Steve Hailes is a Professor of Wireless Systems at the Department of Computer Science, University College London. He has served as Head of Department since 2019 and Deputy Head from 2005. His research spans wireless networks, computational trust, AI, and sensor systems for health, ecological, and environmental applications. Education: PhD and undergraduate degree from Cambridge University Appointment: Joined UCL in 1991 (postdoc), Lecturer in 1992 Research interests include: Trust and security in networked systems (co-founder of computational trust) Security of industrial control systems AI/ML applications in security and causal discovery Multi-agent reinforcement learning and moral behavior modeling Gas sensor fabrication and deployment for diverse applications Recent publications focus on feature selection for cybersecurity , moral alignment in LLM agents , trust-based consensus algorithms , and causal discovery using reinforcement learning . Collaborations include co-authors like Westphal, Musolesi, and Tennant. Applications span healthcare (dementia, JIA), ecology (endangered species in Botswana), and environmental monitoring (CO distribution, meth lab detection).
Professor Jun Zhang is a leading academic in cybersecurity at Swinburne University, Australia, where he directs the Cybersecurity Lab. He has been honored as Australia's top cybersecurity researcher and instrumental in establishing Swinburne as a globally recognized cybersecurity research institution. His work includes high-impact papers and multi-million-dollar R&D projects, culminating in awards like the 2021 'Top Cybersecurity Research Institution' accolade. As course director of the Bachelor of Cyber Security, he pioneered an industry-driven teaching model with Deloitte and CSIRO, significantly boosting course enrollment. His collaborations extend to Adobe's Curriculum Innovation Program and the Australian P-TECH initiative, promoting STEM education and cybersecurity awareness. He supervises doctoral candidates and leads grants focused on AI-driven cybersecurity, smart home security, and blockchain-based edge computing. His research spans vulnerability detection, GAN forensics, IoT security, and privacy preservation in OSNs. Research interests include cybersecurity fundamentals, data science applications, and distributed systems. Notable achievements include the PTFix framework for Java vulnerabilities, the IoTFuzz smart home testing system, and CTI mining methodologies. Awards reflect his mid-career research excellence and industry partnerships. His grants with CSIRO and defense organizations emphasize real-world impact, addressing challenges from malware detection to adversarial machine learning. The Cybersecurity Lab and collaborative projects like Artchain demonstrate his commitment to bridging academia and industry. Professional activities include supervising over 20 HDR students and securing grants totaling millions. His work on blockchain-based edge storage (CSEdge) and SDCCP congestion control highlights innovation in networking. Future directions include advancing AI for design collaboration with CSIRO and enhancing privacy in smart energy technologies. His contributions span technical, educational, and community outreach domains, positioning him as a pivotal figure in cybersecurity's evolution.
Dr. Kanchana Thilakarathna is a Senior Lecturer in Distributed Computing at the University of Sydney's School of Computer Science, and a member of the Centre for Distributed and High Performance Computing. They hold a PhD from the University of New South Wales (UNSW) and a B.Sc. Eng (Hons) from the University of Moratuwa, Sri Lanka. Prior to academia, they worked as a Research Scientist at CSIRO/Data61 and had industry experience as a Mobile Radio Network Engineer. Research Interests : Dr. Thilakarathna focuses on cybersecurity, privacy in mobile and IoT systems, mixed reality privacy, and distributed computing platforms. Their work emphasizes user-centric solutions like the Yalut social media app, which enables decentralized data sharing. Key themes include privacy-preserving techniques, edge computing, and secure federated learning frameworks. Recent Work : Recent articles (2023–2025) explore machine unlearning for large language models, federated learning security, and IoT network slicing using P4 programmability. Their work on synthetic video traffic generation (VideoTrain++) and drone detection (DronePrint) demonstrates cross-disciplinary innovation. Awards : Malcolm Chaikin Prize (2015), Meta Research Awards (2020/2022), and Heidelberg Laureate Fellowship (2019). Grants : ARC Research Hub for Future Digital Manufacturing (2024), NSW Defence Innovation Network Projects (2024/2021), and Facebook Research Awards (2022/2020). Students : Advising 4 current PhD students on topics like wireless trust establishment and machine unlearning. Labs/Teams : Part of the Centre for Distributed and High Performance Computing and Sydney Nano Institute.
Prof. Claudio J. Tessone is a Professor of Blockchain and Distributed Ledger Technologies at the Department of Informatics, University of Zurich. He serves as Head of the Blockchain and Distributed Ledger Technologies group, Chairman of the UZH Blockchain Center, and is incharge of the NetSci Society. His academic background includes a PhD in Physics (Complex Systems) and an Habilitation in Complex Socio-Economic Systems from ETH Zurich. Education: PhD in Physics (2006): Thesis on synchronization in stochastic systems, Universitat de les Illes Balears, Spain Habilitation (2015): Thesis on agent-based modeling of socio-economic systems, ETH Zurich Master in Physics (1999): Thesis on stochastic resonance, Instituto Balseiro, Argentina Research Interests: Prof. Tessone specializes in modeling complex socio-economic and socio-technical systems, with a focus on blockchain-based systems. His work explores crypto-economics, blockchain scalability, decentralized finance (DeFi), and the interplay between micro-level agent behavior and macro-level emergent properties. Notable areas include transaction network analysis in Bitcoin/Ethereum, consensus mechanisms (Proof-of-Stake/Work), and blockchain governance models. Publications Trends: Recent articles emphasize empirical blockchain analysis (e.g., Ethereum microvelocity, Bitcoin mesoscopic structure), DeFi arbitrage strategies, and privacy-preserving blockchain applications in healthcare. His work bridges theoretical agent-based models with real-world blockchain datasets, addressing both technical and socio-economic dimensions of distributed ledger technologies. Grants & Labs: Director of the UZH Summer School on Blockchain and Certificate of Advanced Studies program. Active in interdisciplinary collaborations through the URPP Social Networks (2015–2021) and ETH Zurich’s Systems Design group (2007–2014). Labs/Initiatives: Leads the UZH Blockchain Center, a hub for academic-industry research on blockchain applications in finance, governance, and digital transformation.
Srdjan Lukic is the Deputy Director of the FREEDM Systems Center and a Distinguished Professor in the Department of Electrical and Computer Engineering at North Carolina State University. His research focuses on power electronics, power systems, and electric vehicle infrastructure. He holds a Ph.D. in Electrical Engineering from the Illinois Institute of Technology (2007). His work emphasizes high-power converters, DC microgrids, and extreme fast charging (XFC) technologies for electric vehicles. Recent projects include the development of a 13.2 kV solid-state transformer for EV XFC stations and resilient distributed control frameworks for smart grids. He has contributed to wireless charging systems and modular medium-voltage fast chargers. Key Awards: University Faculty Scholars (2022) Grants: DOE-funded XFC projects, modular EV charging infrastructure Labs/Teams: FREEDM Systems Center, RIAPS control architecture development Publications highlight innovations in microgrid control, power electronics modeling, and privacy-preserving distributed systems. His work addresses grid resilience, cyber-physical integration, and high-efficiency energy conversion.
Dr Anandadeep Mandal is an Associate Professor in Finance and the Scotcoin Distinguished Chair of Digital Finance at the University of Birmingham , within the Birmingham Business School and the Department of Finance . He is the founding director of the MSc Financial Technology programme and the Programme Director for the MBA (Distance Learning), demonstrating significant leadership in academic program development. Education: PhD in Probability Distribution Fitting, Cranfield University (2016) MRes in Management Science, Cranfield University (2012) MSc in Finance and Investments, Durham University (2008) Bachelor’s in Electronics Engineering Research Interests: Dr Mandal’s interdisciplinary research lies at the intersection of mathematical modelling, artificial intelligence, finance, and digital innovation . His work focuses on AI-enabled investment strategies , blockchain for financial transparency , ESG performance measurement , and the development of the Sustainable Efficiency Index (SEI) . He also pioneers AI applications in digital education , including a patent-pending platform for automated grading of multi-modal student submissions using ensemble AI methods. Publication Trends: His recent scholarly output spans high-impact journals and conferences, reflecting a strong focus on digital finance , climate and social media analytics , cryptocurrency regulation , and AI in financial forecasting . His work combines advanced data science techniques with real-world policy and financial applications, particularly in sustainability and public health. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: Dr Mandal has secured over £2 million in research funding from sources including UKRI, UoB QR Funding, and industry partners. While specific students are not listed, his role as programme director and research leader suggests active mentorship. His research has direct policy impact through collaborations with the NHS Trusts , NIHR , and the UK Government . Labs, Teams, and Impact: Dr Mandal leads a research agenda that bridges academia and public policy. His work extends beyond the university through public engagement at science festivals, outreach for young learners, and expert contributions to UK Parliamentary consultations on AI, sustainability, and financial innovation. He is a key figure in advancing digital finance education and research at the University of Birmingham.
Aishwarya Ganesan is an Assistant Professor at the Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign. Her research focuses on distributed systems, storage systems, and fault tolerance mechanisms, with emphasis on high-performance computing and datacenter infrastructure. She leads projects addressing challenges in replicated storage, consensus protocols, and system resilience. Her work explores fault tolerance in disaggregated datacenters, log abstractions for low-latency applications, and novel replication strategies for modern storage systems. She has developed frameworks like LazyLog and IONIA to improve system efficiency and reliability. Her research also extends to automatic reliability testing for cluster management controllers and analyzing distributed storage vulnerabilities. Key contributions include demonstrating how redundancy alone does not guarantee fault tolerance, and proposing consistency-aware durability mechanisms for storage systems. She received the NSF CAREER Award in 2024 for her research on storage-aware fault tolerance. Her work spans 21 peer-reviewed publications, with notable contributions in conferences like SOSP, EuroSys, and FAST. Current projects investigate fault tolerance in emerging memory technologies and system recovery protocols for consensus-based storage.
Dustin Tingley is a Professor of Government at Harvard University and holds a joint appointment at the Harvard Kennedy School of Public Policy . He serves as Interim Vice Provost for Advances in Learning and directs the Data Science and Technology Group and the Harvard Initiative on Learning and Teaching . He earned a PhD in Politics from Princeton and a BA in political science and math from the University of Rochester. Key Roles : Deputy Vice Provost (past), Chair of Harvard's Standing Committee on Climate Education Research Focus : Climate change politics, data science, causal inference, and international political economy His recent work explores the political economy of climate transitions , public opinion on carbon policies , and machine learning applications in social sciences . He co-founded ABLConnect , a repository for active learning pedagogy, and organized conferences on causal mechanisms , teaching with AI , and equitable classrooms . Awards : Gladys M. Kammerer Award (2015) for co-authored book Sailing the Water’s Edge Notable Publications : Uncertain Futures: How to Unlock the Climate Impasse (2023, with Alex Gazmararian) The Political Economy of the Clean Energy Transition (2025)
Stephanie Gil is an Assistant Professor of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences. Her research focuses on artificial intelligence, robotics, and distributed systems, particularly addressing challenges in multi-agent coordination, resilience to adversarial attacks, and wireless communication for autonomous systems. She leads the REACT Lab, advancing research in resilient multi-robot networks and cyber-physical systems. Her work integrates machine learning, control theory, and wireless sensing to solve problems such as whale tracking via autonomous robots, proactive multi-robot routing, and decentralized exploration without explicit information exchange. She has received prestigious awards, including the DARPA Young Faculty Award (2024) and the Amazon Research Award (2021). Key research areas include resilient distributed optimization, trust-centered coordination in multi-agent systems, and leveraging wireless signals (e.g., WiFi-CSI) for sensing and bearing estimation. Her contributions span both theoretical frameworks and practical implementations, with a focus on real-world applications like autonomous rideshare routing and environmental monitoring. Dr. Gil’s research also explores trust and cybersecurity in dynamic networks, with publications on crowd vetting, malicious robot detection, and adaptive communication strategies. She collaborates on interdisciplinary projects, such as Project CETI, combining AI and robotics for ecological studies.
Giancarlo Ferrari Trecate is an Adjunct Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) , affiliated with the School of Engineering and the SCI-STI-GFT department. He is also involved in teaching and research through the STI-SGM and EDRS-ENS programs. Research Interests : Automatic control, state estimation, system identification, machine learning, distributed control, hybrid systems, microgrids, biochemical networks, voltage and frequency stabilization in AC/DC microgrids. Publications Trends : His recent work focuses on integrating Neural ODEs and Hamiltonian structures for stable control systems, regret minimization in distributed control, and robust state estimation under uncertainty. Applications include autonomous mobility-on-demand , power grid optimization , and secure microgrid control against cyber-attacks. Scientific Awards : No specific awards mentioned in the provided data. Teaching & Advising : He supervises PhD students in mechanical engineering and teaches courses on Multivariable control and Networked control systems . His lab, DECODE , specializes in Dependable Control and Decision systems.
Emmett Witchel is a Professor of Computer Science at the University of Texas at Austin , with research spanning computer architecture, systems, networking, security, and privacy . His work focuses on low-level systems optimization and secure concurrent execution. Research Interests: Concurrent systems, secure execution environments, GPU integration, distributed systems. Teaching: CS 380L (Advanced Operating Systems), CS 371M (Mobile Computing). Scientific Awards: Runner-up Best Paper, ASPLOS 2013 Runner-up Award for Outstanding Research, USENIX Symposium 2012 IEEE Micro Top Pick Award 2007 ACM Honorable Mention 2004 George M. Sprowls Award, MIT EECS 2004 Recent Publications demonstrate leadership in CXL pod databases ( Tigon ), stateful serverless computing ( Boki ), SmartNIC-accelerated file systems ( LineFS ), and GPU security ( Telekine ). His work bridges hardware-software co-design and practical systems implementation.
Karl Henrik Johansson is a Professor at the School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology in Stockholm, Sweden, where he also serves as the Founding Director of Digital Futures. He is a Fellow of both IEEE and the Royal Swedish Academy of Engineering Sciences, and has held leadership positions including Immediate Past President of the European Control Association and IEEE Control Systems Society Vice President Diversity, Outreach & Development. Dr. Johansson earned his MSc in Electrical Engineering and PhD in Automatic Control from Lund University. His academic journey includes visiting positions at prestigious institutions such as UC Berkeley, Caltech, and NTU. His research focuses on networked control systems and cyber-physical systems with applications in transportation, energy, and automation networks. His work investigates fundamental challenges in connecting physical world systems through communication networks, exploring how wireless communication and sensor technology can enhance system robustness, reliability, energy efficiency, and safety. Current research directions include security of cyber-physical systems, distributed optimization, multi-agent systems, and applications to intelligent transportation and energy networks. Analysis of his recent publications reveals a strong focus on distributed optimization algorithms, secure networked control, multi-agent systems, and applications to transportation and energy networks. His work increasingly integrates machine learning techniques with traditional control theory, addressing challenges in privacy-preserving distributed computation, resilient state estimation, and resource allocation in complex networked systems. IEEE Control Systems Society Hendrik W. Bode Lecture Prize (2024) Swedish Research Council Distinguished Professor (2018-2027) Wallenberg Scholar (2009-2026) IFAC Young Author Prize IEEE CSS Distinguished Lecturer (2017-2019) IFAC Outstanding Service Award IEEE Fellow Dr. Johansson has supervised over 100 postdocs and PhD students, with many now holding prominent positions at institutions worldwide. His research has been supported by significant grants including the Swedish Research Council Distinguished Professor Grant (2018-2027), multiple Wallenberg Foundation grants, and numerous EU and national research projects. He has directed major research centers including ACCESS Linnaeus Centre (2009-2016) and Strategic Research Area ICT TNG (2013-2020). His research group operates within the Digital Futures initiative and maintains strong connections with industry partners through projects like the Integrated Transport Research Lab (supported by Scania and Ericsson) and Smart Mobility Lab. The group actively collaborates with international institutions and participates in major EU-funded projects addressing challenges in cyber-physical systems, transportation, and energy networks.
David Basin is a Full Professor at the Department of Computer Science, ETH Zurich, and heads the Information Security Group. He has held academic positions since 2003, including roles at the University of Freiburg (1997–2002) and the Max-Planck-Institut für Informatik (1992–1997). His research focuses on Information Security, including methods and tools for secure systems, formal verification, and cryptographic protocols. He is Editor-in-Chief of the ACM Transactions on Privacy and Security and Springer's Information Security and Cryptography book series. Basin founded the Zurich Information Security Center (ZISC) in 2003 and led it until 2011. Education: B.Sc. in Mathematics (Reed College, 1984), Ph.D. (Cornell University, 1989), and Habilitation (University of Saarbrücken, 1996). Research interests span formal methods for security protocol verification, privacy-preserving systems, and cryptographic implementations. He has contributed to foundational work on security protocols, including the Tamarin verification framework. His work addresses real-world systems like payment protocols (EMV), DNS security, and database isolation guarantees. Awards: ACM Fellow (2018) for contributions to Information Security and Formal Methods, IEEE Fellow. He has organized numerous conferences, including IEEE S&P, Euro S&P, and ACM CCS. Labs/Teams: Leads the Information Security Group at ETH Zurich and co-founded Anapaya Systems, a startup focused on network security solutions. His team develops tools like VeriMon (formally verified monitoring) and Tamarin for protocol analysis.
Tania Burchardt is an Associate Professor of Social Policy at the London School of Economics (LSE) , where she serves as Deputy Director of STICERD and Associate Director of CASE (Centre for Analysis of Social Exclusion). Her work bridges theoretical frameworks like the capability approach with empirical analyses of inequality , disability policy , and applied welfare policy . Key Research Areas : Theories of justice, inequality measurement, time poverty, and social care systems Leadership Roles : Co-led projects on multidimensional inequality, intergenerational exchanges, and child poverty Her recent work explores intra-household resource allocation , social care inequities , and public engagement in policymaking . She has collaborated with organizations like the Nuffield Foundation and Sense about Science to translate research into practice. Scientific Contributions span empirical studies on: Long-term care funding reforms (2015–2020) Disability-related income disparities Time poverty intersections with economic hardship Data-driven policy recommendations for Roma/Gypsy/Traveller communities Multidimensional child poverty frameworks
Ying Cai is an Associate Professor in the Department of Computer Science at Iowa State University, joining in 2003 after earning his Ph.D. in Computer Science from the University of Central Florida (2002). His research focuses on AI, machine learning, data science, cybersecurity, privacy protection, and database systems. He leads projects funded by the Air Force Research Laboratory, including work on authentication data structures for rank-aware queries, requiring U.S. citizenship and expertise in linear algebra/cryptography. Dr. Cai’s work spans cybersecurity (e.g., adversarial example defense, secure secret sharing), spatio-temporal systems (e.g., traffic risk prediction, check-in time modeling), and healthcare AI (e.g., cervical spine diagnosis with transformers). His publications emphasize practical applications of ML in privacy, security, and distributed systems. Professional roles include Associate Editor for Multimedia Tools and Applications (since 2009), Co-chair for COMPSAC TAIN/NCIW symposium (2014–2017), and TPC Chair for Mobilware 2010. His service includes contributions to INFOCOM, ICDCS, and MDM conferences. Current research opportunities exist for graduate students with strong programming/math skills, particularly in cryptography and linear algebra. He emphasizes interdisciplinary work, such as bridging AI with social sciences via large language models.
