Find Academic Supervisors

Nick NikiforakisView profile

Associate Professor

• Web Security
• Software Security
• Cybersecurity
• +3 more

Nick Nikiforakis is an Associate Professor in the Department of Computer Science at Stony Brook University, with an affiliation to the National Security Institute. His research focuses on web security, privacy, software security, and intrusion detection, with particular emphasis on analyzing online ecosystems, domain squatting, honeypot deployment, and client-side defense mechanisms. He completed his PhD in Computer Science at KU Leuven (Belgium), and holds an MSc in Parallel and Distributed Systems and a BSc in Computer Science from the University of Crete, Greece. His work has been funded by NSF and ONR grants, including projects addressing vulnerability scanning, social engineering defenses, and mobile browser security. Nikiforakis' awards include a Distinguished Paper Award at NDSS 2017 and a Best Paper Award at ISC 2014. He teaches courses CSE 508 (Computer Security), CSE 509 (Advanced Topics in Security), and CSE 361 (Data Structures and Algorithms). His research explores cutting-edge threats like blockchain naming system abuse, cryptocurrency scams, and adversarial AI-driven misinformation campaigns.

Rachida DssouliView profile

Professor

• Software Engineering
• Quality Assurance
• Service Engineering
• +7 more

Rachida Dssouli is a Professor at the Concordia Institute for Information Systems Engineering (Concordia University). Her research focuses on advanced software engineering methodologies, quality assurance systems, and distributed computing frameworks. She specializes in model-based testing, federated learning optimization, and big data quality management. Her work integrates formal verification techniques with modern machine learning approaches to address challenges in edge computing, IoT, and safety-critical systems. Key research areas include: Development of hybrid swarm intelligence algorithms for optimizing large language model deployment in edge-cloud environments Design of reinforcement learning frameworks for robotics motion planning and IoT device scheduling Creation of interpretable machine learning tools for fault detection in software systems Establishment of holistic big data quality frameworks for continuous monitoring and unstructured data analysis Formal verification methods for avionics systems using multi-agent models Her recent work demonstrates trends toward AI-driven solutions for testing methodologies (e.g., SHAP-Driven fault detection) and edge-cloud integration (e.g., MIMO-based computation offloading optimization). The 2025 publications highlight advancements in federated learning and trust-aware IoT scheduling. Earlier works (2018-2020) emphasize foundational contributions to cloud trust models, big data quality metrics, and safety-critical system testing. Her research also addresses emerging technologies for developing countries through frameworks like neurodegenerative disease monitoring systems and mobile application requirements engineering. She has contributed to service-oriented architectures for healthcare systems and cloud-based resource orchestration strategies.

Dejun YangView profile

Associate Professor

• Networking
• Mobile Sensing
• Edge Computing
• +5 more

Dejun Yang is an Associate Professor in the Department of Computer Science at Colorado School of Mines. He directs the NEMOS (Networking and Mobile Sensing) Lab, focusing on advancing networking, mobile sensing, and edge computing through interdisciplinary approaches involving game theory, optimization, machine learning, and algorithm design. His work addresses challenges in resource allocation, security, and privacy across domains like IoT, quantum internet, and blockchain-based systems. Education: B.S. in Computer Science, Peking University (2007) Ph.D. in Computer Science, Arizona State University (2013) Research Interests: Networking and satellite communications Edge computing security and SLA enforcement Incentive mechanisms for crowdsourcing and blockchain Quantum internet resource distribution Privacy-preserving mobile sensing Recent Article Trends: His 2023-2025 work emphasizes blockchain payment networks (e.g., fee-aware routing, crypto capital incentives) and edge computing SLA markets. Earlier studies focused on crowdsourcing mechanisms and spectrum auctions. Scientific Awards: Recipient of Best Paper Awards at GLOBECOM’15, ICC’12, ICC’11, MASS’11, and a Best Paper Runner-Up at ICNP’10 (2010-2015). Lab & Collaboration: Leads the NEMOS Lab, which develops innovative solutions for mobile sensing, edge computing, and secure distributed systems. Active in interdisciplinary collaborations involving industry partners and academic institutions.

• Database Systems
• Data Management
• Data Mining
• +4 more

Michael Grossniklaus is a Professor at the University of Konstanz, Germany, specializing in database systems, data management, and information systems. His research focuses on query optimization, social media data streams, and object-oriented databases. He has contributed to the development of C-SPARQL for RDF stream processing and frameworks for adaptive data management. Grossniklaus has collaborated extensively with researchers in areas such as trajectory data modeling, cloud database optimization, and context-aware systems. His work emphasizes practical applications in education technology, mobile computing, and semantic web technologies. Affiliation: University of Konstanz, Germany Key Research Areas: Database Systems, Data Mining, Social Media Analysis, Query Optimization Notable Projects: C-SPARQL, Sahara (cloud database optimization), LPLM (neural cardinality estimation) Recent publications highlight advancements in neural models for cardinality estimation, trajectory data models, and memory optimization in cloud databases. His interdisciplinary approach bridges theoretical foundations with real-world applications in education, social media, and mobile systems.

Cain EvansView profile

Teaching Professor

• Software Engineering
• Cyber Security
• Artificial Intelligence
• +5 more

Dr. Cain Evans is a Teaching Professor at Aston University, serving as co-Programme Director for the MSc DTSS Degree Apprenticeship within the College of Engineering and Physical Sciences. He holds a prominent role in leading degree apprenticeship programs and has over 24 years of teaching experience across the UK and Far East, specializing in Computer Science, Software Engineering, and pedagogical research. His research focuses on intelligent systems, context-aware technologies, digital health (smart-care spaces), and AI-driven applications. He has served as an external examiner at multiple UK universities and has held senior academic roles at institutions like Birmingham City University and Northumbria University. His professional affiliations include Fellow of the Higher Education Academy (FHEA), STEM Ambassador, and memberships in BCS and IEEE. Research Interests: Dr. Evans' work spans interdisciplinary areas including software engineering, cyber security, AI (data science/mining), and pedagogy. Recent trends in his publications highlight advancements in smart care systems (e.g., pervasive sensing for at-home care), algorithmic trading models using neural networks, and mobile advertising frameworks like iMAS. His contributions also address challenges in e-education and future iCampus developments. Awards : Birmingham and Solihull STEM Ambassadors Award (2010) 15th Anniversary Outstanding Reviewer Awards (2016) Nominated for Engaging & Inspiring Teacher of the Year (2017) Advising & Grants : Supervisor for MSc Data Science and DTSS Professional projects Past roles include Programme Director for BSc DTS Professional and external examiner at Bradford, Brighton, and University of Wales Labs/Teams : Active in interdisciplinary collaborations, particularly in smart-care and AI applications, though no specific lab names are mentioned.

Véronique VEQUEView profile

Professor

• Wireless Networks
• Vehicular Networks
• Network Routing
• +3 more

Véronique VEQUE is a Professor at CentraleSupélec, working within the L2S research laboratory. Her research focuses on networking technologies including wireless networks, vehicular networks, and satellite communications. She specializes in developing efficient routing protocols, mobility management systems, and energy optimization techniques for next-generation networks. Dr. Veque's current research examines flexible resource allocation in disaggregated RAN architectures, intelligent routing algorithms for dense WiFi networks, and predictive modeling for IoT congestion control. Her work combines theoretical modeling with practical implementations for telecommunications systems. Her publication record spans network architecture design, mobility modeling, routing optimization, and energy-efficient communication. Recent work has focused on Open-RAN functionality placement, Cloud-RAN resource allocation, and stochastic mobility modeling for urban environments.

Carlos CardonhaView profile

Assistant Professor

• Discrete optimization
• Mixed-integer linear programming
• Combinatorial optimization
• +6 more

Carlos Cardonha is an Assistant Professor in the Department of Operations and Information Management at the University of Connecticut School of Business since 2019. He holds a Ph.D. in Mathematics from Technische Universität Berlin (2011) and degrees in Computer Science from the University of São Paulo (B.Sc. 2004, M.Sc. 2006). Previously, he worked as a Research Staff Member at IBM Research – Brazil (2012–2019). His research focuses on discrete optimization, approximation algorithms, and applications of machine learning and mathematical programming to operations research problems. He teaches courses such as OPIM 5641 (Business Decision Modeling) and OPIM 3511 (Business Data Analytics II), supported by DataCamp. Education: Ph.D. in Mathematics, Technische Universität Berlin, Germany (2011) M.Sc. in Computer Science, University of São Paulo, Brazil (2006) Bachelor in Computer Science, University of São Paulo, Brazil (2004) Research Interests: His work spans analytics, optimization, and theoretical computer science, with a focus on mixed-integer linear programming, combinatorial optimization, and algorithm design. He applies these techniques to real-world problems in scheduling, resource allocation, and machine learning model optimization. Grants & Advising: No specific grants or advisees are listed in the provided materials. Labs/Teams: Not explicitly mentioned in the text.

Tuan-Loc NguyenView profile

Lecturer

• High Performance Computer Architecture
• Multi-cloud Computing
• 5G Networks
• +5 more

Tuan-Loc Nguyen serves as a Lecturer in the Department of Electrical Engineering at San José State University while concurrently working as Sr Technical Product Manager at VMware. His academic credentials include a Ph.D. in Telecommunications from Paris-Sorbonne University (2004) and an IT Engineering degree from Polytechnic University, Vietnam (1999). Ph.D. in Telecommunications, Paris-Sorbonne University, France (2004) IT Engineering, Polytechnic University, Vietnam (1999) His research centers on High Performance Computer Architecture across multi-cloud platforms (AWS, Azure, GCP, IBM, KVM, VMware ESXi, OpenStack) and 5G Network Slicing applications (vEPC, IoT/connected vehicles, Mobile Edge Cloud). He actively develops open-source networking solutions through OpenFlow, OpenDaylight, SDN/OPNFV/M-CORD, and Networking Orchestration projects, with specialized expertise in DPDK and SRIOV technologies through the Intel Innovator program. Current collaborations with VMware's CTO office focus on 5G Telco solutions for Service Assurance, Network Automation, and containerization initiatives. Professional recognition includes: Intel Innovator Program Member for Network High Performance While no formal advising relationships or grant details are documented in the source material, his industry-academia bridge through VMware and open-source contributions demonstrates significant professional impact. His work environment spans SJSU's Engineering Building (Room 347A) and VMware's virtualization ecosystem without dedicated lab/team specifications in the provided text.

• Cloud Computing
• High Performance Computer Architectures
• Parallel and Distributed Processing
• +3 more

Dr. Robert K. Chun is a Professor in the Department of Computer Science at San José State University (SJSU), part of the College of Engineering. He holds a BSEE (1979), MSCS (1981), and Ph.D. (1989) from UCLA. With 20+ years in industry, he joined SJSU as a full-time faculty in 2001. His research focuses on Cloud Computing, parallel processing, high-performance architectures, and AI. He received NASA Faculty Fellowships (2002-2003) and holds a U.S. patent for real-time expert systems integration. Education: Bachelor of Science, Electrical Engineering, UCLA (1979) Master of Science, Computer Science, UCLA (1981) Doctor of Philosophy, Computer Science, UCLA (1989) Research Interests: Cloud Computing architectures and scalability High-performance computing and parallel algorithms Software engineering for distributed systems CAD tools for VLSI design verification Artificial intelligence and neural networks Publications highlight advancements in parallel processing, distributed systems, and compiler optimization. Notable works include adaptive transactional memory algorithms, wireless cluster computing frameworks, and EJB performance measurement tools. His NASA-funded research at Ames Supercomputing Center explored parallel computing applications. Advising and Grants: Advised 16 Master’s theses, including topics like dynamic clusters and intelligent debuggers Contributed to industry-university partnerships through NASA collaborations Labs/Teams: Active in SJSU’s parallel processing and computer architecture research groups, contributing to course development in advanced parallel processing and operating systems.

Jay ChenView profile

Assistant Professor

• ICT for Development
• Human-Computer Interaction
• Pluralistic Networked Systems
• +2 more

Jay Chen is Research Assistant Professor at NYU Tandon School of Engineering and Co-Director of the Design Technology Lab. His research develops information and communication technologies for underserved populations, focusing on voice-based systems, privacy in shared device contexts, and pluralistic network architectures. Key contributions include: Karamad voice-based crowdsourcing platform for low-literacy users Studies of mobile privacy in Bangladesh and India Stencil pluralistic cloud architecture Publications demonstrate 50% focus on Global South technologies, 30% on network architectures, and 20% on sustainable computing. Recent work examines financial networks, game theory representations, and resilient connectivity solutions.

Blesson VargheseView profile

Associate Professor

• Distributed Systems
• Cloud Computing
• Edge Computing
• +3 more

Dr. Blesson Varghese is an Associate Professor and Reader in the School of Computer Science at the University of St Andrews, leading the Edge Computing Hub funded by Rakuten, Japan. He holds an honorary faculty position at Queen's University Belfast. His research focuses on distributed systems, edge computing, and federated learning, addressing challenges in scalability, resource efficiency, and real-time applications. He has received prestigious awards, including the 2021 IEEE Rising Star Award and a Royal Society Industry Fellowship. Teaching includes CS5052: Data-Intensive Systems, emphasizing large-scale distributed systems design. He advises PhD students in edge computing and collaborative machine learning. Notable publications include DNNShifter (2024), EcoFed (2024), and NeuroFlux (2024), advancing edge computing and federated learning techniques. Awards include the IEEE Rising Star Award, Best Paper Award (IEEE Edge Conference 2022), and Finalist at GSMA Mobile World Congress 2019. His work bridges academia and industry, with collaborations across continents and contributions to open-source projects like FedAdapt and DNNShifter.

Ming XiaoView profile

Associate Professor

• Wireless Communications
• Network Coding
• Machine Learning
• +10 more

Ming Xiao is an Associate Professor in the Division of Information Science and Engineering at KTH Royal Institute of Technology's School of Electrical Engineering and Computer Science (EECS). He is affiliated with the Digital Futures Faculty and leads research in wireless communications, machine learning, and network coding. His work focuses on 6G networks, distributed learning, and secure communications. Affiliations: KTH EECS, Digital Futures, Swedish Research Council, EU Horizon Europe projects Roles: Editor for IEEE Transactions on Wireless Communications, TPC Co-Chair for VTC Fall Research Interests: Dr. Xiao's expertise spans wireless communication systems (e.g., mmWave, NOMA), network coding, machine learning applications in communications, and energy-efficient distributed systems. He has pioneered work on intelligent reconfigurable surfaces (RIS), federated learning in edge computing, and integrated sensing-communications (ISAC). Projects: Ongoing EU-funded projects include ASCENT (autonomous vehicular networks) and COVER (unmanned aerial vehicles for emergency response). Past projects include 6G channel coding and intelligent energy management in smart communities. Grants: Over 12 active grants from VR, EU Horizon Europe, FORMAS, STINT, and VINNOVA Awards: IEEE Vehicular Technologies Society Best Paper Award (2023), World Top 2% Researcher (2020–2023), Highly Cited Researcher in Computer Science/Engineering. Labs/Teams: Leads the KTH Digital Futures initiative, collaborates with RISE Research Institutes, and manages a team of 12 PhD students/postdocs focusing on 6G, distributed ML, and secure IoT.

• Database Systems
• Mobile and Pervasive Data Management
• Distributed Computing
• +5 more

Panos K. Chrysanthis is a Professor of Computer Science at the University of Pittsburgh and an adjunct Professor at Carnegie-Mellon University and the University of Cyprus. He holds a BS in Physics with a Computer Science concentration from the University of Athens, Greece, and MS and PhD degrees in Computer and Information Sciences from the University of Massachusetts Amherst. He has been affiliated with the University of Pittsburgh since 1991, serving as Director of the Advanced Data Management Technologies (ADMT) Lab. His research focuses on database systems, mobile and pervasive data management, distributed computing, and real-time systems, with recent emphasis on data streams and energy-efficient data management for IoT and sensor networks. Chrysanthis has authored over 100 peer-reviewed publications, including a book on transaction processing and consistency in distributed databases. He has received the NSF CAREER Award (1995) and the University of Pittsburgh's Provost Award for Excellence in Mentoring (2015). He has held editorial roles at the VLDB Journal, IEEE TKDE, and DAPD, and has organized major conferences like ICDE and MDM. His work bridges theoretical database research with practical applications in urban informatics, healthcare, and sustainability. Chrysanthis has advised numerous students, contributed to grants focused on big data and healthcare analytics, and co-developed tools like the ADMT Lab's experimental platforms for urban mobility and congestion. He is a Senior Member of IEEE and an ACM Distinguished Scientist.

• Computer Networks
• Edge Computing
• Internet of Things (IoT)
• +5 more

Paolo Bellavista is a Full Professor of Distributed and Mobile Systems at the Department of Computer Science - Science and Engineering, Alma Mater Studiorum – University of Bologna. His research focuses on edge computing, federated learning, IoT, digital twins, and blockchain applications. With over 140 journal articles and 200+ conference papers, his work appears in top venues such as ACM Computing Surveys and IEEE Transactions. He serves as Editor-in-Chief of the MDPI Computers Journal and holds editorial roles in IEEE Communications Surveys&Tutorials and ACM Computing Surveys. His contributions span network optimization, cybersecurity, and smart cities, with notable achievements in citation metrics (h-index 46 on Google Scholar). Research interests include distributed systems, vehicular networks, AI-driven security, and QoS-aware edge infrastructures. He has organized major conferences like IEEE Mobile Cloud and ACM ICDCN. Current projects explore federated learning unlearning, digital twin entanglement, and blockchain-based data spaces. His work bridges theoretical foundations with real-world deployments in smart manufacturing and healthcare. Editorial Roles : MDPI Computers (Editor-in-Chief), IEEE Communications Surveys&Tutorials (Associate Editor), ACM Computing Surveys (Editor) Conference Leadership : Technical Program Chair for IEEE Mobile Cloud 2015, General Co-Chair for SCNS 2018 Key Contributions : Over 140 journal papers, 15 special issues as guest editor, and 200+ conference publications His lab develops middleware for edge-cloud continuum applications and collaborates internationally on projects like InAbled Cities. Office hours are held weekly at the University of Bologna’s DISI department.

Siris VasiliosView profile

Professor

• Resource Management in Networks
• Distributed Ledger Technologies (DLTs)
• Blockchains and IoT Security
• +3 more

Professor Siris Vasilios holds the position of full Professor at the Department of Informatics, Athens University of Economics and Business (AUEB). Previously, he served as Assistant and Associate Professor at AUEB (2009–2020) and the University of Crete (2002–2009). His expertise spans resource management in networks, blockchain-based IoT security, and future communication systems. He has published over 150 papers in top venues like IEEE INFOCOM and ACM Mobicom, and holds three patents in wireless resource management. Education: Diploma in Physics (1990), National and Kapodistrian University of Athens M.S. in Computer Science (1992), Northeastern University, Boston, USA Ph.D. in Computer Science (1998), University of Crete Research Interests: His work focuses on trusted communication in IoT , leveraging blockchain technologies for secure systems. Key areas include distributed ledger applications, energy-efficient network protocols, and satellite-terrestrial integration. He emphasizes combining theoretical methods with practical system implementations. Awards & Recognition: He has coordinated EU-funded projects (e.g., SOFIE) and served as Technical Program Chair for IEEE WoWMoM 2018 and IQ2S 2015. His research has been recognized through grants from Greek governmental and industry partners. Grants & Projects: Principal Investigator for multiple EU research projects Lead on Greek national and industry-funded initiatives Contributed to the SOFIE project addressing IoT security via interledger technologies Labs & Teams: Active in the Department of Informatics' research groups, focusing on experimental systems like Dedalus for wireless maritime networking and blockchain-based IoT prototypes.