Find Academic Supervisors

Kirill DjebkoView profile

Researcher

• Artificial Intelligence
• Machine Learning
• Optimization Algorithms
• +4 more

Kirill Djebko is a researcher at the Chair of Computer Science VI - Artificial Intelligence and Knowledge Systems within the Institute of Computer Science, Faculty of Mathematics and Computer Science at the University of Würzburg . His work spans AI-based optimization systems , autonomous spacecraft operations , and deep reinforcement learning applications. Doctorate completed in 2020 Active in research since 2015 Key projects: KINERGY (heating system optimization), VeriKI (AI verification for space), LeLaR (AI attitude control for nanosatellites) Research focuses on metaheuristics , genetic algorithms , regression algorithms , and deep reinforcement learning for practical applications. His work integrates digital twin modeling , decision support systems , and AI robustness in industrial and space contexts. Recent publications (2024-2016) analyze heating system optimization , spacecraft fault detection , and autonomous nanosatellite operations . These studies emphasize sim-to-real-world transfer , data-driven calibration , and AI quality assurance in complex environments. Current affiliations include the Center for Artificial Intelligence and Data Science (CAIDAS) . Contact details: Email - kirill.djebko@uni-wuerzburg.de | Phone +49 931 31-86405 | Room 03.010, Emil-Fischer-Straße 50, Würzburg.

• Semantic Web
• Knowledge Representation
• Artificial Intelligence
• +6 more

Deborah L. McGuinness is the Tetherless World Senior Constellation Chair and Professor of Computer, Cognitive, and Web Sciences at Rensselaer Polytechnic Institute (RPI). She serves as founding director of the Web Science Research Center, focusing on next-generation ontology-enabled research infrastructure for interdisciplinary applications. Leaders in Semantic Web and AI research Bridging AI with eScience and healthcare Developer of semantic frameworks for data-intensive resource efforts Her research spans artificial intelligence, knowledge representation, clinical decision support systems, and ontology engineering. She investigates how semantic technologies can enhance AI explainability, data interoperability, and interdisciplinary science. Her recent publications highlight trends in AI explainability frameworks Knowledge graph construction Clinical decision support Commonsense reasoning benchmarks Health informatics Data harmonization Scientific awards include Fellow of the American Association for the Advancement of Science (AAAS) Robert Engelmore Award from the Association for the Advancement of Artificial Intelligence (AAAI) She leads large data-intensive research efforts and has contributed to projects involving blockchain integration with semantic web standards, FAIR data principles, and incentivized research data sharing mechanisms.

Samarjit ChakrabortyView profile

Professor

• Distributed Embedded Systems
• Hardware/Software Co-design
• Embedded Control Systems
• +9 more

Samarjit Chakraborty is the William R. Kenan, Jr. Distinguished Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. He previously held the Chair of Real-Time Computer Systems at the Technical University of Munich (2008–2019) and was an assistant professor at the National University of Singapore (2003–2008). His research spans real-time embedded systems, cyber-physical systems (CPS), and automotive security. Research Interests include distributed embedded systems, hardware/software co-design, low-power systems, energy storage, electromobility, and sensor network-based information processing. His work addresses challenges in scheduling algorithms for autonomous vehicles, timing predictability in automotive networks, and safety-critical controller implementations. Recent Publications highlight advancements in Timing analysis for automotive networks Energy modeling of Bluetooth Low Energy Autonomous vehicle perception computing Security in automotive systems Flexible manufacturing with process dynamics Scientific Awards include the ETH Medal, European DAAD Outstanding Doctoral Dissertation Award, multiple best paper awards at conferences (ISLPED, ICCD, RTCSA, etc.), the 2023 Humboldt Professorship, and IEEE Fellowship. Advising active PhD students: Clara Hobbs, Shengjie Xu, Sharmin Aktar, and postdoc Enrico Fraccaroli. His research is supported by NSF grants and industry partnerships with General Motors, Intel, Google, BMW, Audi, Siemens, and Bosch.

Robert ClementsView profile

Assistant Professor

• Data Science Education
• AI and Data Ethics
• Machine Learning
• +2 more

Robert Clements is an Assistant Professor in the Master of Science in Data Science (MSDS) program at the University of San Francisco (USF) and serves as Director of the Center for AI and Data Ethics. After nearly ten years in industry as a data scientist and senior director of data science across Bay-Area companies including Optum, Walmart Labs, UnitedHealthcare, GE Digital, and Verisk Analytics, he returned to academia to focus on education and ethical issues surrounding AI and data. Education PhD in Statistics, University of California, Los Angeles, 2011 MS in Statistics, University of California, Los Angeles, 2009 BA in Mathematics, Humboldt State University, 2006 Research Interests Dr. Clements focuses on data science education , exploring innovative pedagogies that equip students with practical and ethical data skills. He studies the societal impacts of AI and datafication , seeking frameworks to ensure responsible deployment of machine-learning systems. Additional interests include MLOps (the engineering practices that support reliable machine-learning workflows) and applied statistics across diverse domains. His peer-reviewed work to date concentrates on statistical seismology, where he developed advanced residual-analysis and model-evaluation techniques for earthquake-forecast models. These contributions provide rigorous methods for assessing space-time point processes and improve the reliability of seismic hazard assessments. Academic & Professional Service As Director of the Center for AI and Data Ethics, Dr. Clements leads initiatives that create open educational resources, case studies, and student practicum projects centered on ethical AI. He co-hosts the USF Data Science Podcast alongside faculty colleague Cody Carroll, offering guidance to prospective and current MSDS students on program insights, learning strategies, and career development.

• Cyber-physical systems
• Green and sustainable computing
• Mobile and pervasive computing
• +7 more

Sandeep Gupta is a Professor and Director of the School of Computing and Augmented Intelligence at Arizona State University's Ira A. Fulton Schools of Engineering. He also serves as a Senior Global Futures Scientist. His work bridges computer science, engineering, and healthcare applications with a focus on creating reliable cyber-physical systems that interact safely with humans. Education: Ph.D. from The Ohio State University (1995) Research Interests: Professor Gupta's research spans cyber-physical systems, green and sustainable computing, mobile and pervasive computing, and parallel and distributed computing. His work increasingly focuses on human-in-the-loop systems where AI and humans collaborate safely, particularly in healthcare contexts. Recent research integrates large language models with cyber-physical systems to enhance safety and operational effectiveness in critical applications like medical monitoring and industrial automation. Research Trends: Analysis of Professor Gupta's recent publications reveals a strong focus on operational safety in human-AI collaborative systems, particularly in healthcare applications. His work combines physics-guided models with machine learning to detect "unknown-unknowns" in safety-critical systems, develops LLM-based approaches for medical image classification, and creates frameworks for ethical human-AI collaboration. The research increasingly addresses real-world challenges in diabetes management, epilepsy diagnosis, and industrial automation. Professional Service: IEEE Communication Letters Editorial Board, Area Editor (2008-Present) IEEE Journal on Special Areas in Communications - Issue on Body Area Network, Co-editor (2006-Present) Elsevier COMNET - Computer Network Journal, Reviewer (2008-Present) Technical Advisory Committee Chair for Networks (2005-Present) Advising and Grants: Professor Gupta has secured numerous research grants from NSF, NIH, Intel, Raytheon, and other organizations, totaling millions of dollars. His research portfolio includes projects on smart stadiums, mobile ECG sensing, power-aware scheduling, medical device verification, and sustainable data center management. He actively advises PhD and Master's students through thesis courses and research supervision, focusing on cyber-physical systems and healthcare applications. Labs and Research Groups: Professor Gupta leads research in cyber-physical systems with applications in healthcare, sustainable computing, and mobile networks. His work involves interdisciplinary collaboration across engineering, computer science, and medical domains, particularly through ASU's Global Futures initiatives.

• Biometrics
• Machine Learning
• Deep Learning
• +5 more

Raghavendra Ramachandra is a Professor at the Department of Information Security and Communication Technology (IIK) , within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU) in Gjøvik. His research focuses on biometric systems, particularly in face, fingerprint, and finger vein recognition, with emphasis on presentation attack detection, morphing attack detection, and deep learning applications. Current research projects include: SALT (2022-2026) : Developing privacy-preserving facial biometric authentication systems. OffPAD (2022-2025) : Creating cryptographic tools and presentation attack detection for fingerprint biometrics. SWAN (2015-2020) : Developing biometric countermeasures against presentation attacks. His recent publications demonstrate technical expertise in: Face morphing attack detection using vision transformers and point cloud networks Image fusion techniques for multispectral biometrics GAN-based synthetic data generation for security evaluation Explainable AI approaches for biometric verification Professor Ramachandra also supervises PhD and Master’s students, and has extensive experience in leading national and EU research initiatives.

Akbar Siami NaminView profile

Professor

• Cybersecurity
• Software Engineering
• Program Analysis
• +5 more

Dr. Akbar Siami Namin is a Professor in the Department of Computer Science at Texas Tech University's Whitacre College of Engineering . He leads the AdVanced Empirical Software Testing & Analysis (AVESTA) research group and contributes to cybersecurity, software engineering, and program analysis. Ph.D., Computer Science, University of Western Ontario (2008) M.S., Lakehead University/University of Western Ontario (2004) Research Interests : Dr. Namin specializes in Natural Language Processing , Software and Cyber Security , Machine Learning , Time Series Analysis , Modeling Human Factors , and Program Analysis . His work bridges security testing , mutation analysis , and empirical software engineering . Publications : His research spans sonification of security threats , keystroke dynamics , statistical fault localization , and mutation testing , with recent works published at CHI , ICMLA , and CyberWorlds (best paper award 2015). Scientific Awards : Best Paper Award at CyberWorlds 2015; 'Most Influential Professor' recognition by Computer Science undergraduates (2012). Students & Grants : Supervised numerous Ph.D. and Master's students, including Alaa Darabseh and Xiaozhen Xue. Secured over $1M in NSF grants for projects like CyberCorps Capacity Building , Security Sonification , and Cybersecurity Education for Community Colleges .

Michael SirivianosView profile

Associate Professor

• Cybersecurity
• Social Media Analysis
• Disinformation Detection
• +5 more

Michael Sirivianos is an Associate Professor at the Cyprus University of Technology (CUT), where he serves as Dean of the School of Engineering and Technology. He holds a PhD in Computer Science from Duke University (2010) and leads research in cybersecurity, disinformation detection, and social media analysis. He coordinates multiple EU-funded projects including ReCRED (Horizon 2020) and ENCASE (Marie Curie RISE), securing over €3M in research funding. Research Focus His work spans: Cybersafety : Detection of cyberbullying, hate speech, and inappropriate content targeting children Trust Systems : Device-centric authentication and blockchain applications Disinformation Analysis : Graph-based detection of fake news and state-sponsored manipulation Scalable Systems : Distributed databases and network infrastructure Achievements & Recognition Best Paper Award (2019) for work on state-sponsored disinformation Distinguished Paper (2018) for fringe web community analysis Spotlight Session recognition (2020) for child protection research Featured in NYT, Washington Post, and Wired for YouTube content analysis Leadership Co-directs the Network Systems Research Lab, serves on the Board of CYENS Centre of Excellence, and coordinates the Fact-check Cyprus Centre against Disinformation.

Timo SeppäläView profile

Lecturer

• Supply Chain Management
• Digital Platforms
• Artificial Intelligence
• +4 more

Timo Seppälä is a University Lecturer in Digital Operations at Aalto University's School of Science, Department of Industrial Engineering and Management. His research focuses on global value chains, supply chain management, and digital technology implementations in technology- and service-based businesses. He explores platformization of supply chains, collaborative innovation management for complex digital ecosystems, and the implications of artificial intelligence platforms across industries. Global Value Chains Digital Platforms & Ecosystems Artificial Intelligence Governance Blockchain Applications in Industry Recent publications highlight trends in AI diffusion monitoring, blockchain-based systems for industrial applications, and sustainability challenges in digital economies. His work spans empirical analysis of corporate digitalization, platform governance, and multi-actor value creation. No scientific awards are currently documented.

Ahmad LotfiView profile

Professor

• Computational Intelligence
• Ambient Intelligence
• Robotics
• +7 more

Ahmad Lotfi is a Professor of Computational Intelligence and Head of Department of Computer Science at Nottingham Trent University , with a Visiting Professor role at Tokyo Metropolitan University . He leads the Computational Intelligence and Applications (CIA) research group and has supervised over 30 PhD students to completion. PhD in Learning Fuzzy Systems (University of Queensland, 1995) MTech in Control Systems (Indian Institute of Technology, India) BSc in Control Systems (Isfahan University of Technology, Iran) His research spans computational intelligence , ambient intelligence , robotics , and machine learning , with applications in dementia monitoring , smart environments , and healthcare technology . Recent work focuses on using thermal sensor arrays for privacy-preserving human activity analysis. He has secured funding from Innovate UK , EPSRC , The Royal Society , and Horizon 2020 , with projects like iCarer (assistive living), SmartBerry (agricultural AI), and BigSpark (financial data augmentation). His 15 most recent articles demonstrate expertise in Wi-Fi-based activity recognition , EEG fall detection , and thermal sensor fusion . Senior Member IEEE Member of British Computer Society (MBCS) Editorial roles in Soft Computing and Journal of Ambient Intelligence and Smart Environments He has served as Program Chair for conferences like PETRA and ICCRT , and as Keynote Speaker at PETRA 2023 . His 28+ years of academic leadership include organizing UKCI and UKRAS conferences.

Yupeng ZhangView profile

Assistant Professor

• Cybersecurity
• Applied Cryptography
• Zero-Knowledge Proofs
• +4 more

Yupeng Zhang is an Assistant Professor at the University of Illinois Urbana-Champaign in the Department of Electrical and Computer Engineering, with an affiliate appointment in Computer Science. His research focuses on cybersecurity and applied cryptography , particularly zero-knowledge proofs , secure multiparty computations , and their applications in blockchain and machine learning. Education: Ph.D., Electrical and Computer Engineering, University of Maryland (2018) M.Phil., Information Engineering, Chinese University of Hong Kong (2013) Bachelor of Engineering, Information Engineering, Chinese University of Hong Kong (2011) Research Highlights: Developed scalable zero-knowledge proof systems for blockchain and machine learning Created verifiable computation frameworks for SQL and RAM Advancing privacy-preserving ML and cross-chain blockchain bridges Grants: NSF CAREER award Air Force Research Lab DARPA Google Research Scholar Award Facebook Research Award Latticex Foundation Teaching: CS 461/ECE 422: Computer Security I CS 591 SP: Security and Privacy ECE 407/CS 407: Cryptography ECE 598 YPZ: Advanced Topics in Applied Cryptography Co-taught MOOC on Zero-Knowledge Proofs (Spring 2023) Professional Service: Program Vice Co-Chair, USENIX Security 2024 Program Committee, Crypto 2025, S&P 2025 Reviewer for major journals and conferences

Rianne de HeideView profile

Assistant Professor

• Machine Learning
• Statistics
• Hypothesis Testing
• +7 more

Rianne de Heide is an Assistant Professor in the Statistics group (STAT) within the Department of Applied Mathematics at the University of Twente's Faculty of Electrical Engineering, Mathematics and Computer Science. She maintains collaborative arrangements with LUXs Data Science in Leiden, CWI, and VU Mathematics in Amsterdam as a guest researcher while working partly remotely during her family's relocation. Her academic journey includes a previous position as Assistant Professor at Vrije Universiteit Amsterdam. PhD Dissertation: 'Bayesian Learning: Challenges, Limitations and Pragmatics' (2020) MSc Thesis: 'The Safe-Bayesian Lasso' (2016) De Heide's research spans multiple interconnected domains within statistics and machine learning, with particular emphasis on developing mathematically rigorous frameworks that remain accessible to diverse audiences. Her work bridges theoretical foundations with practical applications, focusing on hypothesis testing with e-values, Bayesian learning methodologies, and best-arm identification problems in multi-armed bandit settings. She demonstrates exceptional interdisciplinary range, connecting statistical theory with philosophical inquiry and even theological discussions as evidenced by her publications on biblical authorship verification and mathematical beauty. Analysis of her publication trajectory reveals a clear evolution toward developing anytime-valid statistical methods, particularly through e-values and e-processes for multiple testing scenarios. Her recent work shows increasing focus on foundational questions in statistical inference while maintaining strong connections to practical machine learning applications. The 2024 'Safe Testing' paper in the Journal of the Royal Statistical Society represents a significant contribution that generated a formal discussion meeting. VENI project 'E-values for Multiple Testing' NWO M2 grant of €742,708 with Jelle Goeman (funding 2 PhD students and a scientific programmer) 2025 Bernoulli Society New Researcher Award De Heide actively supervises research through her VENI project and the NWO M2 grant, while also contributing to broader academic service through the 'Kindness and Excellence in Academia' initiative she co-founded. This initiative addresses critical cultural issues in academic environments through opinion pieces, resources, and community building around compassionate academic practices. She has organized specialized events like the E-Day meet-up for e-value researchers at CWI in Amsterdam, demonstrating leadership in her niche research community. Her research activities are centered around the Statistics group at the University of Twente, with significant external collaborations through the E-mailing list for e-value researchers and partnerships with institutions including CWI, VU Amsterdam, and Leiden's LUXs Data Science. The interdisciplinary nature of her work creates connections across mathematics, computer science, philosophy, and even religious studies.

Aws AlbarghouthiView profile

Researcher

• Program Synthesis
• Formal Verification
• Quantum Computing
• +5 more

Aws Albarghouthi is affiliated with the University of Wisconsin-Madison, USA. He is an active researcher with significant contributions to program synthesis, formal verification, and machine learning. Key roles: Author, Session Chair, Committee Member in conferences like PLDI, POPL, VMCAI, SPLASH, and ICFP. Research spans quantum computing, differential privacy, and static analysis. Research Trends include: Quantum Circuit Compilation and Optimization Probabilistic Verification of Fairness and Privacy Synthesis of Datalog and MapReduce Programs Neural-Augmented Static Analysis Bias Detection in Data Security Robustness in Machine Learning

Márk JelasityView profile

Professor

• Distributed Systems
• Peer-to-Peer Computing
• Gossip Protocols
• +7 more

Márk Jelasity is a Full Professor in the Department of Algorithms and AI at the University of Szeged, Hungary, where he has been working since 2016. Previously, he served as a research advisor (equivalent to full professor) and senior research scientist at the Research Group on Artificial Intelligence (RGAI) of the Hungarian Academy of Sciences. His career includes numerous international research positions at institutions in Sweden, Norway, France, Italy, and the Netherlands. Professor Jelasity's research spans distributed systems, peer-to-peer computing, gossip protocols, and decentralized machine learning. His work bridges theoretical foundations with practical applications, particularly in the areas of self-organizing systems and privacy-preserving computation. His research has significant implications for smart grid technologies, secure distributed systems, and robust machine learning. His publication record shows a clear evolution from foundational work in gossip protocols and peer-to-peer systems toward cutting-edge research in decentralized machine learning, adversarial robustness, and privacy-preserving AI. Recent publications demonstrate his leadership in comparing gossip learning with federated learning approaches and exploring novel techniques for enhancing robustness in neural networks. Bolyai Plaquette (2015) 10 years best paper award at ACM/IFIP/USENIX Middleware Conference (2014) Best paper award at IEEE International Conference on Peer-to-Peer Computing (2014) Best paper award at IEEE International Conference on Self-Adaptive and Self-Organizing Systems (2013) Scientific Award of the Faculty of Science and Informatics, University of Szeged (2013) Fulbright Scholarship to visit Cornell University (2013) Multiple Bolyai Scholarships (2007-2014) Professor Jelasity has been actively involved in the academic community as an organizer of major conferences including DAIS'16 (TPC co-chair), SASO 2010 (General Co-Chair), and SASO 2007 (TPC co-chair). His leadership in the field is evidenced by his extensive publication record in top venues and his role in editing special issues and conference proceedings.

Yves Le TraonView profile

Professor

• Machine learning systems
• Software testing
• Software security
• +8 more

Dr. Yves Le Traon is a Full Professor of Computer Science at the University of Luxembourg, where he serves as Vice-Director of the Interdisciplinary Centre for Security, Reliability and Trust (SnT). He leads the 25-member SerVal research group (SEcurity, Reasoning and VALidation), focusing on software testing, security, and data-intensive systems. Previously, he chaired the CSC Research Unit (2013-2016) and pioneered model-driven engineering at INRIA. PhD and engineering degree in Computer Science from Institut National Polytechnique, Grenoble (1997) Former Associate Professor at University of Rennes (1998-2004) His research spans three main areas: innovative software testing and repair , Android security through static analysis and machine learning , and robust machine learning system design . Collaborations include industry leaders like PayPal, CREOS, and Cebi in fintech, smartgrid, and industry 4.0 domains. Awarded IEEE Fellow (2022) and Facebook Testing & Verification Research Award (2019) , he chairs editorial boards for STVR, SoSym, and IEEE Transactions on Reliability. His team has produced 20+ PhD graduates including Li Li (Monash University), Donia El Kateb (European Investment Bank), and Alexandre Bartel (SnT Research Associate). Commercial impact includes co-founding Datathings for runtime AI decision systems.