Find Academic Supervisors

Bharanidharan ShanmugamView profile

Associate Professor

• IoT Security
• Cyber Risk Management
• Network Security
• +3 more

Dr. Bharanidharan Shanmugam is an Associate Professor in Information Technology at Charles Darwin University's Faculty of Science and Technology. He specializes in cybersecurity, IoT security, and cyber risk management in microgrids. His research focuses on addressing real-world challenges in IoT, smart grids, and medical devices to enhance community impact. **Research Interests:** - IoT Security - Cyber Risk Assessment in Microgrids - Network and Information Security - Applied Cybersecurity Solutions - Blockchain and Privacy-Preserving Technologies **Key Projects (2019–2025):** - Cyber Territory Skills Hub (2023–2025) - Renewable Energy Microgrid Hub (2021–2024) - Blockchain-Based Digital Identity (2019–2020) **Publications:** Focuses on IoT security frameworks, intrusion detection systems, and AI-driven cybersecurity solutions. Recent works include studies on smart grid load forecasting, medical IoT threat detection, and water leakage detection using machine learning. **Grants & Supervision:** Principal Investigator on multiple ARC-funded projects. Supervises PhD students in DevSecOps and IoT security. Active in organizing workshops on digital awareness for indigenous communities.

Liqiang WangView profile

Professor

• Big Data Analytics
• High-Performance Computing (HPC)
• Parallel Computing
• +3 more

Liqiang Wang is a Professor in the Department of Computer Science at the University of Central Florida (UCF), where he directs the Big Data Lab. Previously, he served as faculty at the University of Wyoming (2006-2015). He holds a Ph.D. in Computer Science from Stony Brook University (2006) and spent a visiting research period at IBM T.J. Watson Research Center (2012-2013). His research focuses on big data analytics, high-performance computing, parallel systems optimization, and applying deep learning to detect programming errors and enhance model robustness. Education: Ph.D., Computer Science, Stony Brook University (2006); Visiting Researcher, IBM Watson (2012-2013). Research Interests: Improving accuracy and security of big data models, optimizing parallel computing systems (HPC, Cloud, GPUs), program analysis for concurrency errors, and deep learning applications in anomaly detection and adversarial robustness. Notable projects include scalable LSQR algorithms for seismic tomography and the OpenMP Analysis Toolkit (OAT) for concurrency error detection. Key Awards: NSF CAREER Award (2011), Castagne Faculty Fellowship (2013-2015), UCF Mid-Career Refresh Award (2020), and grants including a $50K NSF CIVIC-PG grant (2022) and Google/Meta donations. Advising and Grants: Supervises over 20 Ph.D./M.S. students and has secured grants totaling over $100K. Notable collaborations include seismic tomography with NCAR and cloud computing optimization. Labs/Teams: Director of UCF’s Big Data Lab, collaborating on projects like Parallel LSQR and Anti-Neuron Watermarking.

Rocco OLIVETOView profile

Professor

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +7 more

Prof. Rocco OLIVETO is a Full Professor at the University of Molise, affiliated with the School of Biosciences and Territory. His research spans software engineering, artificial intelligence, cybersecurity, and healthcare technology. He focuses on empirical studies of developer practices, AI-driven code analysis, vulnerability detection in smart contracts, and human-centric computing. His work also addresses challenges in game development, mobile app optimization, and wearable health monitoring systems. Notable research areas include code readability assessment, machine learning applications in healthcare diagnostics, and the effectiveness of AI tools like GitHub Copilot. He has contributed to projects like QualAI (continuous quality improvement for AI systems) and 2Vita-B (cognitive and physical rehabilitation systems). His empirical studies often bridge academic research with real-world developer workflows, emphasizing practical applicability. Prof. Oliveto's recent work explores topics such as automated gameplay analysis for game debugging, detection of engagement issues in video games, and robust methods for identifying security vulnerabilities. He has also investigated Dockerfile quality, developer frustration metrics, and the ethical implications of AI in administrative document simplification.

• Software Engineering
• Cyber-Physical Systems
• Digital Ecosystems
• +3 more

Tero Päivärinta is a Professor at the University of Oulu, Faculty of Information Technology and Electrical Engineering. His work focuses on software engineering, digital ecosystems, and cybersecurity. He specializes in empirical studies of software systems, digital twins, and autonomous driving technologies. His research explores hybrid intelligence systems, data-centric decision-making, and governance of collective ambidexterity in digital initiatives. Education: PhD holder with extensive experience in academic and industry collaborations. Key research domains include cyber-physical systems, DevSecOps automation, and IT governance in public sectors. He co-leads projects such as the NUVE Lab’s vehicle testing frameworks and contributes to initiatives like the Software-Defined Vehicle project. Research highlights include advancing knowledge graphs for manufacturing, cybersecurity compliance in DevOps pipelines, and evaluating data-driven decisions. His articles emphasize interoperability challenges, adaptive systems design, and sustainable digital transformation in public utilities. Professional contributions include organizing the TKTP Annual Symposium and co-editing volumes celebrating academic peers like Markku Oivo. His work bridges theoretical software engineering with practical applications in mobility, governance, and industrial systems.

Tanel AlumäeView profile

Associate Professor

• Speech Processing
• Natural Language Processing
• Machine Learning
• +5 more

Tanel Alumäe is a Tenured Associate Professor of Speech Processing and Head of the Laboratory of Language Technology at Tallinn University of Technology (TalTech). He holds a PhD in Information and Communication Technology from TalTech (2006) and has conducted research at institutions like LIMSI/CNRS, Aalto University, and Raytheon BBN Technologies. His research focuses on speech processing, speaker and language recognition, and low-resource language technologies. Affiliations: Department of Software Science, School of Information Technologies, TalTech. Education: PhD in ICT (2006), MSc in Informatics (2002), Diploma in Computer & Systems Engineering (1999). Research interests include speech recognition, speaker diarization, spoken language translation, and combating DeepFake voices. He leads teams achieving top results in competitions like IARPA BABEL, NIST LRE, and Interspeech challenges. His work emphasizes open-source tools and equitable AI solutions. Key Awards: Best Student Paper at Odyssey 2024 and TSD 2018. Keeletegu Awards (2019, 2011) for contributions to Estonian language technology. Grants & Leadership: Managed the National Programme for Estonian Language Technology (2011–2017). Serves as Secretary of the Northern European Association for Language Technology (NEALT) and Area Chair for ICME, EACL, and Interspeech conferences. Labs & Teams: Directs the Laboratory of Language Technology, focusing on practical applications of speech and language technologies.

Karim ZKIKView profile

Associate Professor

• Cybersecurity
• Blockchain Technologies
• Artificial Intelligence
• +3 more

Karim ZKIK is an Associate Professor of Cyber Security and Information Systems at ESAIP Graduate School of Engineering, Angers, France. Previously, he served as an Assistant Professor at the International University of Rabat (UIR), Morocco. His roles include Educational Manager of the Cyber Security track, Head of the Cybersecurity Innovation Hub, and committee member for ABET certification and curriculum design. He actively contributes to academic service, organizing conferences such as the International Conference on Cryptology, Coding Theory, and Cyber Security (I4CS 2022), and serves as a Guest Editor for Computers and Industrial Engineering . His research focuses on cybersecurity for connected systems, blockchain technologies, AI-driven security solutions, and cyber resilience in industrial control systems. Recent work explores integrating blockchain and machine learning for threat detection, secure IoT networks, and supply chain resilience. Key contributions include frameworks for cyber resilience in retail and airlines, blockchain-based crowdfunding security, and SDN-based attack mitigation. ZKIK holds a Habilitation (2024) and PhD in Cyber Security from Université d’Angers and Mohamed V University, Rabat. He holds over 20 certifications from EC-Council, IBM, and Cisco. His work bridges theoretical research and industry applications, addressing challenges in smart environments, industrial systems, and sustainable supply chains.

M. Hadi AminiView profile

Assistant Professor

• Distributed Machine Learning
• Federated Learning
• Interdependent Networks
• +7 more

M. Hadi Amini is an Assistant Professor at Florida International University's Knight Foundation School of Computing and Information Sciences. He founded and directs the Sustainability, Optimization, and Learning for InterDependent networks (SOLID) laboratory, focusing on cyber-physical-social systems and distributed AI applications. Ph.D., Electrical and Computer Engineering (2019), Carnegie Mellon University M.Sc., Electrical and Computer Engineering (2015), Carnegie Mellon University M.Sc. (2013), Tarbiat Modares University B.Sc. (2011), Sharif University of Technology His research spans federated learning, interdependent network optimization, and AI applications in smart cities , energy systems , and healthcare . Recent work emphasizes privacy-preserving techniques, quantum encryption, and blockchain integration for secure distributed learning. The 15 most recent publications highlight trends in large language models , edge computing , medical imaging security , and infrastructure resilience , with interdisciplinary emphasis across computer science, systems engineering, and urban planning. Best Paper Award, IEEE Conference on Computational Science & Computational Intelligence (2019) Best Journal Paper Award, Springer Nature Operations Research Forum (2021) Excellence in Teaching Award, FIU (2020) Multiple Best Reviewer Awards, IEEE Transactions NSF Travel Awards (2019) As Associate Editor for Frontiers in Communications and Networks and book series editor for Sustainable Interdependent Networks , he actively shapes research discourse. His lab has secured $3.6M in federal/state funding for AI-driven infrastructure projects.

Alan MisloveView profile

Professor

• Algorithmic Auditing
• Fairness
• Privacy
• +4 more

Alan Mislove is a Professor of Computer Science at Northeastern University and serves as Senior Associate Dean for Academic Affairs and Interim Executive Director of the Institute of Experiential Artificial Intelligence (EAI). He is also a core faculty member of the Cybersecurity and Privacy Institute and EAI at Northeastern. His research focuses on algorithmic auditing, fairness, and privacy in online systems. Notably, he has testified before Congress on algorithmic discrimination, challenged the CFAA in ACLU litigation, and contributed to landmark FTC and DOJ cases against Meta. His work has been funded by the NSF, Army Research Office, Google, and Amazon Web Services. Mislove’s academic leadership includes roles in Khoury College, where he supports over 2,000 students and faculty. He has advised numerous PhD students, including current research scientist Piotr Sapieżyński. His lab explores algorithmic transparency, PKI security, and middlebox traffic differentiation. Key awards include the 2017 ACM SIGCOMM Test of Time Award and recognition for work on QUIC protocol evaluation. He has authored over 150 publications, including seminal studies on Facebook ad discrimination and Uber’s surge pricing. His teaching spans systems, networks, and social computing courses, emphasizing experiential learning. Mislove actively serves on program committees for IMC, PETS, and other top conferences, and contributed to policy as Deputy U.S. CTO for Privacy (2023–2024).

Nicola DragoniView profile

Professor

• Cybersecurity
• Internet of Things (IoT)
• Machine Learning
• +7 more

Nicola Dragoni is a Professor in Cybersecurity Engineering at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU). As Deputy Director and Head of Section, he leads research initiatives focused on securing emerging technologies. Key Research Areas : Internet of Things (IoT) security, machine learning for intrusion detection, cyber-deception techniques, fog computing, malware analysis, blockchain applications, and wireless sensor network security. Supervision : Actively supervising multiple PhD students in projects related to cyber-deception, moving target defense, and bio-inspired security mechanisms. Recent Publications : Contributions to IoT honeypots, drone identification via RF signals, passkey adoption challenges, and cyber range taxonomies.

Albert TreytlView profile

Researcher

• Communication Technologies
• Security
• Distributed Systems
• +4 more

Albert Treytl is a Senior Researcher at the Danube University Krems , serving as Head of the Center for Distributed Systems and Sensor Networks and Deputy Head of the Department for Integrated Sensor Systems. He holds a Master’s degree in Electrical Engineering from the Vienna University of Technology (2001) and has over two decades of experience in communication technologies and security. Current roles: Head of Center, Deputy Head of Department Research focus: Security for embedded systems, IoT, digital twins, AI in energy optimization Involvement: IEEE, CEN TC 247 WG4, IEEE1588 standardization His work addresses distributed data management, smart grid security, and model predictive control strategies for energy efficiency in buildings and traffic systems. He leads multiple national and international projects funded by FFG and EU programs. Recent research projects include KI4HVACS (AI-driven HVAC optimization), Factories4Renewables (industrial renewable energy integration), and Dataskop (sensor-based data economy). He has authored over 100 peer-reviewed publications and serves as co-lecturer at the Vienna University of Technology.

• Artificial Intelligence
• Cybersecurity
• Machine Learning
• +7 more

Vahid Behzadan is an Assistant Professor in Data Science and Computer Science at the University of New Haven's Tagliatela College of Engineering. He leads the SAIL Lab, focusing on AI safety and security, particularly in autonomous systems like driverless cars and smart cities. His work addresses adversarial attacks on machine learning and reinforcement learning, with applications in cybersecurity and healthcare. Behzadan has held prior positions at Kansas State University, University of Nevada Reno, and University of Birmingham, UK. He holds a Ph.D. in Computer Science and an M.S. from the University of Nevada Reno, and a B.Eng. from the University of Birmingham. His research spans AI ethics, cybersecurity, and complex systems. Behzadan advises the UNH hacking team and actively participates in policy initiatives, including Connecticut's AI Working Group and the Connecticut AI Alliance. He has contributed to over 30 peer-reviewed articles and frequently engages in media discussions on topics like AI safety, facial recognition, and cybersecurity threats. Key research areas include adversarial machine learning, AI forensics, and ethical AI design. His work bridges theoretical advancements with real-world applications in transportation, healthcare, and national security. Behzadan collaborates with organizations such as the Transportation Research Laboratory (TRL) and Open Web Application Security Project (OWASP).

Carly WayneView profile

Assistant Professor

• Political Violence
• Political Psychology
• Conflict Studies
• +7 more

Carly Wayne is an Assistant Professor in the Political Science Department at Washington University in St. Louis, with a PhD from the University of Michigan. Her research focuses on the psychological underpinnings of political violence, including emotions in conflict, foreign policy decision-making, and the Israeli-Palestinian conflict. She examines how cognitive and emotional processes influence public and elite behavior in conflict contexts. Her work bridges international relations and political psychology, with key projects analyzing the long-term effects of political violence exposure, group dynamics in foreign policy, and radicalization pathways. She co-authored The Polythink Syndrome (2016 Alexander George Book Award winner) and Beyond Rationality (2021), which integrate behavioral approaches into political science frameworks. Education : PhD in Political Science, University of Michigan Funding : NSF grant ($300K) for studying political radicalization and de-radicalization via social media analysis Research Themes : Emotion and cognition in conflict Exposure to violence and public opinion Group processes in foreign policy Israeli-Palestinian conflict dynamics White nationalist radicalization Her research has been published in top journals including the American Journal of Political Science, International Organization, and World Politics. She collaborates with scholars like Taylor Carlson (WashU) and Erin Rossiter (Notre Dame) on interdisciplinary projects. She currently leads a team analyzing a 180,000+ interaction dataset on Israeli-Palestinian violence (2010–2020) and investigates interpersonal communication pathways in radicalization. Her work emphasizes behavioral microfoundations and methodological innovation, including experiments and machine learning applications.

• Artificial Intelligence
• Machine Learning
• Software Engineering
• +6 more

Talal Shaikh is an Associate Professor at Heriot-Watt University's School of Mathematical and Computer Sciences in Dubai. He serves as Director of Undergraduate Studies and Programme Director for BSc Computer Science, BSc CS (AI), and MSc Software Engineering. With a decade of industry experience as a Chief Information Officer and Software Engineer, he bridges practical insights with academic research. Research Interests: Pervasive Computing, IoT/M2M, AI/ML, WiFi Sensing for Healthcare, Financial Machine Learning, Educational Technology Awards: Teaching Excellence Awards (2017/18), Fellow of the Higher Education Academy (FHEA), multiple Learning and Teaching Oscars (2016, 2017, 2018) His work spans Ubiquitous Computing and IoT , focusing on sensor networks and WiFi-based sensing for healthcare. In Artificial Intelligence , he applies ML to robotics, financial analytics, and educational innovation. Recent articles analyze Reinforcement Learning , Emotion Recognition , and WiFi Sensing applications. His teaching emphasizes student-centric learning, with over 100 supervised dissertations achieving distinctions. Collaborations include international conferences and interdisciplinary research in smart environments and adaptive systems.

• Data Management
• Digital Preservation
• Machine Learning
• +4 more

Andreas Rauber is an Associate Professor in the Department of Data Science at Technical University of Vienna. He serves as Curriculum Coordinator for Bachelor and Master programs in Business Informatics and Data Science, and chairs the Curriculum Commission for Business Informatics. His research focuses on Information Systems Engineering, Logic and Computation, and Visual Computing, addressing challenges in data management, digital preservation, and reproducibility in e-science. He leads projects like OS Trails and FAIR-AI, emphasizing FAIR principles and trustworthy research infrastructures. Rauber has contributed to over 150 publications, including works on data citation frameworks, adversarial ML defenses, and reproducibility in IR. His work bridges technical innovation with policy, exemplified through roles in the EOSC Support Office Austria and RDA Austria initiatives. Key projects include establishing FAIR data practices across universities and advancing digital preservation through repositories like DBRepo. He coordinates international collaborations, such as the EU-funded EOSC-Life and EGI Advanced Computing projects. His teaching spans courses in machine learning, information retrieval, and research methods, fostering next-generation data scientists.

Haiyang XueView profile

Assistant Professor

• Cryptography
• Post-quantum cryptography
• Threshold cryptography
• +5 more

Affiliations Full-time Assistant Professor of Computer Science at the School of Computing and Information Systems (SCIS) , Singapore Management University (SMU). Research focuses on cryptography, post-quantum systems, and secure protocols. Previously affiliated with PolyU for select teaching and collaborations. Education PhD in Computer Science, Chinese Academy of Sciences (2015). Research Interests Specializes in advanced cryptographic techniques including: Post-Quantum Cryptography (e.g., lattice-based systems) Threshold Cryptography (e.g., secure distributed ECDSA) Zero-Knowledge Proofs and Privacy-Preserving Technologies Authenticated Key Exchange (AKE) protocols Efficient implementations of cryptographic primitives (e.g., Kyber, NewHope) Notable Awards First Prize (LAC.PKE) and Second Prize (SIAKE, LAC.KEX) in Chinese Post-Quantum Cryptography Competition (2020) Best Paper Awards at IWSEC 2015 and ProvSec 2014 Advising & Collaborations Advises PhD students JIANG Bowen and WANG Jiaheng at SMU. Collaborates with researchers such as Guofeng Tang (post-doc) and international teams. Active in organizing conferences (e.g., CCS, ProvSec) and contributes to open-source projects like the Preprocess-then-NTT library. Labs & Teams Leads research initiatives at SMU focused on cryptographic protocol design and implementation. Collaborates with PolyU on advanced security projects.