Find Academic Supervisors

Miroslava KavgicView profile

Associate Professor

• Sustainable Building Engineering
• Carbon Capture Materials
• HVAC Systems Optimization
• +6 more

Miroslava Kavgic is an Associate Professor in the Department of Civil Engineering at the University of Ottawa. She holds a Ph.D. (United Kingdom), M.Sc. (United Kingdom), and B.Sc. (Serbia), and is a Professional Engineer (P.Eng.). Her research focuses on sustainable building engineering, carbon-negative materials, and energy-efficient design for remote communities. She leads the Centre for Indigenous Community Infrastructure at uOttawa, emphasizing culturally appropriate solutions. Education: Ph.D. in Environmental Design and Engineering (University College London, 2013) M.Sc. in Environmental Design and Engineering (University College London, 2006) B.Sc. in Mechanical Engineering (Serbia) Research Interests: Carbon capture building materials (e.g., hempcrete composites) Bioclimatic design strategies for net-zero buildings Urban energy modeling to decarbonize cities Renewable energy systems integration Advanced HVAC controls and energy efficiency Her recent publications (2021–2025) emphasize: Phase change material applications in building envelopes Machine learning for energy demand prediction Optimization algorithms like MEVO for building performance Hybrid renewable energy systems Labs/Teams: Active in the Centre for Indigenous Community Infrastructure, focusing on Northern communities' sustainable infrastructure. Collaborates with industry on building design innovations.

• AI Algorithms
• Economic Inequality
• Pricing Algorithms
• +3 more

Shunyuan Zhang is an Assistant Professor at Harvard Business School with research focusing on AI algorithms, economic inequality, and computer vision applications in business contexts. His work examines how algorithmic systems impact economic outcomes, particularly in sharing economy platforms like Airbnb. His research interests include AI algorithms, economic inequality, pricing algorithms, machine learning, computer vision, and the sharing economy. Zhang's work often combines technical computer vision approaches with economic analysis to understand platform dynamics. Zhang's recent publications demonstrate a strong focus on the intersection of AI, fairness, and economic outcomes. His work analyzes how algorithmic pricing affects racial disparities on platforms like Airbnb, and how visual content impacts demand in the sharing economy. His research employs sophisticated methodologies including deep learning, structural modeling, and causal inference. He has published in top journals and working paper series, with notable work including 'Can an AI Algorithm Mitigate Racial Economic Inequality? An Analysis in the Context of Airbnb' and 'What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features.' Zhang collaborates extensively with leading researchers at Carnegie Mellon University and University of Toronto, particularly on topics related to algorithmic fairness and platform economics. His work has significant implications for both academic understanding and practical policy recommendations regarding algorithmic systems in marketplace contexts.

Andrew M. OlneyView profile

Professor

• Natural Language Processing
• Intelligent Tutoring Systems
• Dialogue Systems
• +5 more

Andrew M. Olney is Professor in both the Institute for Intelligent Systems and Department of Psychology at the University of Memphis. His work bridges artificial intelligence, cognitive science, and education, with a primary focus on natural language interfaces for learning. His educational background includes a Ph.D. in Computer Science from the University of Memphis (2006), an M.S. in Evolutionary and Adaptive Systems from the University of Sussex (2001), and a B.A. in Linguistics with Cognitive Science from University College London (1998). Dr. Olney's research centers on intelligent tutoring systems and natural language processing applications in education. His specific interests include vector space models, dialogue systems, unsupervised grammar induction, and computational representations of meaning. He has made significant contributions to conversational intelligent tutoring systems and task-oriented natural language interfaces, with particular emphasis on dyadic interaction and engagement in learning contexts. Analysis of his recent publications reveals a consistent focus on leveraging AI for educational enhancement, particularly through automated content creation, question generation, and adaptive learning systems. His work spans multiple disciplines including computer science, cognitive science, linguistics, and education, demonstrating strong interdisciplinary integration. Scientific Awards and Recognition: Best Paper Award, Proceedings of Empowering Education with LLMs (2023) Associate Editor, International Journal of Artificial Intelligence in Education (Impact Factor 4.9) Dr. Olney has been actively involved in mentoring graduate students and securing research funding. He has served as Principal Investigator on $6M of federal grants within a total of $18M in federal grant funding. His service includes former editorship of the Journal of Educational Data Mining (2017-2022) and former leadership roles as Director/Associate Director of the Institute for Intelligent Systems (2006-2017). He currently coordinates both the Cognitive Science Graduate Certificate and Undergraduate Minor in Cognitive Science at the University of Memphis. His BrainTrust project, funded by the NSF, addresses the knowledge engineering bottleneck for intelligent tutoring systems through innovative approaches to virtual student simulation and knowledge representation.

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.

• Supply Chain Management
• Modeling and Optimization
• Production and Service Systems Management
• +3 more

Prof. Şule Itır Satoğlu is a faculty member in the Department of Industrial Engineering at Istanbul Technical University, holding the rank of Professor since 2019. She has held multiple administrative roles, including Head of Department (2025–present), Vice Rector (2020–2024), and Vice Dean (2018–2020). Her research focuses on supply chain management, optimization, sustainable operations, and disaster response systems. She has a PhD in Industrial Engineering from Istanbul Technical University (2008), an MSc in Engineering Management (2002), and a BSc in Mechanical Engineering (2000). Her work emphasizes practical applications of optimization techniques in logistics, healthcare, and disaster management. Notable contributions include developing models for blood supply chains under uncertainty, UAV-based waste detection, and sustainable urban transport fleet electrification. She has collaborated on projects funded by public and private sectors, addressing issues like lean manufacturing integration with Industry 4.0 and RFID-enabled maintenance systems. Her publications span over two decades, with recent focus on multi-objective optimization in humanitarian logistics, smart waste collection systems, and energy-efficient drone surveillance. She is a member of the TMMOB Chamber of Mechanical Engineers and actively contributes to national technology initiatives through academic leadership roles.

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
• Machine Learning
• Software Architecture
• +4 more

Cagatay Catal is a Lecturer at the Information Technology Department of Wageningen University & Research in the Netherlands. Previously, he served as Associate Professor at Istanbul Kultur University's Department of Computer Engineering (2012–2017), including three years as Department Head (2014–2017). Prior to academia, he worked for 8 years at TÜBİTAK's Information Technologies Institute as Senior Researcher & Project Manager (2002–2012), contributing to large-scale software systems. He holds a BSc/MSc from Istanbul Technical University and a PhD from Yildiz Technical University, all in Computer Engineering. His research focuses on machine learning applications in software engineering, software quality assurance, testing methodologies, and architecture design. He actively reviews for funding bodies like the European Union's EUROSTARS program, Canada's Research Council, and Turkey's Research Council. Catal leads projects such as INREF Smart-In-Ag (SMART farming in Indonesia), VIRAL (ICT in agricultural education), and malware detection in software systems. His work bridges academic research with practical software development challenges in diverse sectors like healthcare and education.

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.

Bruno FruchardView profile

Researcher

• Human-Computer Interaction (HCI)
• Haptics
• Embodied Interaction
• +3 more

Bruno Fruchard is a Researcher at Inria in the Loki team in Lille, France. He previously held a postdoctoral position at the Human-Computer Interaction (HCI) Lab at Saarland University, Germany, and completed his PhD in Computer Science focused on HCI at Télécom Paris (formerly Télécom ParisTech). His research centers on adaptable interaction techniques, novel interfaces, and haptic systems, with a focus on embodied interaction and wearable technologies. Key areas of interest include designing haptic feedback systems (e.g., TactJam, Weirding Haptics), exploring microgestures for wearables (e.g., MicroPress, SoloFinger), and applying user-centered design to sports analytics (e.g., lead climbing performance tools with the French Federation of Climbing). His projects span prototyping tools for on-body interfaces (BodyStylus, Polysense), evaluating recall-based interaction techniques, and critical design explorations like Eyecam, which examines sensing device ethics. Collaborative haptic design frameworks (CollabJam) and empirical studies on user memorization and interaction efficiency are also central to his work.

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).

• 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.

Weihua ZhuangView profile

Professor

• Wireless Communications
• Networking Algorithms
• Internet of Things (IoT)
• +7 more

Dr. Weihua Zhuang is a University Professor and University Research Chair in the Department of Electrical and Computer Engineering at the University of Waterloo. She holds prestigious fellowships from IEEE, Royal Society of Canada, and other organizations. Her research focuses on future communication networks, including 6G, network virtualization, autonomous vehicles, and smart grids. She has led groundbreaking work on MAC protocols like VeMAC for vehicular networks and has contributed extensively to AI-driven network management. Education : Doctorate in Electrical Engineering, University of New Brunswick, Canada (1993) M.Sc. and B.Sc. in Electrical Engineering, Dalian Maritime University, China Research Interests : Dr. Zhuang's work spans wireless networking, IoT, autonomous systems, and smart infrastructure. She explores solutions for network architecture evolution, machine learning applications in communication systems, and service customization for dynamic environments. Her recent projects include digital twin-driven networks, cross-modal transmission strategies, and AI-native slicing for 6G. Awards : Women's Distinguished Career Award (IEEE VTS, 2021) R.A. Fessenden Award (IEEE Canada, 2021) Fellowships from IEEE, RSC, CAE, EIC Grants & Professional Activities : She led the Tier I Canada Research Chair in Wireless Communication Networks (2010–2024) and has held roles such as IEEE VTS President (2023–2024). Her grants include the NSERC Discovery Accelerator Supplements and PREA awards. She edits journals like IEEE Transactions on Vehicular Technology and co-chairs major conferences. Labs & Teams : Her research group focuses on network architecture, AI-driven protocols, and vehicular communication. Collaborations include projects on 6G, satellite-terrestrial integration, and edge computing for autonomous systems.

Liu DerongView profile

Professor

• Neural Networks
• Reinforcement Learning
• Intelligent Control
• +5 more

Liu Derong is a distinguished academic holding the position of Chair Professor at Southern University of Science and Technology (Shenzhen, China) since 2022. He is also a Full Professor at the University of Illinois at Chicago (UIC) since 2006. His academic journey includes roles as Professor at Guangdong University of Technology (2017–2022) and the Chinese Academy of Sciences' Institute of Automation (2008–2016). He earned his Ph.D. in Electrical Engineering from the University of Notre Dame (1994), M.S. from the Chinese Academy of Sciences (1987), and B.S. from Nanjing University of Science and Technology (1982). His research focuses on neural networks, reinforcement learning, intelligent control, and adaptive dynamic programming. He has authored 19 books and 260+ journal papers, contributing significantly to computational intelligence and control systems. Notable works include Adaptive Dynamic Programming with Applications in Optimal Control (2017) and co-editing volumes like Frontiers of Intelligent Control and Information Processing (2014). Liu Derong has held leadership roles in professional societies, including Editor-in-Chief of Artificial Intelligence Review , Deputy Editor-in-Chief of the IEEE/CAA Journal of Automatica Sinica , and President of the Asia Pacific Neural Network Society (2018). He has organized major conferences such as the IEEE World Congress on Computational Intelligence (2014) and received prestigious awards like the Dennis Gabor Award (2018) and membership in Academia Europaea (2021). His contributions span theoretical advancements and practical applications in control systems, with a focus on optimization, robotics, and energy systems. He has also served on editorial boards of leading journals and as a keynote speaker at 30+ international conferences.