Find Academic Supervisors

• AI-enabled communications
• Green and energy-efficient communications
• Online optimization and machine learning
• +6 more

E. Veronica Belmega is a Full Professor at ESIEE Paris (Université Gustave Eiffel) and a researcher at the LIGM laboratory in Marne-la-Vallée, France. Previously, she served as an Associate Professor at ENSEA graduate school and Deputy Director of the ETIS laboratory in Cergy. She holds an Engineer Degree from the University Politehnica of Bucharest, M.Sc. and Ph.D. from Université Paris-Sud 11, and an HDR habilitation from Université de Cergy-Pontoise. Her research focuses on AI-driven communication systems, energy efficiency, online optimization, and cyber-physical security, with a strong emphasis on applications in smart grids and IoT. Her work spans securing wireless communications against adversarial attacks, optimizing resource allocation in cognitive radio networks, and leveraging machine learning for GNSS localization and MIMO systems. Notable contributions include game-theoretic frameworks for PMU deployment and energy-efficient NOMA systems. Belmega has received prestigious awards such as the 2021 CY Alliance Award and the L’Oréal-UNESCO fellowship, and serves as an Area Editor for IEEE Trans. on Machine Learning in Communications and Networking. Current projects include a CEA LETI postdoc position on AI localization and a PEPR 5G project. She actively contributes to special issues like the EURASIP JASP on sustainable wireless communications. Belmega’s advising includes PhD student S. Maleki, co-author of her 2024 IEEE SmartGridComm Best Paper Award-winning work.

• Biomimetic Architecture
• Adaptive Building Envelopes
• Space Architecture
• +10 more

Valentino Manni is an Associate Professor at the Department of Architecture and Design, Polytechnic University of Turin, where he conducts research in technological and environmental design of architecture. He is a member of the Interdepartmental Center Ec-L - Energy Center Lab and actively contributes to PhD programs in Technological Innovation for the Built Environment. His teaching includes core courses such as 'Culture and Fundamentals of Architectural Technology' across multiple academic years and specialized workshops on dry-layered construction technologies. Academic Rank: Associate Professor Institution: Polytechnic University of Turin Department: Department of Architecture and Design (DAD) Email: valentino.manni@polito.it Phone: +39 0110904317 His research centers on sustainable and innovative architectural systems, with a focus on biomimetic design , adaptive building envelopes , and space architecture for lunar and Martian settlements. He investigates the use of agri-food and textile waste to develop thermo-acoustic insulation panels, aligning with circular economy principles. His work intersects with key sustainability goals, particularly SDG 11 (Sustainable Cities) and SDG 13 (Climate Action) , and is supported by commercial research contracts and interdisciplinary collaborations. The recent publication trends highlight a dual focus: advancing sustainable building technologies on Earth and pioneering modular, resilient habitat designs for space exploration. His work frequently appears in international conferences such as the International Astronautical Congress and in journals like Sustainability and AGATHÓN , demonstrating a strong integration of environmental, technological, and architectural innovation. Scientific Awards: No formal awards listed in the provided text. Manni supervises PhD student Luca Saverio Valzano , whose thesis explores biomimetic approaches to climate-adaptive building envelopes. His research projects include a 2024–2029 Memorandum of Understanding with the Poroton Italia Consortium and prior roles as Scientific Manager for urban placemaking and environmental certification initiatives. He leads the LaSTIn Laboratory of Innovative Technological Systems, fostering applied research in sustainable construction and smart building technologies. Laboratories and Teams: LaSTIn – Laboratory of Innovative Technological Systems (DAD) Member of research group on Poroton Italia Consortium project (2024–2029) Scientific Manager for Corso Farini urban redevelopment (2023)

• Telecommunications
• Wireless Sensor Networks
• Air Quality Monitoring
• +7 more

Alexandre Manuel de Castro Passos de Almeida is an Assistant Professor in the Department of Information Science and Technology at the University Institute of Lisbon (ISCTE-IUL), where he also contributes to the School of Technology and Architecture. He is an Associate Researcher at the Institute of Telecommunications - IUL, actively involved in the Radio Systems Group, focusing on telecommunications and sensor-based environmental monitoring. PhD in Telecommunications, ISCTE-IUL, 2012 His research interests span telecommunications, wireless sensor networks, air quality monitoring, computer architecture, and robotics. He has led and contributed to innovative projects such as ExpoLis, which uses mobile sensor networks on public buses to map urban air pollution. His work bridges engineering and environmental science, aiming to influence urban policy and public health through real-time data systems. The most recent publications highlight a strong trend toward deploying low-cost, mobile sensor networks for environmental monitoring, particularly in urban settings. His work integrates computer systems, signal processing, and sustainable technology, with applications in smart cities, public health, and robotics. Topics like air quality mapping, energy harvesting, and noise-aware robot navigation reflect a multidisciplinary approach to solving real-world problems. He has advised seven Master’s students at ISCTE-IUL, guiding research in sensor networks, air pollution, database performance, robotic navigation, and personal photography assistants. While no specific scientific awards are listed, his contributions to funded research projects and consistent scholarly output indicate recognition in his field. He has held leadership roles in academic governance, including Vice President of the Pedagogical Council, underscoring his institutional engagement. His teaching portfolio includes core courses such as Fundamentals of Computer Architecture, Operating Systems, and Big Data Processing, delivered across multiple undergraduate and postgraduate programs. He is involved in research projects that combine academic innovation with practical urban applications, particularly through the deployment of scalable, open-source environmental sensing systems.

Kevin GaryView profile

Associate Professor

• Software Architecture and Design
• Open Source Software
• Agile Methods
• +3 more

Kevin Gary is an Associate Professor in the School of Computing and Augmented Intelligence (SCAI) within the Ira A. Fulton Schools of Engineering at Arizona State University (ASU). He joined ASU in 2004 after prior industry experience and faculty work at the Catholic University of America. His research focuses on software agility, open source software, and applications in healthcare and e-learning. He has contributed to mHealth platforms addressing pediatric chronic conditions and adaptive e-learning systems. Education: Ph.D. in Computer Science from Arizona State University (1999). Research Interests: Software Architecture, Agile Methods, Open Source Software, Healthcare Informatics, and Educational Technology. His recent work explores agile impact on regression testing and lean metrics in open source software. He has developed mobile health apps for asthma, epilepsy, and anxiety, leveraging agile principles and AI. Teaching & Innovation: Created the Software Enterprise program, an industry-aligned pedagogy integrated into ASU’s software engineering curriculum. This initiative earned the President’s Award for Innovation in 2011. He has taught courses in software engineering, web applications, and secure software systems. Grants & Projects: Led projects funded by NSF, industry partners (e.g., UNICON, GEORGETOWN UNIV MED CTR), and foundations (Children’s National Medical). Notable projects include the Image-Guided Surgical Toolkit and the ATIC-funded Software Enterprise pedagogy model. Service: Reviewed for journals/conferences, served as Associate Chair of computing programs, and contributed to professional organizations (IEEE, ACM, ASEE).

• Real-Time Control Systems
• Cloud Computing
• Automation of Large-Scale Systems
• +7 more

Johan Eker is a Professor in Real-Time Control Systems at Lund University's Faculty of Engineering and a Principal Researcher in Cloud Technology at Ericsson Research. He holds a dual affiliation, actively contributing to both academic and industrial research in the domain of control systems and cloud automation. His research interests lie at the intersection of computer science and control theory, with a focus on the automation of large-scale software systems such as cloud services and telecommunications networks. He leverages machine learning and advanced control methodologies to develop intelligent, adaptive, and scalable systems. His work benefits from close collaboration with Ericsson Research, enabling access to real-world data and operational environments for validation and innovation. Johan Eker is involved in cutting-edge research areas including autonomous cloud systems, event-based control, and learning-based control architectures. His contributions support the evolution of resilient, efficient, and self-managing infrastructures in modern computing and networking environments. He is actively engaged in research collaboration between academia and industry, bridging theoretical advancements with practical deployment. His work is supported through partnerships with Ericsson, allowing for real-world testing and implementation of control solutions in cloud and telecom systems. Johan Eker is affiliated with the Department of Control Engineering at Lund University, where his expertise contributes to education and research in systems, control, and real-time computing. He plays a key role in advancing the integration of control theory into modern software and networked systems.

Stephanie RennaneView profile

Professor

• Disability Policy
• Labor Economics
• Health Economics
• +10 more

Stephanie Rennane is a Senior Economist at RAND and Professor of Policy Analysis at the RAND School of Public Policy. Her work bridges labor and health economics with a focus on disability policy, social insurance, and military compensation. She leads major research initiatives funded by the National Institute on Minority Health and Health Disparities (NIMHD) and contributes to critical policy evaluations for the Department of Defense and Veterans Affairs. Her research interests center on the economic and social impacts of disability programs, including Social Security Disability Insurance (SSDI), workers’ compensation, and Medicaid. She specializes in analyzing how these programs affect vulnerable populations, particularly children with special health care needs, low-SES families, and military personnel. Her work explores disparities in caregiver burden, insurance coverage, and access to workplace accommodations. The trends in her recent publications reveal a consistent focus on health and labor policy, with increasing attention to military compensation, food insecurity in military families, and systemic reform in disability evaluation. Her research combines rigorous econometric analysis with policy-relevant insights, often using administrative and survey data to assess program effectiveness and equity. Scientific Awards: None listed in the provided text. As a principal investigator on multiple NIMHD and DoD-related grants, Rennane plays a leading role in advising on public policy. Her research has informed congressional inquiries and federal program evaluations. She has not disclosed any formal students or advisees in the material provided. She is involved in research teams at RAND focused on disability policy, military health, and social safety nets. Her work often involves collaboration with interdisciplinary teams analyzing large-scale datasets and evaluating the cost and impact of public programs.

Shivam SaxenaView profile

Assistant Professor

• Smart Grids
• Energy Systems
• Distributed Control

Shivam Saxena is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of New Brunswick, located in Head Hall D65, Fredericton. His research focuses on smart grid technologies, including distributed energy resource integration, blockchain applications for energy trading, electric vehicle-grid interactions, and resilient microgrid design. This work addresses decarbonization challenges through technological and market innovations. Publications demonstrate a strong emphasis on real-world implementation, with field-tested solutions for V2X integration, blockchain-based transactive energy, and distributed control systems. Recent work explores novel applications in agricultural energy management and trust mechanisms for decentralized systems.

Declan HumphreysView profile

Lecturer

• Ethics in Artificial Intelligence
• Cyber Security
• Technological Ethics
• +4 more

Dr Declan Humphreys is a Lecturer in Cyber Security at the School of Science, Technology and Engineering at the University of the Sunshine Coast. He coordinates courses on ethics in cyber security, covering topics such as surveillance, disinformation, ethical design, and corporate responsibility. His research explores the intersection of artificial intelligence, ethics, and societal impact, with a focus on epistemic harms, AI replicas of deceased individuals, and algorithmic market risks. Research Focus: Ethics in AI development and deployment Cyber security risks of generative AI Philosophical implications of digital afterlife technologies Ethical challenges in reinforcement learning and sycophantic AI Critical analysis of pricing algorithms Scientific Awards: Associate Fellow of the Higher Education Academy (AFHEA) Professional Memberships: Australasian Association of Philosophy (AAP) Teaching Areas: Ethics in Cyber Security Artificial Intelligence Technological Ethics Program Coordination for Bachelor of Information and Communications Technology Research Projects: He supervises HDR and Honours students in projects related to ethics in AI, societal risks of disinformation, AI modeling for moral decisions, and cyber security protection for NGOs. Labs & Teams: Dr Humphreys contributes to the Healthy Ageing Research Cluster and participates in the MindSET-do project, which engages young students in technology and programming education.

Rafid Al-KhannakView profile

Associate Professor

• Cloud Computing
• Cybersecurity
• Distributed Systems
• +4 more

Dr. Rafid Al-Khannak is an Associate Professor in Computing at Buckinghamshire New University. He holds a PhD in Engineering and IT from the University of Bolton, completed in collaboration with Siemens AG. His research focuses on engineering and IT operational development, particularly in cloud computing, distributed systems, cybersecurity, and infrastructure automation. Al-Khannak maintains industry collaborations with Amazon and Siemens on cloud implementation and security projects. Key research areas include: Secure cloud migration frameworks using AWS hybrid models Infrastructure automation through CI/CD pipelines Penetration testing methodologies for cloud applications AI-enhanced education system transformation Healthcare application development for specialized needs

Travis W. KnightView profile

Professor

• Advanced nuclear fuels
• Spent fuel disposition
• Micro-reactor design
• +2 more

Travis W. Knight is Professor and Chair of Mechanical Engineering at the University of South Carolina's Molinaroli College of Engineering and Computing, where he also serves as Program Director for the Nuclear Engineering Graduate Program. His research focuses on advanced nuclear technologies including fuel development, reactor design, and spent fuel management. Education: Ph.D. Nuclear Engineering Science, University of Florida (2000) M.S. Nuclear Engineering Science, University of Florida (1995) B.S. Nuclear Engineering, University of Florida (1994) Dr. Knight's research interests span nuclear fuel development, reactor design innovations, and nuclear waste solutions. His work integrates computational modeling with experimental validation to advance nuclear energy applications in power generation, space propulsion, and defense systems. His publications demonstrate a consistent focus on nuclear fuel behavior, reactor safety, and waste management, with recent emphasis on experimental methods for fuel characterization and microreactor technologies. Major Awards: Fellow of the American Nuclear Society (2024) Breakthrough Leadership in Research Award (2020) Research Achievement Award (2018) Dr. Knight has supervised numerous doctoral and master's students in nuclear engineering, maintaining active research groups focused on fuel development and reactor safety. His lab facilities include capabilities for nuclear material synthesis, characterization, and computational modeling.

Ziqi SongView profile

Associate Professor

• Transportation network modeling
• Transportation Electrification
• Intelligent Transportation Systems
• +2 more

Ziqi Song is an Associate Professor in the Department of Civil, Structural and Environmental Engineering at the School of Engineering and Applied Sciences, University at Buffalo. Their research focuses on Transportation Engineering, with expertise in transportation network modeling, electrification, intelligent transportation systems, and traffic operations. Recent work includes zero-emission mobility strategies , electric bus charging infrastructure , autonomous vehicle lane deployment , and pedestrian group dynamics . Key themes involve optimizing transportation systems for electrification, integrating renewable energy into transit networks, and addressing equity in mobility through accessibility studies. Publications show strong emphasis on electric vehicle integration , urban transit optimization , and pedestrian behavior modeling . The work spans multi-disciplinary approaches combining transportation network analysis , renewable energy , and machine learning techniques.

Reza TouraniView profile

Assistant Professor

• Security and Privacy
• Internet of Things (IoT)
• Information-Centric Networking (ICN)
• +7 more

Reza Tourani is an Assistant Professor in the Department of Computer Science at Saint Louis University since Fall 2018. He earned his Ph.D. (2018) and M.S. (2012) in Computer Science from New Mexico State University, preceded by a B.S. in Computer Engineering from Islamic Azad University of Tehran (2008). His career includes prior work in the telecommunications industry in Iran. University: Saint Louis University School: School of Science and Engineering Department: Department of Computer Science Academic Rank: Assistant Professor Dr. Tourani’s research focuses on security and privacy in resource-constrained environments, including: Internet of Things (IoT) : Secure communication protocols and edge computing Information-Centric Networking (ICN) : Access control and request flooding mitigation Cyber-Physical Systems : Smart grid and UAV swarms Private Communication : Anonymity in distributed systems Networked Systems : DDoS defense and caching optimization His recent articles explore trends in: DDoS mitigation in Named Data Networking (PERSIA framework, 2020) Secure UAV swarm communications (2020) Attribute-based encryption for edge computing (APECS, 2021) Collaborative caching mechanisms (MuNCC, 2016) Smart grid data security (iCASM, 2020) Dr. Tourani has secured research grants from Saint Louis University and Intel Labs to advance projects on privacy-aware contact tracing and edge computing security . He actively mentors students in cybersecurity, IoT, and networked systems.

Giulia TotiView profile

Assistant Professor

• Computer Science Education
• Ethics in Data Science
• Machine Learning
• +3 more

Giulia Toti is an Assistant Professor of Teaching in the Department of Computer Science at the University of British Columbia (UBC), part of the Faculty of Science. Her work focuses on computer science education, equity in curriculum design, and fostering inclusive learning environments. She teaches courses such as Applied Machine Learning (CPSC 330), Fairness, Accountability, Transparency, and Ethics (FATE) in Data Science (DSCI 430), and Computers and Society (CPSC 430). Her research explores diversity initiatives in CS education, mastery learning frameworks, and equitable grading practices. Notable contributions include studies on pandemic-era remote teaching impacts and the development of Agora, a tool for enhancing large-classroom engagement. Toti has received UBC Faculty Teaching Awards for her pedagogical innovations. Her interdisciplinary work spans machine learning applications in industry and healthcare, including semantic search systems for clinical data (SemEHR) and predictive analytics for energy production. She is affiliated with the ACE Lab and actively contributes to curriculum reforms addressing DEI (Diversity, Equity, Inclusion) challenges in STEM education. Grants/Awards: Faculty Teaching Awards Labs/Teams: ACE Lab (Advancing Computing Education) Advising: No explicit advisee listings found, but contributes to pedagogical research impacting teaching practices.

Adam MooreView profile

Professor

• Geopolitics
• Political Violence
• Ethnic Conflict
• +5 more

Adam Moore is a Professor in the Department of Geography at UCLA's College of Social Sciences, with a PhD from the University of Wisconsin, Madison (2010). His research examines geopolitical dynamics of conflict and peacebuilding, with expertise in military labor, ethnic conflicts, and post-war reconstruction. Research interests focus on political violence, ethnic conflict dynamics, military contracting, and peacebuilding processes, particularly in Southeast European contexts. His investigations explore how militarization shapes foreign policy and spatial organization. Publications demonstrate sustained focus on conflict geography, military logistics, and peace studies, with recent work examining spatial dimensions of peacebuilding and decolonial geopolitics. Earlier scholarship analyzed military outsourcing and ethnic territoriality. Awards: Globe Book Award for Public Understanding of Geography Julian Minghi Distinguished Book Award Advises PhD students on topics including police violence, migration, and humanitarian infrastructure. Current students include Lindsey Rogers and Irma Losada Olmos.

• Machine Learning
• Reinforcement Learning
• Sample-efficient Generalization
• +5 more

Dr. Yangchen Pan is a Departmental Lecturer in Machine Learning at the University of Oxford's Department of Engineering Science. His research focuses on achieving sample-efficient generalization in machine learning, particularly in settings involving distribution shifts (e.g., adversarial learning, domain adaptation) and adaptive capabilities like offline/online reinforcement learning and continual learning. He has contributed to foundational work in reinforcement learning, robustness, and risk-averse optimization. Education and Academic Background: While specific degree details are not explicitly listed, his academic trajectory includes roles at leading institutions such as the University of Alberta (PhD, 2017-2020), where he collaborated with prominent researchers like Martha White and Amir-massoud Farahmand. Additional affiliations include teaching roles at the University of Waterloo, University of Toronto, and Indiana University. Research Interests: Pan's work spans machine learning theory and applications, with emphasis on scalable algorithms for complex decision-making systems. Key areas include adversarial robustness, offline reinforcement learning, and mitigating distribution shifts in real-world deployments. His recent contributions explore risk-aware policy optimization and novel approaches to sample efficiency. Professional Service: Pan serves on the program committees of top conferences like NeurIPS, ICML, and ICLR. He has reviewed for journals including the Journal of Machine Learning Research and Transactions on Machine Learning Research. Teaching: Pan teaches advanced courses in optimization, machine learning, and AI at the University of Oxford, including C25 Optimization and AI/ML with Python. He has also taught at the University of Alberta and Indiana University. Labs/Teams: While no specific lab name is mentioned, his research is closely tied to Oxford's Engineering Science department and collaborative projects with institutions like the ZERO Institute (as seen in event leadership at IMAD2025).