Giuliano Casale is a Professor in the Department of Computing at Imperial College London, leading the Quality of Service Research Lab (QORE). His research focuses on performance assurance, resource management, and fault-tolerance in distributed systems. He teaches courses on Probability and Statistics and Scheduling and Resource Allocation at undergraduate and Master’s levels. Casale’s work spans cloud computing, edge AI, and machine learning applications in system modeling. Key contributions include methodologies for performance engineering, anomaly detection, and automated resource management in large-scale systems. He actively participates in international conferences, delivering keynote speeches on topics such as performance evaluation and AI-driven systems. His research integrates queueing theory, machine learning, and generative models to address challenges in distributed software systems. Casale also engages in service activities like PhD admissions tutoring and collaborates on projects involving resilience planning and cloud service optimization. His lab, QORE, emphasizes practical solutions for real-world distributed systems, including edge federations and serverless architectures. Casale’s work bridges theoretical performance analysis with industrial applications, contributing to advancements in both academia and industry.
Dr. Jonathan Buonocore is an Assistant Professor in Environmental Health at the Boston University School of Public Health and Core Faculty at the Institute for Global Sustainability (IGS). His research evaluates health impacts of energy systems, focusing on climate mitigation strategies' co-benefits, equity, and unintended consequences. He holds a Sc.D. and MS from Harvard School of Public Health and a BS from Clarkson University. Education: Sc.D., Environmental Science & Risk Management, Harvard School of Public Health MS, Environmental Health, Harvard School of Public Health BS, Environmental Science & Policy, Clarkson University Research Interests: Dr. Buonocore examines energy systems through integrated frameworks combining health impact assessment, risk modeling, and energy policy analysis. Key areas include: Health co-benefits of renewable energy expansion Air pollution consequences of fossil fuel infrastructure Environmental justice in energy transitions Geoengineering health risks Recent work analyzes electrification policies, methane leakage risks, and extreme climate interventions. Articles emphasize spatial equity in exposure to oil/gas development and transportation policies. Grants & Advising: His research is supported by grants focusing on energy-climate-health linkages. He advises on projects related to decarbonization pathways and environmental justice. Labs & Collaborations: Associated with IGS and prior work at Harvard's Center for Climate, Health, and Global Environment. Collaborates with environmental justice organizations on policy-relevant research.
Joe Geunes is a Professor and Associate Department Head for Graduate Affairs in the Department of Industrial & Systems Engineering at Texas A&M University, holding the Mike and Sugar Barnes Professorship. His research focuses on production planning, supply chain management, logistics, and operations optimization. He earned his Ph.D. in Business Administration (Management Science & Operations Research) and M.B.A. from The Pennsylvania State University in 1999 and 1993, respectively. Dr. Geunes has received notable accolades including Fellow of the Institute of Industrial Engineers (2015), Marilyn and L. David Black Faculty Fellow (2022), and Best Reviewer Award from Omega (2022). His work spans infrastructure network restoration, supply chain resilience, and optimization algorithms for logistics systems. Recent projects address railcar operations, distribution network fortification, and disaster response strategies. Education: Ph.D., Business Administration (Management Science & Operations Research), The Pennsylvania State University – 1999 M.B.A., The Pennsylvania State University – 1993 Awards: Fellow, Institute of Industrial Engineers – 2015 Marilyn and L. David Black Faculty Fellow – 2022 Best Reviewer Award, Omega – 2022 Best Application Paper, IISE – 2018 His research integrates mathematical modeling and computational methods to address real-world challenges in supply chain design, inventory management, and infrastructure resilience. Recent publications emphasize multi-modal logistics, robust optimization under uncertainty, and post-disaster network recovery strategies.
Bassam Bamieh is a Professor of Mechanical Engineering at the University of California, Santa Barbara (UCSB), with affiliate roles in Electrical and Computer Engineering and the Center for Control, Dynamical Systems and Computation (CCDC). His research focuses on control systems, dynamical systems, and their applications in fluid mechanics, quantum control, and network science. He holds fellowships from IEEE and IFAC and has received accolades such as the NSF Early Career Award and IEEE Distinguished Lecturer designation. Education: B.Sc. in Electrical Engineering and Physics from Valparaiso University (1983), M.Sc. and Ph.D. in Electrical and Computer Engineering from Rice University (1986, 1992). Formerly an Assistant Professor at the University of Illinois at Urbana-Champaign (1991–98). Research interests span robust and optimal control, distributed systems, shear flow turbulence, and thermoacoustic energy conversion. He has authored over 200 publications and pioneered work in spatially invariant systems and network controllability. His teaching includes courses on linear systems, vibrations, and control systems design. Awards include the IEEE Axelby Award (twice), Hugo Schuck Best Paper Award, and recognition for student research mentorship (e.g., Outstanding Student Paper Awards at CDC and IFAC NecSys22). His group collaborates across disciplines, integrating mathematical analysis with engineering applications.
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.
Hamed Badihi is an Assistant Professor in Automation Technology and Dependable Systems at Tampere University , part of the Faculty of Engineering and Natural Sciences. He leads the Dependability and Automation Research in Cyber-Physical Systems (DARES) Group within the Dependable Systems Cyber Laboratories . His research focuses on critical aspects of condition monitoring, fault-tolerant control, and attack-resilient control to advance sustainable, dependable cyber-physical systems. Research Interests include: Cybersecurity for industrial control systems Fault-tolerant control mechanisms Resilient control strategies for renewable energy systems Condition monitoring of wind turbines and microgrids Recent Contributions emphasize hybrid approaches combining machine learning and control theory for cyber-attack detection and system resilience in wind farms and microgrids. His work addresses challenges like real-time fault diagnosis and adaptive control under adversarial or environmental perturbations. Awards & Roles : Senior Member of IEEE, editor for International Transactions on Electrical Energy Systems , Advances in Fuzzy Systems , and Processes journals. Active in EU projects like StreamSTEP . Labs & Teams : Directs the DARES Group, collaborating on initiatives like the Dependable Systems Cyber Laboratories to pioneer innovations in cyber-physical system dependability.
Dr. Nikhil Chopra is a Professor in the Department of Mechanical Engineering at the University of Maryland, College Park, with affiliate appointments in Electrical and Computer Engineering. He earned his Bachelor of Technology from IIT Kharagpur (2001) and his M.S. and Ph.D. from University of Illinois at Urbana-Champaign (2003, 2006). As Director of Undergraduate Studies, he leads academic programs while advancing research in systems, control, and robotics. His work focuses on robotic system control, soft robotics, teleoperation, and machine learning integration. Research highlights include co-authoring the book *Passivity-Based Control and Estimation in Networked Robotics* (2015), co-chairing the IEEE Technical Committee on Telerobotics, and serving as Associate Editor for *Automatica* and related journals. His lab, the Semi-Autonomous Systems Lab, explores control-theoretic frameworks for robotics and optimization, collaborating with institutions like Sintef and IEEE RAS Technical Committees. Key projects involve underwater robotics navigation, cyber-physical system privacy, and distributed optimization algorithms. His team has exhibited strong presence at ICRA and IROS conferences, including awards for work on 3D water quality mapping and control frameworks. Current initiatives include robotic parasitic arrays for communication enhancement and secure bilateral teleoperation systems. Lab: Semi-Autonomous Systems Lab (SAS Lab) Affiliations: Institute for Systems Research, Maryland Robotics Center Recent Funding: NSF grants, industry partnerships
Chen Binbin is an Associate Professor and Associate Head of Pillar (Innovation and Enterprise) in the Information Systems Technology and Design (ISTD) pillar at Singapore University of Technology and Design (SUTD). He serves as Deputy Director for the Future Communications Research and Development Programme (FCP), Singapore. Previously, he was a Principal Research Scientist at the Advanced Digital Sciences Center (now Illinois ARCS), affiliated with the University of Illinois. Education: PhD in Computer Science from National University of Singapore, and Bachelor's from Peking University. Research focuses on wireless networking, distributed systems, and cyber security for critical infrastructures like smart grids and industrial control systems. His work addresses secure communications, intrusion detection, and resilience against cyber-physical threats. Notable contributions include error-estimating coding, provenance verification in ICS, and AI-driven network security solutions. Key awards include the 2010 ACM SIGCOMM Best Paper Award for error-estimating coding research. His grants span agencies like Singapore's National Research Foundation (NRF), Cyber Security Agency (CSA), and Energy Market Authority (EMA). He leads projects on secure smart grid communication, industrial control system defense, and AI-enhanced cybersecurity tools. Technical leadership involves developing frameworks like CyberSAGE for security assessment and CMD for IoT malware detection. Active in collaborations with industry and government, his work bridges theory and practice in securing critical infrastructure systems.
Camilo Mora is a Professor in the Department of Geography at the University of Hawaii at Manoa, where he maintains an active research laboratory and teaches courses on environmental issues, biogeography, and data analysis. His academic journey began with a BSc in Marine Biology from Universidad del Valle in Colombia (1999), followed by a PhD in Biology from the University of Windsor, Canada (2005). He completed postdoctoral fellowships at the University of Auckland (2005), Scripps Institution of Oceanography (2006-2008), and Dalhousie University (2008-2010). BSc, Marine Biology, Universidad del Valle, Colombia (1999) PhD, Biology, University of Windsor, Canada (2005) Postdoctoral Fellow, University of Auckland (2005) Postdoctoral Fellow, Scripps Institution of Oceanography (2006-2008) Postdoctoral Fellow, Dalhousie University (2008-2010) Mora's research spans interconnected lines focused on understanding biodiversity patterns and their modification by human activities, with particular emphasis on climate change impacts. His lab specializes in big data analytics applied to diverse environmental challenges including heatwaves, disease transmission, marine ecosystems, and even unconventional topics like Bitcoin's environmental footprint. The Mora Lab operates on a 'divide and conquer' approach to tackle large research questions by breaking data gathering into individual parts that can be concatenated into central databases. Mora has received the CSS Excellence in Research award (2014) for his significant contributions to environmental science. His influential publications include groundbreaking work on the global risk of deadly heat (2017), the projected timing of climate departure from historical variability (2013), and the finding that over half of known human pathogenic diseases can be aggravated by climate change (2022). CSS Excellence in Research (2014) Highly cited publications in Nature and Nature Climate Change Research featured in major international media outlets Development of innovative research methodologies for large-scale analyses Mora leads an active research group that engages students in the full scientific process from idea generation to publication. His approach to mentoring involves creating yearly classes where graduate students, professors, and international advisors collaborate to tackle significant research questions, with papers typically completed within a single semester. His Carbon Neutrality Challenge project, spearheaded by his daughter Asryelle Mora, provides a practical mechanism for individuals to offset carbon emissions through tree planting. The Mora Lab maintains a distinctive approach to environmental research, working on seemingly diverse topics from reef fishes to Bitcoin, united by their reliance on big data analytics. This interdisciplinary methodology has produced impactful research across multiple domains of environmental science and climate change impacts, establishing Mora as a significant contributor to our understanding of humanity's environmental challenges.
Denis Fischbacher-Smith is a Professor and Research Chair in Risk and Resilience at the University of Glasgow's Adam Smith Business School, within the College of Social Sciences. Previously, he held roles at the University of Liverpool, including founding director of its Management School, and held academic positions at Sheffield, Durham, and John Moores Universities. He also served as a visiting professor at Kobe University (Japan), San Diego State University (USA), and Innsbruck University (Austria). His academic journey includes degrees from Manchester, Glasgow, St Andrews, and others, culminating in a DLitt in Crisis Management. He holds over a dozen professional certifications, including Fellowships from the Academy of Social Sciences and Higher Education Academy, and Chartered statuses in Geography, Security, and Management. Research focuses on risk management, crisis response, and organizational resilience, with 112+ publications spanning three decades. Key areas include evacuation strategies, crisis team performance, emergency planning limitations, and organizational vulnerability. He advises governments (e.g., UK Department of Health, Lesotho), corporations, and regulatory bodies, and has led projects on healthcare safety and terrorism preparedness. Publications emphasize interdisciplinary approaches to risk, such as using comics in education and analyzing post-EU expansion crises. Awards recognize his contributions to public health policy, emergency planning, and security practices. He chairs HARM Consulting and serves on boards of NHS trusts and sports organizations.
Richard Silberglitt is a Senior Physical Scientist at RAND and Professor of Policy Analysis at the RAND School of Public Policy, where he conducts interdisciplinary research at the nexus of science, technology, and public policy. With over 50 years of experience across academia, government, and industry, he is a leading expert in technology foresight, energy systems, and R&D portfolio management. His research focuses on emerging technologies , science and innovation policy , energy security , and nanotechnology . He has developed influential methodologies such as an energy scenario analysis framework and the PortMan portfolio management system, both widely applied in U.S. and international contexts. His work supports strategic planning in defense, public safety, and economic development. His recent publications reflect a strong trend toward technology foresight , critical materials supply chains , quantum technology assessment , and public sector innovation . These works often employ scenario planning, Delphi methods, and data-driven analytics to inform high-stakes policy decisions. Member, American Physical Society Member, Materials Research Society Member, American Ceramic Society As a subject matter expert, Silberglitt has advised the United Nations, U.S. Department of Defense, National Security Agency, and multiple federal agencies. He has chaired the International Advisory Board of the APEC Center for Technology Foresight and delivered testimony to U.S. Congressional committees on critical materials and technology policy. His research has been supported by grants and contracts from the U.S. Army, Navy, CDC, and National Institute of Justice. He has led major initiatives on law enforcement technology, transportation safety ( The Road to Zero ), and international technology foresight. His work often involves collaborative teams and cross-sector partnerships to address complex technological and policy challenges.
Professor Xiaodong Liu is a faculty member at Edinburgh Napier University, affiliated with the School of Computing, Engineering and the Built Environment . His research spans Internet of Things , Edge Computing , Artificial Intelligence , and Cybersecurity , with a focus on decentralized systems and data-driven decision-making. Research Themes : IoT orchestration, federated learning, smart city infrastructure, building maintenance optimization, and automotive cybersecurity. Current Projects : Leading Swarmchestrate (EU-funded), Long-range Perceptive Autonomous Vehicles (Royal Society), and Met-Bot for Disaster Surveillance (Royal Society). His recent publications emphasize privacy-preserving edge learning , semantic IoT data validation , and deep learning for weather prediction . As a supervisor, he has guided PhD students in areas like federated learning, smart building systems, and IoT security. Collaborations include partnerships with institutions in Scotland, China, and Italy, alongside funding from European Commission , Royal Society , and Scottish Funding Council . He contributes to international conferences and journals, with notable work in IEEE Transactions , ACM TAAS , and MDPI publications.
Dr. Yanjun Zhang is an Honorary Research Fellow at the School of Electrical Engineering and Computer Science, The University of Queensland. His research focuses on privacy-preserving technologies, federated learning, cybersecurity in IoT systems, and machine learning security. He holds a PhD in Privacy-Preserving Sharing for Genome-Wide Analysis from The University of Queensland (2021). Education: PhD in Information Technology, School of Information Technology and Electrical Engineering, The University of Queensland (2021) Research Interests: Designing secure collaborative machine learning frameworks Defending against adversarial attacks in cyber-physical systems Privacy preservation in distributed genomic and medical data analysis Compliance and ethics in virtual personal assistant applications Key Contributions: Developed privacy-preserving federated learning frameworks (AgrAmplifier, PrivColl) Conducted foundational studies on evasion attacks in IoT systems Created datasets for analyzing malicious browser extensions and Alexa skills Labs/Teams: Active contributor to UQ Cyber initiatives, including the 2021-2022 Seed Funding project on federated deep learning for medical imaging.
Prof. Nan Yang is a Professor at the Australian National University's ANU College of Engineering, Computing and Cybernetics, leading the Information and Signal Processing Cluster and the Emerging Communications Laboratory. He holds a PhD in Electronic Engineering from Beijing Institute of Technology (2011) and has held postdoctoral roles at CSIRO and UNSW before joining ANU in 2014. His research focuses on terahertz communications, ultra-reliable low-latency systems, and cyber-physical security, with notable contributions to molecular communications and massive MIMO systems. Education: B.S. in Electronics, China Agricultural University (2005) M.S. in Electronic Engineering, Beijing Institute of Technology (2007) Ph.D. in Electronic Engineering, Beijing Institute of Technology (2011) Key Roles: Associate Dean for Higher Degree Research (2019–2021) Editorial Board Member of IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, IEEE Communications Letters, and others Organizer of workshops at IEEE ICC, GlobeCOM, and ACM MobiCOM His research interests span terahertz communication systems, cyber-physical security, and intelligent communications. Recent work emphasizes secure beamforming, UAV-assisted networks, and molecular communication protocols. He has authored over 180 publications and secured grants totaling millions in funding for projects like the Ultra-Fast and Secure Terahertz Communications for 6G Wireless Systems (2023–2026). Awards & Recognition: IEEE ComSoc Distinguished Lecturer (2023–2024) Best Paper Awards at IEEE ICC 2024, GlobeCOM 2022, and VTC Spring 2013 Exemplary Editor/Reviewer Awards from IEEE Transactions Grants & Projects: iLAuNCH: SWIFT-iLAuNCH Project A (SC-9) (2024–2026) Ultra-Fast and Secure Terahertz Communications for 6G (2023–2026) Facility for Energy Security and Resilience Research (2022) His lab, the Emerging Communications Laboratory, develops cutting-edge solutions for 6G networks, including hybrid beamforming for terahertz systems and secure short-packet protocols. Collaborations span global institutions, emphasizing interdisciplinary research in communications and signal processing.
Golnoosh Farnadi is an Assistant Professor at McGill University's School of Computer Science , an Adjunct Professor at Université de Montréal , and a Visiting Faculty Researcher at Google Research . She holds the Canada CIFAR AI Chair and is a core academic member of Mila – Quebec AI Institute . Her research focuses on algorithmic fairness , responsible AI , and optimization . She founded the EQUAL Lab (EQuity & EQuality Using AI and Learning algorithms) to address bias and discrimination in AI systems. Key publications explore fairness in kidney exchange programs, generative model geometry, multilingual LLM de-biasing, and prototype-based recommender systems. Her work bridges causal inference, adversarial robustness, and ethical AI. Google Award for Inclusion Research (2023) Women in AI Awards North America Finalist (2023) Facebook Privacy Enhancing Technologies Award (2021) IVADO Postdoctoral Fellowship (2018–2021) She has supervised over 15 PhD and Master's students, including Prakhar Ganesh (McGill) and William St-Arnaud (Université de Montréal). Her teaching includes Responsible AI and Machine Learning courses at McGill and HEC Montréal.
