bridges empirical, formal, and engineering approaches to address developer challenges in ML-enabled systems. Key trends in his work include model-driven methods for ML deployment, variability management in robotics, and empirical studies of tool usability. He has co-edited a Journal of Systems and Software special issue on software product lines. Scientific Awards : Best Reviewer Awards (SoSyM 2025, GPCE 2024), Transformation Tool Contest Awards (2017, 2020), Best Paper Awards (VAMOS 2019, ICMT 2016), and multiple conference nominations. As a supervisor, he guides current Ph.D. students like Vladislav Indykov and Weixing Zhang, while his former advisees include Shayan Ahmadian and Samuel Idowu. Grants include a VR Open Call Grant (2022-2024) for SEMLA and a DFG Individual Fellowship (2019) for EUphORia. His teaching spans courses on Software Engineering for AI Systems and Software Product Lines , often integrated with real-world projects via GiPHouse.

Ilhan MutluView profile

Researcher

• Environmental Informatics
• Machine Learning
• Graph Databases
• +4 more

Dr. İlhan Mutlu is a postdoctoral researcher at the Helmholtz Centre for Environmental Research - UFZ in the Department of Computational Biology and Chemistry since 2023. Previously, he worked at TU Dresden (2021-2023) and IAV GmbH (2017-2021). He holds a PhD in Control and Automation Engineering (Istanbul Technical University, 2017) and focuses on data integration , graph databases , and machine learning models for toxicology prediction . His research bridges environmental data analysis with automated systems , particularly in freshwater toxicity assessment and optimal control techniques . Recent projects include ChEOS (toxicity prediction in European waters) and SafePol (pollinator protection). His technical expertise spans Neo4j , CleanGeoStreamR , and ecoKI platform development. Publications emphasize data curation for environmental monitoring, graph-based toxicity tools , and ML-driven chemical risk assessment . His work also involves automated driving systems , including model-free trajectory planning and robust control algorithms . Though no scientific awards are listed, his contributions span interdisciplinary domains combining environmental science with computational engineering .

Péter EklerView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Internet of Things
• +7 more

Péter Ekler is an Associate Professor at the Department of Automation and Applied Informatics , Budapest University of Technology and Economics (BME) , Hungary. He is affiliated with the Applied Mobile Research Group (AMORG) and the Applied Computer Science Group , focusing on cutting-edge research in AI, IoT, and mobile systems. Research Interests: Artificial Intelligence and Machine Learning Internet of Things (IoT) and Smart Cities Wireless Sensor Networks and Energy-Efficient Routing Network Coding and Mobile Peer-to-Peer Systems Blockchain and Distributed Systems Computer Vision and Sensor Data Analysis His recent work includes the development of AI-based thermal imaging systems, energy-aware IoT routing, and secure authentication mechanisms using JWT. He has published extensively on optimizing IoT performance, enhancing mobile streaming with network coding, and applying machine learning to real-world sensor data. Scientific Contributions: Published over 50 peer-reviewed articles from 2013 to 2023 Active on platforms like Google Scholar, Scopus, ResearchGate, and ResearcherID Research spans both technical systems and historical studies in science Contact & Affiliations: Email: Ekler.Peter@aut.bme.hu Location: Q.B226, Magyar tudósok krt. 2., Budapest 1117, Hungary Phone: +36 (1) 463-3702 LinkedIn: http://hu.linkedin.com/in/peterekler

Amin KaramiView profile

Associate Professor

• Artificial Intelligence and Data Science
• Big Data Technologies
• Blockchain and Cryptocurrencies
• +4 more

Dr Amin Karami is an Associate Professor in the School of Computer Science and Digital Technologies (CDT) at the University of East London, within the School of Architecture, Computing and Engineering. He serves as course leader for MSc Big Data Technologies and leads postgraduate programs, having secured £1.23 million in funding from the Office for Students to develop inclusive AI and Data Science courses for non-STEM and far-STEM graduates. His research spans Artificial Intelligence, Big Data Analytics, Blockchain, and Optimization, with focus on Industry 5.0 applications. Current work addresses federated learning heterogeneity, smart contract security, healthcare fraud detection, and ethical AI implementation. He develops cloud-based platforms for large-scale data processing and computational intelligence solutions for real-world industry challenges. Recent publications demonstrate strong trends in federated learning techniques, blockchain vulnerability mitigation, and big data applications across healthcare, finance, and social media. His work consistently bridges academic research with industry needs through partnerships with Multiverse and Cambridge Spark, emphasizing practical solutions for credit risk assessment, satellite telemetry, and personalized marketing. Scientific recognition includes: UEL Vice-Chancellor & President Impact & Innovation Award for Industry 4.0 readiness (2023) Fellow of the Higher Education Academy (FHEA) Dr Karami actively supervises UG/PG/PhD students while leading curriculum innovation through externally funded projects. His Chainlink Bootcamp initiative connects academia with industry practitioners, and he serves as external examiner and conference program chair. Significant grant achievements include developing diversity-focused STEM pathways that enhance graduate employability through industry-aligned training in AI and Data Science.

• Artificial Intelligence
• Human-Computer Interaction
• Digital Health
• +6 more

Maurice D. Mulvenna is a Researcher at the School of Computing and Mathematics, Ulster University , focusing on Artificial Intelligence, Digital Health, and Human-Computer Interaction . His work explores the application of AI in mental wellbeing, assistive technologies for dementia care, and usability testing methodologies. Research Themes : AI for Wellbeing, Ambient Assisted Living, Machine Learning in Healthcare, IoT for Elderly Care, Sentiment Analysis Recent Articles : 2025 study on AI's impact on mental health; 2024 work on employee wellbeing platforms; 2023 papers on chatbots and IoT lighting solutions for dementia His collaborations span Raymond R. Bond, Siobhan O'Neill, and Chris D. Nugent , with publications in journals like Behavior & Information Technology and conferences such as ICT4AWE and ECCE . While no explicit awards are listed, his contributions include co-editing conference proceedings and advancing ethical-by-design frameworks. Labs/Teams : Involved in projects like SenseCare (2016) for emotional wellbeing visualization and UX-Handle (2017) for usability analytics. His work bridges technical innovation with user-centered approaches in healthcare and digital platforms.

Hossain Muhammad MuctadirView profile

Researcher

• Digital Twin Technology
• Model Management
• Model-Driven Software Engineering (MDSE)
• +3 more

Hossain Muhammad Muctadir is a researcher at Eindhoven University of Technology’s Department of Software Engineering and Technology within the School of Mathematics and Computer Science. His work focuses on digital twin technology, model management, and model-driven software engineering. He holds a BSc in Information Technology from the University of Dhaka (2013), an MSc in Software Systems Engineering from RWTH Aachen University (2017), and a Professional Doctorate in Engineering (PDEng) in Software Technology from TU/e (2020). Research Interests: Digital Twin Development & Maintenance Model Management Systems Model-Driven Software Engineering Graph-Based Consistency Solutions Artifact Reuse in Software Systems Key Contributions: His work includes developing a consistency management framework for digital twin models, conducting industry interview studies on digital twin practices, and creating the LaMa web application for thematic labeling. He contributed to the NWO-funded Digital Twin project and the Internet of Food consortium involving Unilever and Wageningen University. Professional Experience: Five+ years as a software developer in Bangladesh and Germany, specializing in desktop/web applications and AR for HoloLens. Participated in projects with global partners like ASML and Philips Healthcare during his PDEng.

• Biomedical informatics
• mHealth
• Artificial intelligence in medicine
• +3 more

Alex Anh-Tuan Bui serves as Professor of Radiological Sciences and Associate Dean of Biological Chemistry at the University of California Los Angeles (UCLA) David Geffen School of Medicine. He is the Director of the Medical & Imaging Informatics (MII) group and holds the David Geffen Chair in Informatics. Dr. Bui leads UCLA's Bridge2AI Coordination Center and serves as Senior Associate Director for Informatics at UCLA's Clinical and Translational Science Institute (CTSI). PhD in Computer Science, UCLA (2000) BA in Computer Science, UC Berkeley (1995) Dr. Bui's research focuses on biomedical informatics, mHealth, and artificial intelligence in medicine. His work bridges contemporary computational approaches with biomedical observations and electronic health records (EHRs), addressing translational challenges in healthcare. He develops distributed information architectures, methodological approaches for AI/ML in healthcare, and data visualization techniques. His research spans multiple domains including predictive modeling for chronic diseases, natural language processing of clinical text, and real-time health monitoring systems. Analysis of Dr. Bui's recent publications (2021-2024) reveals a strong emphasis on applying machine learning to clinical problems across diverse medical domains. His work demonstrates expertise in developing predictive models for renal disease, cardiovascular outcomes, cancer screening, and substance use disorders. A recurring theme is the application of advanced AI techniques to electronic health records, with particular attention to data quality issues, model interoperability, and addressing health disparities. His research increasingly incorporates real-time data collection through mobile and wearable technologies. Dr. Bui has led numerous significant research initiatives including the NIH-funded Los Angeles PRISMS Center focused on mHealth informatics, and currently directs UCLA's Bridge2AI Coordination Center. He serves as Program Director for multiple NIH training grants (TL1/T15/T32) in biomedical informatics and data science, and is Director for the Medical Informatics Home Area in UCLA's Graduate Program in Biosciences. As Director of the Medical & Imaging Informatics group, Dr. Bui oversees research on the Biomedical REAl-Time Health Evaluation (BREATHE) platform and other initiatives focused on integrating AI with clinical workflows. His team develops tools for clinical decision support, patient portals, and imaging informatics that bridge the gap between computational methods and practical healthcare applications.

• Augmented Reality
• Conceptual Modeling
• Enterprise Modeling
• +3 more

Dr. Fabian Muff is a Senior Researcher at the Department of Informatics, University of Fribourg, within the Interfaculty Informatics unit. He holds a position as Oberassistent (Senior Research Assistant) specializing in Digitalization and Information Systems. His research focuses on the intersection of conceptual modeling with augmented reality (AR) and virtual reality (VR), emphasizing workflow modeling languages, AR application frameworks, and AI integration in modeling tools. He teaches courses on Requirements Engineering, Information Systems Modeling, and Project Development. Dr. Muff's work addresses challenges in hybrid modeling environments, contextual AR applications, and the limitations of large language models in conceptual modeling. His recent projects include developing the M2AR web-based modeling tool and exploring the use of ChatGPT in schema generation. He actively collaborates with academic and industry partners, publishing widely in venues like ER Conference and AAAI workshops. His contributions span technical innovations in AR modeling languages (e.g., ARWFML) and methodological advancements in combining conceptual modeling with emerging technologies. Current research explores AI-augmented visualization, context-aware AR systems, and the ethical implications of digital-physical integration in enterprise systems.

• Artificial Intelligence
• Machine Learning
• Data Science
• +7 more

Dr. Alireza Moayedikia is a Lecturer in Information Systems at the School of Business, Law and Entrepreneurship, Swinburne University of Technology. His research focuses on Artificial Intelligence, Machine Learning, and Data Science, with expertise in social network analysis, natural language processing, and back-end software development. He has over ten years of professional experience in AI and ML, emphasizing data preparation for machine learning tasks. Research Interests: Dr. Moayedikia’s work spans optimization algorithms for crowdsourcing, microtask management, and feature selection. His recent contributions include advancements in matrix factorization, dynamic payment systems for microtask platforms, and community detection in attributed networks. His methodologies often integrate swarm intelligence (e.g., bee colony optimization) and probabilistic models. Publications: His 19 publications reflect a strong focus on AI-driven solutions, including contributions to data-driven healthcare systems and green logistics. His articles address challenges in sparse data handling, worker reliability estimation, and multi-criteria decision-making frameworks. Grants: He contributed to the SCOPE 3 research contract (2020–2021), developing prototypes for tracking Green House Gas emissions in last-mile delivery systems. Labs/Teams: Collaborates within interdisciplinary teams at Swinburne, focusing on applied AI and sustainable logistics solutions.

Deepak NadigView profile

Assistant Professor

• Computer Networks
• Cloud-Native Infrastructure
• Software-Defined Networks (SDN)
• +3 more

Deepak Nadig is an Assistant Professor in the Department of Computer and Information Technology (CIT) at Purdue University and Director of the Cloud-native, Cyberinfrastructure and Networks (CYAN) Lab. He holds a Ph.D. in Computer Engineering from the University of Nebraska-Lincoln (2021). Prior to academia, he served as Director of Technology and Research at SOLUTT Corporation (India, 2009–2015), leading networking and wireless operations in 4G/LTE and multi-gigabit technologies. He is an IEEE-certified Wireless Communications Professional (2014–2019) and has received awards including the 2017 IEEE ANTS Best Paper Award and 2019 Milton E. Mohr Fellowship. Education: Ph.D. in Computer Science & Engineering, University of Nebraska-Lincoln, 2021. Master’s Thesis: Design and Deployment of DTN Architectures for Interplanetary Communication Systems, RV College of Engineering, India, 2007. Research Interests: His work focuses on computer networks, cloud-native infrastructure, software-defined networks (SDN), network virtualization, AI/ML-driven networking solutions, and cybersecurity. He leads the CYAN Lab, advancing cloud-native and edge computing architectures for data-intensive applications. Grants & Awards: NSF-funded research, Purdue Bravo Award (2021), and multiple dissertation awards. His contributions include optimizing network architectures for GridFTP transfers (SNAG framework) and scalable edge computing for agriculture (ERGO). Labs & Leadership: Director of the CYAN Lab, managing projects on network observability, SDN security, and cloud-native systems. Active in program committees for IEEE conferences and journals like IEEE/ACM Transactions on Networking and IEEE INFOCOM.

• Human-Computer Interaction
• Artificial Intelligence
• Software Engineering
• +7 more

Nadeem Faisal is an Assistant Professor at National Textile University, Pakistan , a Postdoctoral Researcher at the IVU Laboratory (Department of Computer Science, University of Bari, Italy), and a Senior Researcher with the Human Communication and Interaction Group (University of Oviedo, Spain). His academic journey spans 15+ years of teaching and research in Human-Computer Interaction (HCI) , Artificial Intelligence , and Software Engineering . Current Roles : Assistant Professor (NTU), Postdoctoral Researcher (IVU Lab, Bari), Senior Researcher (HCI-RG, Oviedo) Key Research Areas : Software requirements, AI, UX design, smart systems, human-centered technology Education : B.S. Information Technology (2005, AIOU, Pakistan) M.S. Computer Science (2009, Blekinge Institute of Technology, Sweden) Ph.D. Computer Engineering (2017, University of Oviedo, Spain) Research Trends from his 15 most recent publications (2023–2025) show sustained focus on Human-Computer Interaction (mobile UX, educational apps), AI/ML applications (medical imaging, crop disease detection, sentiment analysis), and Smart Systems (IoT, security surveillance). His work bridges technical innovation with real-world applications in healthcare, education, and sustainability. Scientific Collaborations : EU-funded research contributions International partnerships with institutions in Spain, Sweden, and Italy Advising : Supervised 40+ postgraduate students across AI, HCI, and software engineering. Current research involves mentoring teams in deep learning for medical imaging at IVU Lab and developing augmented reality tools for special education. Labs & Teams : IVU Laboratory (University of Bari, Italy) Human Communication and Interaction Group (University of Oviedo, Spain) Collaborative projects with institutions in Sweden, Spain, and Pakistan

Louis BusbyView profile

Senior Lecturer

• Machine Learning for Audio Generation
• Social Robotics
• Musical Robotics
• +2 more

Louis Busby is Senior Lecturer and Course Leader for the MSc Data Science and AI at UAL's Creative Computing Institute. His research explores machine learning applications in audio generation and musical robotics. He developed the MIMIC creative ML platform used by 70k+ students and secured multiple Google grants for AI projects. His curriculum development focuses on NLP, machine learning, and creative computing applications. Previously at Goldsmiths, he researched motion sensor feature engineering for interactive ML systems. Commercial experience includes senior developer roles at AI firms. His robotic drummer Mortimer appeared on BBC's Christmas Lectures. Grants include Alan Turing Institute funding for open-source AI music tools. He continues performing music using neural networks and maintains several open-source libraries.

Alice TonioloView profile

Lecturer

• Artificial Intelligence
• Argumentation Theory
• Human-AI Interaction
• +7 more

Dr. Alice Toniolo is a Lecturer in Computer Science at the University of St Andrews' School of Computer Science. Her research focuses on artificial intelligence, argumentation theory, human-AI interaction, and multi-agent systems. She leads projects exploring deliberation dialogues, planning frameworks, and collaborative intelligence analysis tools like CISpaces.org. Her work bridges formal models with real-world applications in education technology, healthcare, and spatial cognition. Research interests include argumentation schemes, provenance tracking, and normative systems in AI. She supervises PhD students in topics like diverse planning and AR-based learning. Toniolo has published over 40 peer-reviewed works, with recent contributions in CHI, IEEE Transactions, and AI journals. Her projects are funded by grants from the Scottish Funding Council and the Carnegie Trust. She collaborates internationally on tools for collaborative analysis, AR learning environments, and explainable AI systems. Notable contributions include the VocabulARy AR vocabulary tool, Deb8 dialogue analysis software, and the AIF-EL ontology for argument interchange. Current work emphasizes mitigating algorithmic loafing in AI teams and adaptive guidance in AR educational systems. She actively participates in initiatives like the UN Sustainable Development Goals through AI-driven solutions. Key Projects : Argumentation-Based Training (2020), Don't Make a Wave (2017), CISpaces Toolkit Tools : CISpaces.org, Deb8, Write Reason, AIF-EL ontology Grants : Scottish Funding Council, Carnegie Trust Labs/Teams: Core contributor to the CISpaces collaboration platform and the School's AI research group. Engages in interdisciplinary work across computer science, philosophy, and education.