Raju Vatsavai is an Associate Professor in the Department of Computer Science at North Carolina State University, affiliated with the Center for Geospatial Analytics. He joined NC State in 2014 as part of the Chancellor’s Faculty Excellence Program cluster hire in Geospatial Analytics. Education: PhD and MS in Computer Science from University of Minnesota Prior Roles: Lead Data Scientist at Oak Ridge National Lab, roles at University of Minnesota, IBM Research, AT&T Labs, and C-DAC (India) His research in geospatial analytics spans big data management , spatiotemporal data mining , deep learning for remote sensing , and high-performance computing , with applications in national security, climate change, and crop monitoring. Recent work includes deep learning frameworks for cloud imputation , multi-sensor satellite data harmonization , and transfer learning applications in crop classification . He has been a leading investigator on grants from the National Geospatial-Intelligence Agency, Department of Energy, and Department of Homeland Security. Labs: Associate Director of the Center for Geospatial Analytics Expertise: Spatial computing, Earth observation, nuclear proliferation detection via remote sensing
Thorsten Schmidt is Professor of Mathematical Stochastics at the University of Freiburg, succeeding Prof. Ernst Eberlein in the summer semester of 2015. He also serves as Senior Financial Engineer at MathFinance. Previously, he held professorships at Chemnitz University of Technology (2008-2015), Technical University Munich (2008), and University of Leipzig (2004 onwards). From 2017-2019, he was a Research Fellow at the Freiburg Institute for Advanced Studies (FRIAS) in a joint research group with the University of Strasbourg and USIAS on the topic of Linking Finance and Insurance. His research focuses primarily on financial and actuarial mathematics, stochastic processes, and statistics, with recent work on machine learning methods and their applications in financial mathematics and AI regulation. In Freiburg, his goal with his young team is to tackle complex challenges with improved mathematical models and apply these methodologies to various fields. Key Research Areas: Financial mathematics and credit risks Pricing and hedging of derivative financial products Statistics of stochastic processes Energy markets and nonlinear filter theory Machine learning applications in finance and insurance His recent publications show a strong trend toward integrating machine learning with traditional mathematical finance, particularly in risk management, insurance-finance arbitrage, and robust financial modeling. His work increasingly addresses ethical considerations in AI applications within finance, reflecting his broader interest in responsible AI development. Notable Awards: IDA Award Finance (2015) FRIAS-USIAS Research Fellow (2017/2018) IDA Award Machine Learning and AI (2020) MAPFRE Research Grant (2020) Luis Bachelier Fellow (2021) As Editor-in-Chief of Statistics and Risk Modeling and Associate Editor for Mathematical Finance and International Journal of Theoretical and Applied Finance, Schmidt plays a significant role in academic publishing. He leads the CRC 'Small Data' research center with Harald Binder, focusing on medical problems where disease progression must be estimated with few data points per patient. His LeanAI project, funded by the Vector Foundation, explores the connection between machine learning and theorem-proving software LEAN, aiming to develop AI that can translate between mathematics and formal proof systems. His laboratory work centers around the application of stochastic methods combined with machine learning to solve problems in finance and insurance where data is limited ('Small Data' initiative), with significant funding from DFG (€12 million for CRC Small Data) and the Carl Zeiss Foundation.
Mathieu Arnoux is a University Professor and Director of Studies at the École des Hautes Études en Sciences Sociales (EHESS), affiliated with University Paris Diderot. He is attached to the Centre for Economic and Social History François Simiand (CRH) and works within the GrHEco research team. His professional contact is based at the EHESS-CRH center located at 48, boulevard Jourdan, 75014 Paris. Arnoux specializes in Medieval European History with a focus on economic history, particularly examining European economy from the 10th to 16th centuries. His research interests encompass work and techniques in medieval societies, Normandy, and the broader Anglo-Norman world. He is particularly known for his studies on resource management, economic growth, and social organization during the medieval period. His research output demonstrates a consistent focus on medieval economic structures, with particular attention to the relationship between resource availability, agricultural production, and societal development. Arnoux's work bridges historical analysis with contemporary questions about sustainability and economic development, as evidenced by his 2023 publication 'A world without resources. Need and society in Europe (11th-14th centuries)' and his 2019 article 'Renewable Resources and Economic Growth: Medieval Suggestions and Contemporary Questions'. Arnoux is actively engaged in academic life, teaching courses on natural resources including 'renewal, depletion and crisis' for the 2024-2025 academic year. He participates in multiple research groups including GRHECO and LIED (Intradisciplinary Laboratory for the Energies of Tomorrow at Paris 7-Diderot University).
Jon Crowcroft is the Marconi Professor of Communications Systems in the Department of Computer Science and Technology at the University of Cambridge, and serves as the Chair of the Programme Committee at the Alan Turing Institute. He is also a Fellow of Wolfson College, Cambridge, and a visiting professor at the Department of Computing at Imperial College London. With a career spanning over three decades in computer networking research, Professor Crowcroft has made seminal contributions to the development of the Internet and continues to be highly active in cutting-edge research areas. His educational background includes: BA in Physics from Trinity College, University of Cambridge (1979) MSc in Computing from University College London (1981) PhD from University College London (1993) Professor Crowcroft's research spans multiple domains in computer networking and distributed systems. He has worked in Internet support for multimedia communications for over 30 years, with three main focus areas: scalable multicast routing, practical approaches to traffic management, and the design of deployable end-to-end protocols. His current research focuses on opportunistic communications, social networks, and techniques to scale infrastructure-free mobile systems. He is particularly known for his 'build and learn' paradigm for research and has recently been exploring decentralized digital identification systems, smart cities, and edge computing. His work often bridges theoretical foundations with practical implementations, emphasizing privacy-preserving approaches and sustainable network architectures. Professor Crowcroft has received numerous prestigious awards recognizing his contributions to the field, including: Election as Fellow of the Royal Society (2013) ACM SIGCOMM Award (2009) ACM Fellow (2002) Fellow of the Royal Academy of Engineering IEEE Fellow (2004) Chartered Fellow of the British Computer Society Throughout his career, Professor Crowcroft has advised numerous PhD students, including Mark Handley and Pan Hui, who have themselves become influential researchers in the networking community. He has authored several influential books that have been adopted internationally in academic courses, such as 'TCP/IP & Linux Protocol Implementation,' 'Internetworking Multimedia,' and 'Open Distributed Systems.' His research has been supported by various grants and collaborations with both academic institutions and industry partners, contributing to successful startup projects and influencing Internet standards. Professor Crowcroft is actively involved in several research initiatives, including serving on the Scientific Council of IMDEA Networks Institute since 2007 and the advisory board of the Max Planck Institute for Software Systems. He is also a director of the Matrix Foundation, which develops open network protocols. His current research group focuses on privacy-preserving analytics, decentralized systems, and the future of Internet architecture.
Dr Angus Armstrong is a Professorial Research Fellow at the UCL Institute for Global Prosperity, University College London, directing the ESRC-funded Rebuilding Macroeconomics network that has produced 80+ papers and 100+ public events. His work reinterprets macroeconomics as a knowledge-creation system under fundamental uncertainty. Research focuses on decision-making under uncertainty, collective intelligence, agent-based modelling, and macroeconomic policy within ecological economics, comparative systems, and experimental frameworks. He emphasizes institutions and social interactions as foundations of prosperity in complex adaptive systems. Analysis of 2015-2019 publications reveals concentrated expertise in Brexit fiscal impacts, devolution economics, monetary policy at zero bounds, and Scottish independence. Works integrate macroeconomic modeling with political economy, addressing UK/European policy challenges through institutional and uncertainty-focused lenses. Armstrong serves as Chief Economic Advisor to Lloyds Banking Group (2017) and leads the Rebuilding Macroeconomics network. His 'New Economics of Prosperity' teaching reimagines prosperity as emergent from socio-economic interactions rather than an end state, reflecting his view of economies as open systems defined by fundamental uncertainty.
Ron Steinfeld is an Associate Professor at the Cybersecurity Lab of the Faculty of Information Technology , Monash University . His research focuses on lattice-based cryptography , post-quantum cryptographic protocols , and privacy-preserving technologies . He has contributed to advancements in secure multiparty computation , digital signatures , and blockchain confidentiality . Key areas: Lattice-Based Cryptography, Zero-Knowledge Proofs, Blockchain Security Recent work trends: Quantum-safe protocols, Efficient sampling algorithms, Scalable blockchain solutions Scientific Awards : BEST PAPER AWARD (ASIACRYPT 2015) He has served on program committees for major conferences including CRYPTO , EUROCRYPT , and ASIACRYPT . Ron is a member of the Discrete Mathematics Research Group and has collaborated with institutions like Macquarie University in the past.
Ziming Zhang is an Assistant Professor in the Department of Electrical and Computer Engineering at Worcester Polytechnic Institute (WPI) , with additional affiliations in Data Science and Robotics Engineering. He previously held research roles at Mitsubishi Electric Research Laboratories (MERL) and Boston University. PhD in Computing (2013) from Oxford Brookes University , UK MS in Computing Science (2010) from Simon Fraser University , CA BS in Computer Science and Technology (2005) from Northeastern University , China Research interests span computer vision , machine learning , and their applications in point cloud processing , medical imaging , autonomous driving , and IoT . He leads the Vision, Intelligence, and System Laboratory (VISLab) at WPI. Recent publications focus on 3D reconstruction , hyperbolic learning , and robust classifiers . Awards include the R&D100 Award 2018 and NSF funding for data-efficient deep learning. PhD Students: Yecheng Lyu (co-supervised), Guojun Wu (co-supervised), Hangrui Zhang, Xuechu Yu Master's Students: Yun Yue, Yuping Shao Visiting Scholars: Fangzhou Lin His lab partners with industry and academic institutions, focusing on autonomous systems , robotics , and scientific imaging projects.
Mikael Gidlund is a Full Professor of Computer Engineering at Mid Sweden University in Sundsvall and holds an adjunct professorship at Beijing Jiaotong University, China. He serves as head of the Computer Engineering subject and program manager for the international MSc program in Computer Engineering. His academic journey includes a Ph.D. in Electrical Engineering from Mid Sweden University (2005), followed by roles at ABB Corporate Research (2008-2014) where he led wireless technologies research. Dr. Gidlund's research spans Wireless Communication, Industrial IoT, 5G/6G Networks, and Network Security . His group focuses on AI/ML for beyond-5G wireless communication, time-critical industrial applications, and IoT security. Current research themes include Future Wireless Networks (5G/6G) using AI/ML, Time-and mission-critical wireless communication, Industrial IoT, and IoT Security. His work demonstrates strong interdisciplinary connections between wireless systems, industrial automation, and security. His publication portfolio includes over 200 scientific articles and 20+ patents. Recent publications show a clear trend toward AI/ML integration in wireless systems, NOMA techniques, RIS technologies, and security solutions for industrial applications. The research output demonstrates strong international collaboration across six continents. Best Paper Award at IEEE International Conference on Industrial IT (2014) Co-author of IEEE Sweden VT-COM-IT Joint Chapter Best Student Journal Paper Award (2022) Dr. Gidlund actively mentors 6 current PhD students and has supervised 16 former PhD students who now hold positions at institutions including Ericsson, Lund University, Aalborg University, and Mid Sweden University. His research is supported by multiple active projects including IRS TransTech, NIIT, ENSURE 6G, and TRUST. He collaborates with institutions worldwide including City University of Hong Kong, Iowa State University, Kyung Hee University, and KTH Royal Institute of Technology. His research group maintains strong industry connections through projects with ABB, Ericsson, and other industrial partners, focusing on practical implementations of wireless technologies for industrial automation and critical infrastructure.
Joris M. Mooij is a Professor of Mathematical Statistics at the Korteweg-De Vries Institute of the University of Amsterdam, Netherlands. His research focuses on causality, spanning causal modeling, discovery, and inference with applications in biology, medicine, fairness, and business analytics. He combines mathematical modeling with statistical and algorithmic approaches in his work. Dr. Mooij received his PhD with honors from Radboud University Nijmegen in 2007, focusing on approximate inference in graphical models. After postdoctoral work at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany, he obtained an NWO VENI grant in 2011 for further postdoctoral research at Radboud University. He became Assistant Professor at the University of Amsterdam's Informatics Institute in 2013, was promoted to Associate Professor in 2017, and became a full Professor of Mathematical Statistics in 2020. Dr. Mooij's research centers on causal inference, with particular expertise in structural causal models, cyclic causal systems, and causal discovery algorithms. His work addresses fundamental questions about when causal relationships can be identified from observational data and how to develop robust causal discovery methods that work in complex real-world settings with latent variables, cycles, and selection bias. He has made significant contributions to understanding the limitations of existing causal discovery approaches and developing new methods that overcome these limitations. His research group organizes the Amsterdam Causality Meeting series and develops theoretical frameworks for causal modeling that encompass both acyclic and cyclic systems. Dr. Mooij has collaborated extensively on applications of causal methods in biological systems, including protein signaling networks and gene expression data. The group's recent work explores performative predictions, causal domain adaptation, and robust causal discovery methods that account for selection bias and missing data. Dr. Mooij has received numerous awards for his research, including: Best paper award at UAI for "Establishing Markov equivalence in cyclic directed graphs" IEEE Geoscience and Remote Sensing Society 2011 Letters Prize Paper Award ICML Test of Time Honorable Mention Best student paper award at UAI 2010 He has secured competitive research funding through an NWO VENI grant, NWO VIDI grant, and an ERC Starting Grant, which supported the establishment of his research group consisting of 3 PhD students and 3 postdocs focused entirely on causality. Dr. Mooij has supervised several PhD students, including Tineke Blom, whose work on "Causality and Independence in Perfectly Adapted Dynamical Systems" significantly influenced his thinking about causality in complex systems. He has co-taught the MasterMath course on Causality and published lecture notes titled "A Mathematical Introduction to Causality." His research continues to push the boundaries of causal inference methodology and its applications across diverse scientific domains.
Rasheed Hussain is an Associate Professor of Intelligent Network Security at the Smart Internet Lab and Bristol Digital Futures Institute (BDFI), School of Electrical, Electronic and Mechanical Engineering at the University of Bristol, UK. Previously, he served as a Senior Lecturer at the same institution from December 2021 to July 2025. He has held academic positions at Innopolis University, Russia, where he served as Associate Professor and Director of the Institute of Information Security and Cyber-Physical Systems, and as a guest researcher at the University of Amsterdam, Netherlands. His educational background includes a PhD in Computer Engineering from Hanyang University, South Korea (2011-2015), an MS in Computer Engineering from the same institution (2008-2010), and a B.Sc in Computer Software Engineering from the University of Engineering and Technology, Peshawar, Pakistan (2003-2007). Hussain's research focuses on network and cybersecurity, particularly future network security including 6G, the role of Digital Twins in future networks and systems security, and Responsible AI including fairness, trustworthiness, and explainability. His work spans information security, privacy, applied cryptography, vehicular networks, Internet of Things, Content-Centric Networking, cloud computing, API security, and blockchain applications. Senior member of IEEE Member of ACM ACM Distinguished Speaker Editorial board member for IEEE Communications Surveys & Tutorials, IEEE Access, and other journals His recent publications demonstrate a strong focus on the intersection of AI, networking, and security, with particular emphasis on Digital Twins, blockchain applications, federated learning, and 6G security. His research shows a clear trajectory toward addressing security challenges in emerging network architectures while incorporating responsible AI principles. Scientific Recognition: ACM Distinguished Speaker Netherlands University Teaching Qualification (Basis Kwalificatie Onderwijs, BKO) Hussain serves as a reviewer for major IEEE transactions, Springer and Elsevier journals, and participates in technical program committees for conferences including IEEE VTC, IEEE VNC, IEEE Globecom, and IEEE ICC. He is also certified as a trainer for the Instructional Skills Workshop (ISW) and contributes to the ESRC Centre for Sociodigital Futures (CenSoF) at the University of Bristol. His laboratory work centers around the Networks and Blockchain Lab, which focuses on security solutions for next-generation networks, with particular emphasis on Digital Twins security, blockchain applications, and AI-driven network security solutions. His current projects involve developing secure frameworks for future networks, trustworthy AI models, and privacy-preserving federated learning approaches.
Dr. Manav R. Bhatnagar serves as a Professor and Brigadier Bhopinder Singh Chair Professor in the Department of Electrical Engineering at Indian Institute of Technology Delhi. He ranks #517 globally in Networking & Telecommunications among the top 2% scientists worldwide according to Stanford University and is a Fellow of INAE, NASI, IET(UK), IETE, and OSI. His academic credentials include a Ph.D. in Signal Processing for Communications from University of Oslo (2008), M.Tech. in Communications Engineering from IIT Delhi (2005), and B.E. in Electronics from North Maharashtra University (1997). He has held visiting appointments at prestigious institutions including Aalto University (Finland), University of Rennes (France), University of Oslo, Indian Institute of Science Bangalore, and University of Minnesota. Dr. Bhatnagar's research spans cutting-edge domains including 5G/6G communication, optical wireless communication, quantum communication, molecular communication, power line communication, and machine learning applications. His work demonstrates significant interdisciplinary connections between communication theory, signal processing, and emerging technologies. His publication record shows a strong focus on wireless and optical communication systems, with recent work addressing challenges in jamming detection, quantum relay systems, IRS-assisted communication, and game-theoretic approaches to resource allocation. His research consistently bridges theoretical foundations with practical applications in next-generation communication systems. NASI-Scopus Young Scientist Award Shri Om Prakash Bhasin Award (2016) Dr. Vikram Sarabhai Research Award (2017) BASIC RESEARCH AWARD of IIT Delhi (2023) Sir Visvesvaraya Young Faculty Research Fellowship (2016) Senior Member of IEEE As an academic advisor, Dr. Bhatnagar has mentored numerous PhD students who have gone on to successful careers at institutions including IIT Jodhpur, IIT Roorkee, Aalto University, and IIT Kanpur. His editorial roles include current Editor of IEEE Transactions on Communications and former Editor of IEEE Transactions on Wireless Communications (2011-2014). His textbook "Telecommunication Switching Systems and Networks" has become a standard reference in the field.
Edgar Weippl is a Professor at the Faculty of Computer Science, University of Vienna, where he serves as Vice Dean and Head of the Research Group Security and Privacy. His work spans cybersecurity, blockchain, and machine learning, with teaching roles in information security and software security courses. Current Positions: Vice Dean (Faculty of Computer Science), Head (Security and Privacy Research Group), Deputy Head (Neuroinformatics & Knowledge Engineering Groups) Research Interests: Cybersecurity, blockchain, IoT security, code obfuscation, privacy technologies, reinforcement learning, and socio-technical systems security Selected Publications: Focus on blockchain privacy, VoWiFi security, code obfuscation, and reinforcement learning applications
Nikos Hardavellas is a Professor of Computer Science and Electrical and Computer Engineering at Northwestern University, affiliated with the McCormick School of Engineering. He leads the Parallel Architecture Group at Northwestern (PARAG@N), focusing on energy-efficient parallel computing and quantum systems. His research spans quantum computing systems, fault-tolerant quantum error management, memory-centric architectures, and photonics-based interconnects. Education: Ph.D. Computer Science, Carnegie Mellon University (2009) M.S. Computer Science, Carnegie Mellon University (2006) M.S. Computer Science, University of Rochester (1997) B.S. Computer Science, University of Crete (1995) Research Interests: Quantum system software stack and error mitigation Memory-centric computing and programmable memory systems Energy-efficient architectures and dark silicon Photonics and optical interconnects Parallel systems and compiler-hardware co-design Key Contributions: Developed SupermarQ, a scalable quantum benchmark suite Pioneered optical cache hierarchies (Pho$) and energy-proportional photonic networks Advanced compiler-driven virtual memory systems (CARAT) and MPI autotuning (ACCLAiM) Awards & Honors: NSF CAREER Award (2015) Future CRA Leader (2024) Best Paper Awards at HPCA (2022) and ISLPED (2021 nomination) Test-of-Time Award at EDBT (2019) Grants & Service: Secured $4.8M in research funding from NSF, industry partners, and university initiatives Executive Committee member of Northwestern’s INQUIRE Institute for Quantum Research General Co-chair of IEEE/ACM MICRO 2022 Extensive service on departmental committees and thesis advisory boards Labs & Teams: Directs PARAG@N, collaborating on quantum computing, photonics, and energy-efficient architectures. Engages with industry partners like AMD, Intel, and Synopsys.
Professor Yue Rong is a Full Professor at Curtin University's Department of Electrical and Computer Engineering, within the School of Electrical Engineering, Computing and Mathematical Sciences. He holds editorial roles at IEEE Transactions on Signal Processing and IEEE Wireless Communications Letters. His research focuses on signal processing for communications, underwater acoustic systems, wireless networks, and healthcare IoT. Rong has authored over 140 journal and conference papers and received multiple awards, including the 2010 Young Researcher of the Year Award. Education: B.E. (Electrical Engineering), Shanghai Jiao Tong University (1999) M.Sc. (Electrical Engineering), University of Duisburg-Essen (2002) Ph.D. (Electrical Engineering), Darmstadt University of Technology (2005) Research Interests: Rong's work spans cooperative MIMO communications, underwater acoustic systems, OFDM modulation, radar-based healthcare monitoring, and secure wireless protocols. His innovations include adaptive modulation schemes for underwater environments and radar-based vital signs detection. Recent trends in his publications emphasize AI-driven signal processing for healthcare IoT and underwater optical communication systems. Awards: Best Paper Awards (WCSP 2011, APCOMM 2010) Chinese Government Award (2004) DAAD/ABB Fellowship (2001-2002) Grants & Labs: His research is supported by grants focusing on UAV-enabled data collection and underwater network optimization. He leads projects in the Distributed Data Fusion and Emerging Technologies (DDFE) lab, advancing radar-cardiography and wearable health monitoring systems.
James Davis is a Professor and Head of School at Queen's University Belfast's School of History, Anthropology, Philosophy and Politics. He holds a PhD from the University of Cambridge, focusing on medieval English market culture, and has been at Queen's since 2005. His research centers on medieval social and economic history, particularly urban markets, trade, and legal ethics. He leads the History Centre and oversees projects like 'Medieval Street Life: Space, Culture and Commerce' and 'Morality, Law and Misbehaviour in the Medieval English Marketplace.' Education: Bachelor's Degree: University of Durham PhD: University of Cambridge (Retail Trade and Market Culture in Late Medieval England) Research Interests: Dr. Davis explores medieval markets' moral and legal frameworks, urban history, and pre-modern trade networks. His seminal work Medieval Market Morality (2012) investigates ethical dimensions of medieval commerce. Recent projects examine early-Reformation heretical book trade and the cultural role of medieval town spaces. Key Contributions: Published 73+ works including monographs, articles, and edited volumes Recipient of British Academy fellowships and other honors Active in academic governance and peer review (e.g., Economic History Review , Transactions of the Royal Historical Society ) Teaching: Designs modules on medieval social history, including the Peasants' Revolt of 1381 and comparative early modern life in England/Ireland. Grants & Awards: £1.2M funding for collaborative projects British Academy Mid-Career Fellowship (2017) Public Engagement: Regular media contributions include BBC Radio discussions on medieval markets, the Black Death, and urban history.
