Find Academic Supervisors

• Complex Systems
• Computational Modeling
• Data Science
• +6 more

Bryan Daniels is an Assistant Professor at Arizona State University's School of Complex Adaptive Systems . He is affiliated with the ASU-SFI Center for Biosocial Complex Systems , Biosocial Complexity Initiative , and holds the title of Senior Global Futures Scientist . Educational Background: Ph.D. in Theoretical Physics from Cornell University. Research Interests: Daniels focuses on predictive modeling of collective behavior in biological systems, exploring how functional aggregates emerge from heterogeneous networks. His work spans computational biology, network science, and dynamical systems. Key Article Trends: Recent publications emphasize collective behavior in biological systems, network dynamics, criticality, and control strategies. Topics range from neural networks and Boolean models to animal group behavior and conflict analysis. Teaching: He teaches courses like Fundamentals of CAS Science and Applied Complex Adaptive Systems at the graduate level. Labs & Affiliations: Leads the Collective Logic Lab and contributes to interdisciplinary research through multiple ASU-SFI collaborations.

Wessel ReijersView profile

Research Fellow

• Technology Ethics
• Emerging Technologies
• Social Credit Systems
• +5 more

Wessel Reijers is a Postdoctoral Researcher at the Department of Media Studies, Paderborn University, Germany, with visiting scholarships at the Technion and the Robert Schuman Centre, European University Institute. Previously, he was a Max Weber Fellow at the European University Institute, a Research Associate in the ERC project "BlockchainGov" led by Dr. Primavera de Filippi, and a postdoctoral researcher at the University of Vienna. Reijers received his PhD in technology ethics from Dublin City University. His academic journey has spanned multiple European institutions, focusing consistently on the ethical implications of emerging technologies for society and citizenship. His research primarily explores how emerging technologies impact citizenship, with particular attention to social credit systems and their effects on civic virtue. He also investigates distributed governance models, analyzing both their potential to enhance democratic processes and their inherent risks. His work bridges philosophy, political theory, and technology studies, offering critical perspectives on how technological developments reshape societal structures. Recent publications demonstrate a growing focus on AI ethics, interpretability, and what he terms "Positive Luddism"—a critical yet constructive approach to technological development that emphasizes human flourishing while acknowledging technology's dangers. Reijers is the author of "Narrative and Technology Ethics" and co-editor of "Interpreting Technology." His upcoming book "Introduction to the Ethics of Emerging Technologies" (2025) further establishes him as a leading voice in technology ethics. His work has gained recognition in both academic and public spheres, with media appearances including a Deutschlandfunk interview on "Positive Luddism" (2024). Beyond academia, Reijers is a creative individual who writes fiction, composes and produces music (available on Soundcloud), and creates paintings. He is part of an international music collaboration called "Conditio Humana," demonstrating his commitment to interdisciplinary engagement between technology, ethics, and the arts.

Yuhong NanView profile

Associate Professor

• Software Security
• Privacy Leakage Analysis
• IoT Security
• +3 more

Yuhong Nan is an Associate Professor in the School of Software Engineering at Sun Yat-sen University, China, specializing in software security and privacy leakage analysis for emerging platforms including IoT, mobile systems, and blockchain. Previously a Post-doctoral Research Associate at Purdue University under Prof. Dongyan Xu, she builds practical security tools to detect and mitigate vulnerabilities in real-world systems. Dr. Nan earned her PhD from Fudan University in 2018 supervised by Prof. Min Yang. Her academic journey spans rigorous research in security engineering with emphasis on empirical validation and tool development for complex platform ecosystems. Her research program focuses on uncovering systemic security flaws through innovative analysis techniques. Key contributions include vulnerability detection in smart contracts (e.g., state dependencies, reentrancy), privacy leakage analysis in mobile/IoT ecosystems, and countermeasures against deceptive UI patterns. She employs hybrid approaches combining static/dynamic analysis, machine learning, and large-scale empirical studies to develop deployable security solutions. Analysis of her 15 most recent publications (2023-2025) reveals dominant themes in blockchain security (60%), particularly smart contract/DApp vulnerabilities, with significant work in mobile privacy (30%) and cross-platform threats (10%). Her methodology consistently leverages fine-grained static analysis, semantic enrichment, and feedback-driven fuzzing, yielding tools like SmartAxe and Midas that have influenced industry practices. Dr. Nan actively mentors graduate researchers with 17 advisees including Tencent-employed graduates, and serves as a trusted reviewer for premier journals (IEEE TDSC, TMC, TOPS) and conference committees (ASIACCS, ICICS). Her leadership in security communities bridges academic research with practical defense mechanisms. At Sun Yat-sen University, she directs a high-output research group that collaborates with industry partners to address evolving threats in decentralized systems, maintaining her position among top publishing authors in USENIX Security, CCS, and NDSS venues through rigorous technical innovation.

Jingling XueView profile

Professor

• Programming Languages
• Compilers
• Program Analysis
• +5 more

Jingling Xue is a Scientia Professor at the School of Computer Science and Engineering at the University of New South Wales (UNSW) in Sydney, Australia. As an IEEE Fellow of the Computer Society, he leads the Programming Languages and Compilers research group, focusing on practical applications of compiler optimization and program analysis techniques. His work bridges theoretical foundations with real-world software systems, particularly in developing open-source tools for large-scale program analysis. Professor Xue received his B.Eng and M.Eng degrees from Tsinghua University in 1984 and 1987, respectively, followed by a PhD from the University of Edinburgh in 1992. His academic journey has established him as a leading figure in programming languages and compiler technology. Xue's research spans programming languages, compiler technology, and program analysis with emphasis on practical relevance. His current projects include compiler techniques for improving parallelism and locality, pointer/alias analysis for million-line-scale programs, and static/dynamic analysis for detecting bugs and security vulnerabilities in real-world applications like web browsers and Android apps. His group actively develops open-source tools to support scientific replicability and reproducibility in these areas. His recent publications demonstrate a strong focus on applying program analysis techniques to modern challenges including AI compilers, homomorphic encryption, security vulnerability detection, and graph processing systems. The work shows evolution from traditional compiler optimization to addressing emerging domains like privacy-preserving computation and deep learning systems while maintaining rigorous theoretical foundations. Scientific Awards: Best Paper Award at CGO'13 Best Paper Award at CGO'16 Distinguished Paper Award at ECOOP'16 Distinguished Paper Award at ICSE'18 Distinguished Paper Award at ISSTA'19 Distinguished Paper Award at ASE'19 Distinguished Artifact Award at ISSTA'23 Best Artifact Award at FSE'23 Distinguished Paper Award at ASE'23 Test-of-Time Award at CGO'21 Professor Xue has successfully supervised 30 PhD students to completion, many of whom now work as professors or researchers in academia and industry. He has served as Program Chair for major conferences including LCTES'13, CC'18, CGO'20, and General Chair for LCTES'20. His group currently focuses on memory safety in Rust, smart contract analysis, AI compilers, compilation for privacy-preserving computation, and adversarial attacks in deep learning. The Programming Languages and Compilers group maintains strong connections with industry partners, translating theoretical advances into practical tools for real-world software development challenges. Their work on pointer analysis, memory safety, and compiler optimizations continues to influence both academic research and industrial practice.

Stijn ViaeneView profile

Professor

• Digital Transformation
• Business Process Management
• IT Management
• +3 more

Stijn Viaene is a Full Professor at KU Leuven and Partner at Vlerick Business School, specializing in digital transformation, IT management, and business process innovation. He holds a Doctorate in Information Systems Management from KU Leuven and serves as Programme Director of Take The Lead. His research focuses on leveraging technology (big data, AI, blockchain) for enterprise digitalization, with a strong emphasis on leadership, agility, and business-IT alignment. He is the author of Digital Transformation Know How: Connecting digital transformation, agility and leadership and teaches across MBA, Executive Development, and Digital Leadership programs. Recent work explores AI-driven leadership, blockchain platforms for sustainability, and intra-organizational labor platforms. He also serves as Jury President for the Data News Awards and Board Member at Herita vzw. Education: Doctor in Information Systems Management (KU Leuven). Research interests include digital innovation ecosystems, process management, and governance frameworks for digital value creation. His articles address topics such as ambidextrous ERP systems, paradox management in transformations, and open innovation in public administration. Advising & Grants: Involved in multiple industry-public sector collaborations. Notable projects include blockchain-based water trade platforms and frameworks for sustainable digital ecosystems. His work bridges academic research with practical business applications through case-based teaching and action design research methodologies. Labs/Teams: Active in Vlerick’s Digital Transformation and IT Management research groups, contributing to initiatives like the Digital Leadership programme and strategic consulting for global organizations.

Qianqian TongView profile

Assistant Professor

• Stochastic Optimization
• Sparse Learning
• Federated Learning
• +4 more

Qianqian Tong is an Assistant Professor in the Computer Science department at the University of North Carolina at Greensboro. Her research focuses on stochastic optimizations, sparse learning, federated learning, and privacy-preserving machine learning algorithms. She has developed novel methods for efficient optimization in deep learning and federated learning frameworks, including communication-efficient distributed algorithms and decentralized systems. Education: Ph.D. Computer Science and Engineering, University of Connecticut M.S. Computational Mathematics, Zhengzhou University B.S. Mathematics, Zhengzhou University Research interests include designing algorithms for sparse learning, federated learning with privacy guarantees, and applying deep graph learning to drug discovery. Recent projects involve tensor-based models for multidimensional data analysis and improving convergence in ADAM optimization. Her publications span optimization theory, federated learning systems, and molecular modeling applications. Though no awards are listed, her work demonstrates significant contributions to efficient machine learning methodologies. Teaching includes advanced courses on data science and computer science foundations. No lab affiliations or grant details are explicitly mentioned in the provided text.

Dongmei ZhaoView profile

Professor

• Wireless Networking
• Network Resource Management
• Mobile Edge Computing
• +4 more

Dr. Dongmei Zhao is a Professor in the Department of Electrical & Computer Engineering at McMaster University, part of the Faculty of Engineering. She specializes in wireless networking, network resource management, mobile edge computing, mobile computation offloading, and digital twins. Her research clusters focus on Digital & Smart Systems. Dr. Zhao holds a Ph.D. from the University of Waterloo. She teaches courses such as COMPENG 4DK4 (Computer Communication Networks), COMPENG 4DN4 (Advanced Internet Communications), and graduate-level courses like ECE 729 (Resource Management in Wireless Networks). Her research interests span cutting-edge topics including UAV-enabled edge computing, digital twin migration, vehicular networks, and reinforcement learning applications in resource allocation. She actively contributes to advancing 6G networks, security redundancy in autonomous systems, and decentralized manufacturing platforms. Dr. Zhao's recent publications emphasize optimization techniques for dynamic networks, platooning systems, and multi-agent learning frameworks. She has been recognized for her work in vehicular edge computing and digital twin integration, though explicit awards are not listed here. She advises on graduate studies in networking and edge computing, though no specific student names are provided in the text. Her work often intersects with practical challenges in smart infrastructure and autonomous vehicle systems.

• Information Processing Systems
• Internet of Things (IoT)
• Edge Computing
• +4 more

Marcello Pietri is a Researcher (td art. 24 c. 3 lett. A) and Contract Professor at the Department of Engineering Sciences and Methods (DISMI) at the University of Modena and Reggio Emilia. His work focuses on Information Processing Systems, with expertise in IoT, Edge Computing, and Digital Twins. He teaches courses like 'Sistemi Informativi' (Information Systems) for the Engineering Management program, emphasizing database design, SQL, and web application development with Python. His research explores advanced topics including Digital Twin integration in Industry 5.0, Fluid Computing in IoT ecosystems, and Smart City data fusion using 5G MEC architectures. He collaborates with institutions like the DIPI Lab (Distributed and Pervasive Intelligence Group), contributing to projects on telecom security, energy forecasting, and human-centric manufacturing systems. Recent publications highlight innovations in operator digital twins for workplace well-being, distributed data mesh models for IoT-edge-cloud systems, and adaptive monitoring algorithms for large-scale cloud environments. His work bridges theoretical advancements with practical implementations, addressing challenges in scalability, real-time data processing, and interdisciplinary collaboration.

• Electrical Engineering
• Computer Science
• Information Technology
• +3 more

Bernhard Rinner is a Professor at the Institute of Networked and Embedded Systems within the Faculty of Technical Sciences at Alpen-Adria-Universität Klagenfurt. He is a member of the university Senate and serves as Prodekan (Deputy Dean). His research spans robotics, embedded systems, sensor networks, and privacy-aware computing , with a focus on resource-efficient designs for drones, autonomous systems, and IoT applications. Email: Bernhard.Rinner@aau.at Phone: +43 463 2700 3671 Office: B02.1.62, Lakesidepark Haus B02, Klagenfurt, Austria Research Interests include: Self-aware autonomous systems for adaptive mission planning and anomaly detection Resource-efficient embedded AI for drones and camera networks Secure IoT applications with privacy-preserving visual data processing Multi-agent coordination in confined environments and 3D navigation Dynamic sensor calibration for low-cost wireless networks Publications reflect trends in drone networks, self-aware computing, and privacy-aware sensing , emphasizing lightweight architectures, distributed coordination, and energy-efficient designs. Many recent works focus on binary neural networks, decentralized re-identification, and adaptive sensor reconfiguration .

Mehdi DastaniView profile

Professor

• Artificial Intelligence
• Multi-Agent Systems
• Formal Methods in AI
• +5 more

Prof. Mehdi Dastani is a Professor and chair of the Intelligent Systems group within the Department of Information and Computing Sciences at Utrecht University's Faculty of Science. He leads the Master's program in Artificial Intelligence and focuses on formal and computational models in AI, particularly multi-agent systems. His research integrates insights from philosophy, psychology, and law to develop autonomous agents that reason about social and cognitive concepts like norms, emotions, and responsibility. Dastani has held academic roles at Utrecht University since 2001, including postdoctoral research and faculty positions. Education: M.Sc. Computer Science (University of Amsterdam, 1991), M.Sc. Philosophy (University of Amsterdam, 1992), Ph.D. in Humanities (University of Amsterdam, 1998). His work spans theoretical and applied projects, including grants for initiatives like Golden Agents (simulating Golden Age creative industries) and traffic control systems using virtual organizations. He is actively involved in academic committees, editorial boards, and organizing international conferences like AAMAS and PRIMA. Research Interests: Multi-Agent Programming, Normative Systems, Autonomous Agents, Cognitive Robotics, and Human-Centered AI. His projects address challenges like norm enforcement, decision-making in complex systems, and ethical AI integration with societal needs. Advising & Grants: Supervised numerous PhD students (e.g., Birna van Riemsdijk, Bas Testerink) and secured grants for projects such as 'Controllable AI: Human-Centered Approach'. His work includes collaborations on urban governance, autonomous driving, and AI tools for literacy support in children. Labs & Teams: Leads the Intelligent Systems group, contributing to agent-based simulations, ethical AI frameworks, and interdisciplinary collaborations with social scientists and urban planners.

Vijay GaneshView profile

Professor

• SAT/SMT Solvers
• Artificial Intelligence
• Formal Methods
• +5 more

Dr. Vijay Ganesh is a Professor of Computer Science at Georgia Institute of Technology, where he also serves as Associate Director of the IDEaS Institute and is affiliated with Tech AI. Previously, he held roles as Associate Professor (2018–2023) and Assistant Professor (2012–2018) at the University of Waterloo, and Research Scientist at MIT (2007–2012). He earned his PhD from Stanford University in 2007. His research focuses on SAT/SMT solvers and their applications in AI, software engineering, security, mathematics, and physics. Notable contributions include developing solvers like MapleSAT, Z3str4, and AlphaZ3, and exploring machine learning-augmented reasoning. He has led projects in logic for AI, proof complexity, and security of blockchain technologies. His awards include ACM Impact Paper (2019), ACM Test of Time (2016), and DATE’s Ten-Year Most Influential Paper (2008). He has advised startups like Quantstamp, a blockchain security firm, and co-directed the Waterloo AI Institute (2021–2023). His teaching includes courses on discrete mathematics, software engineering, and AI. Education: PhD in Computer Science, Stanford University (2007); Master’s in Electrical Engineering, Stanford (2000) Research Interests: SAT/SMT solvers, formal methods, automated testing, AI security, combinatorial mathematics Affiliations: Georgia Tech’s School of Computer Science, IDEaS Institute

• Business Analytics
• Operations Research/Management
• Operational Analytics
• +7 more

Mehdi Toloo is a Reader in Business Analytics at the University of Surrey's Surrey Business School. He holds a BSc, MSc, and PhD, and is a docent. Previously, he was a Professor at Technical University of Ostrava (Czech Republic) and Sultan Qaboos University (Oman). His research focuses on Business Analytics, Operations Research, Data Envelopment Analysis (DEA), and Decision Analysis. He has supervised over 40 postgraduate students and contributed to top-tier journals like European Journal of Operational Research and Omega. He is an editor for journals including Computers & Industrial Engineering and Decision Analytics. Recognized globally, he ranks in the top 2% of scientists worldwide in Business Analytics & Operations Research (2020-2024). His research projects include performance evaluation with unclassified factors, economies of scope in network DEA, and selective measures in DEA. He collaborates internationally on projects like robust optimization and supply chain sustainability. His teaching spans undergraduate courses in Operations Research, Mathematics for Business, and Programming, alongside postgraduate modules on Quantitative Methods and Advanced DEA. His work bridges theoretical and applied research, with applications in healthcare, renewable energy, and public policy.

• Computational Engineering
• Biomedical Engineering
• Digital Twin
• +4 more

Professor Perumal Nithiarasu is a Professor and Director of Research in the College of Engineering at Swansea University. He also serves as Deputy Head of the College and Dean of Academic Leadership (Research Impact). His expertise spans computational engineering, biomedical engineering, and artificial intelligence, with a focus on blood flow dynamics and finite element methods. He has held leadership roles, including directing the Zienkiewicz Center for Computational Engineering and co-chairing international conferences like the Computational Biomedical Engineering series. Notable awards include the Zienkiewicz ICE Silver Medal (2002) and an EPSRC Senior Fellowship (2006). Research Interests: Computational Fluid Dynamics (CFD) Biomedical Engineering Applications Finite Element Method (FEM) Digital Twin Technology Artificial Intelligence in Biomedical Systems Scientific Contributions: Professor Nithiarasu has pioneered numerical methods like the Locally Conservative Galerkin (LCG) and developed influential tools such as the Zienkiewicz Lecture series. His work bridges computational models with clinical applications, including cardiovascular simulations and patient-specific coronary analysis. He leads a 30+ member research group and edits the International Journal for Numerical Methods in Biomedical Engineering . Grants & Impact: His research has been funded by EPSRC and other bodies, with applications in medical devices (e.g., glaucoma treatment shunts) and thermal systems. Collaborations include RAEng, IACM, and industry partners.

DU MingView profile

Visiting Professor

• Global Economic Governance
• International Law
• Rule of Law in China
• +3 more

Professor DU Ming is a Visiting Professor in Chinese Law and Co-Director of the Global Policy Institute at Durham University. He holds an LLM from Harvard Law School and a DPhil from the University of Oxford. His research focuses on global economic governance, China's approach to international law, and the development of legal frameworks in contemporary China. He advises on complex international disputes and sits on editorial boards of leading law journals. **Education:** Tsinghua University School of Law (China) LLM, Harvard Law School (Victor and William Fung Fellow) DPhil, University of Oxford (Clarendon Scholar) **Research Interests:** His work bridges legal theory and practice, particularly in cross-border trade/investment law, corporate governance, and the ethical implications of emerging technologies. Recent publications explore federated learning governance, model licensing, and AI ethics within legal systems. **Awards:** Victor and William Fung Fellowship (Harvard) Clarendon Scholarship (Oxford) His advisory roles and legal practice in New York and Beijing inform his research on transnational legal challenges. Collaborations span technical and legal domains, addressing issues like data privacy in federated learning systems.

Angel Santamaria NavarroView profile

Associate Professor

• Mobile Robotics
• Autonomous Systems
• Human-Robot Interaction
• +3 more

Angel Santamaria-Navarro serves as Associate Professor at Polytechnic University of Catalonia (UPC) and Robotics Researcher at the Institute of Robotics and Industrial Informatics (IRI), a CSIC-UPC joint center in Barcelona. His work bridges academic research and real-world deployment in mobile robotics, with current leadership in European TRIFFID (autonomous first-responder systems) and national LENA (lifelong navigation learning) projects spanning urban logistics and emergency response applications. His research centers on Mobile Robotics and Autonomous Systems with emphasis on human-robot collaboration in unstructured environments . Key focus areas include robot navigation in crowded urban settings, manipulation of deformable objects, and deployment of delivery systems like the LogiSmile project piloted across European cities. His work uniquely integrates machine learning with field robotics to solve practical challenges in last-mile logistics and disaster response. Recent publications (2022-2025) reveal a concentrated shift toward real-world robotic deployment , particularly in emergency response (TRIFFID) and urban logistics. Dominant themes include communication-aware multi-robot coordination, probabilistic perception for dynamic environments, and human acceptance studies – reflecting his commitment to transitioning lab innovations to operational field systems through Horizon Europe and national projects. Key recognitions include: 1st place at DARPA Subterranean Challenge, urban circuit (2020) 2nd place at DARPA Subterranean Challenge, tunnel circuit (2019) Beatriu de Pinós research fellowship (2021) Georges Giralt PhD award finalist (2018) R3 accreditation as consolidated researcher (2023) He actively mentors next-generation researchers as supervisor of PhD candidate Hafsa Taher (deep learning for autonomous vehicles) and Master's student Joan Tur Ruiz (object pose tracking). His research portfolio includes €5M+ in competitive funding spanning Horizon Europe projects (TRIFFID, TORNADO), national initiatives (LENA, AUDEL), and industry partnerships like the Vaive Logistics spin-off co-founded in 2023. As core member of UPC's robotics team, he contributed to the NeBula framework that won DARPA's Subterranean Challenge and currently leads development of TRIFFID's autonomous first-responder systems. His work with the LogiSmile consortium demonstrates practical urban deployment of delivery robots across Barcelona, Lisbon, and Milan, while the SOCIAL PIA project pioneers cybernetic avatars for cooperative human-robot teams.