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Farhad RachidiView profile

Professor

• Electromagnetic Compatibility
• Lightning electromagnetics
• Lightning and EMP interaction with transmission lines
• +4 more

Farhad Rachidi is a Full Professor at the Swiss Federal Institute of Technology (EPFL), where he serves as the Head of the Electromagnetic Compatibility (EMC) Laboratory within the School of Engineering's Department of Electrical Engineering. His research group has been active in EMC research since the early 1980s and maintains collaborations with numerous international institutions including Universities of Bologna and Rome (Italy), Uppsala University and KTH (Sweden), University of Toronto (Canada), University of Florida (USA), and others. Professor Rachidi's research spans electromagnetic compatibility, lightning electromagnetics, lightning and EMP interaction with transmission lines, electromagnetic time reversal, fault location, numerical computation of electromagnetic fields, and power line communications. His work integrates theoretical modeling with experimental validation, particularly in the context of lightning phenomena and electromagnetic interference. The research group develops innovative techniques such as electromagnetic time reversal for applications ranging from lightning detection to partial discharge localization in power systems. Analysis of his recent publications (2023-2025) reveals a strong focus on electromagnetic time reversal techniques, lightning physics and modeling, machine learning applications in electromagnetic phenomena, and advanced computational methods for electromagnetic field analysis. His work bridges fundamental electromagnetic theory with practical applications in power systems, atmospheric electricity, and security technologies. 2025 IEEE EMC Technical Achievement Award 2005 CIGRE Technical Committee Award 2006 Blondel Medal from SEE 2016 Berger Award from ICLP Best Paper Awards of IEEE Transactions on EMC (2016, 2018) Motohisa Kanda Award for most cited papers (2012-2018) 2024 Distinguished Honorary Professor at Tsinghua University 2014 Honorary Professor at Xi'an Jiaotong University Professor Rachidi has supervised numerous students through semester projects, diploma projects (equivalent to MS), and PhD programs at EPFL. His research is primarily sponsored by Swiss National Science Foundation, European Community programs, European Space Agency, Swiss Electrical Utilities, and private companies. He has served in leadership roles including President of the International Conference on Lightning Protection (2008-2014), Editor-in-Chief of IEEE Transactions on Electromagnetic Compatibility (2013-2015), and President of the Swiss National Committee of the International Union of Radio Science (2012-2020). The EMC Laboratory at EPFL, which he heads, maintains the Säntis lightning research facility and has been instrumental in advancing our understanding of lightning phenomena through direct measurements at instrumented towers. The group has developed innovative techniques including electromagnetic time reversal for fault location in power networks and lightning detection systems.

Hanqing JinView profile

Associate Professor

• Mathematical Finance
• Stochastic Analysis
• Portfolio Optimization
• +3 more

Dr. Hanqing Jin is an Associate Professor in the Mathematical Institute at the University of Oxford, specializing in Mathematical Finance and Applied Stochastic Analysis. His research focuses on investor decision-making under non-utility behavior, dynamic portfolio optimization, and stochastic control problems in financial markets. Prior to Oxford, he held an Assistant Professorship at the National University of Singapore. He has contributed to foundational work on mean-variance portfolio selection, behavioral finance, and the application of stochastic processes to financial modeling. His academic background includes extensive work on continuous-time portfolio optimization, risk management frameworks, and the intersection of behavioral economics with quantitative finance. Notable contributions include studies on optimal lockdown policies during pandemics, blockchain consensus algorithms analysis, and the development of novel biomarker detection techniques using Raman spectroscopy. Dr. Jin's research integrates advanced mathematical techniques with real-world financial challenges, bridging theoretical models with practical applications in areas such as robo-advising systems and cryptocurrency frameworks. His work on transaction cost analysis and dynamic mean-variance strategies has been widely cited in both academic and industry contexts.

Traci J. HessView profile

Professor

• Human-Computer Interaction
• Decision-Making Systems
• Electronic Commerce
• +3 more

Traci J. Hess is the Douglas & Diana Berthiaume Endowed Professor of Information Systems and Senior Associate Dean at the Isenberg School of Management, University of Massachusetts Amherst. She holds a PhD (1999), MA (1997) in Information Systems from Virginia Tech, and a BS in Accounting from the University of Virginia (1988). Her academic career includes roles at Washington State University and industry experience as Senior Vice President in banking and auditing roles at Ernst & Young. Her research focuses on Human-Computer Interaction , Decision Support Systems , and Trust in Digital Technologies . She explores topics like online review dynamics, privacy mechanisms in health communities, and algorithmic labor platforms. Hess has published extensively in journals like Journal of the Association for Information Systems and MIS Quarterly , and her work bridges cognitive psychology with technology design. Hess has received prestigious awards including the Isenberg Outstanding Research Award (2012) and Transactions on Human-Computer Interaction Best Paper Award (2011). Her teaching spans Business Intelligence , Database Management , and Research Methods . She has advised numerous graduate students (not listed explicitly in texts) and contributes to digital strategy research. Her recent work (2023–2024) examines reviewer badges’ impact on consumer trust and human agency in algorithmic labor systems. She emphasizes user-centric design principles to mitigate negative emotional responses to technology (e.g., technostress).

Trac-Duy TranView profile

Professor

• Digital Signal Processing
• Sparse Representation
• Sparse Recovery
• +6 more

Trac-Duy Tran is a Professor in the Department of Electrical and Computer Engineering at Johns Hopkins University's Whiting School of Engineering. His research focuses on digital signal processing, including sparse representation, transforms, and their applications in compression and communications. He has contributed to standards like JPEG XR and Microsoft Windows Media Video 9. Education: BS and MS in Electrical Engineering, Massachusetts Institute of Technology (1993, 1994) PhD in Electrical Engineering, University of Wisconsin (1998) Research Interests: Dr. Tran explores sparse recovery , filter banks , and wavelet transforms , with applications in signal analysis and communication systems. His work emphasizes practical implementations in multimedia standards. Awards: NSF CAREER Award (Research Excellence) William H. Huggins Award (Teaching) Capers & Marion McDonald Award (Mentoring) IEEE Fellow (2023) Professional Roles: He served as Associate Editor for IEEE Transactions on Signal Processing and IEEE Transactions on Image Processing . Currently consults for the U.S. Army Research Laboratory and chairs the IEEE IVMSP Technical Committee.

Natasha FernandesView profile

Senior Lecturer

• Data Privacy
• Differential Privacy
• Privacy-Preserving Machine Learning
• +3 more

Natasha Fernandes is a Senior Lecturer in the School of Computing at Macquarie University. She holds a PhD in Computing from Macquarie University and École Polytechnique (France), and an undergraduate degree in Pure Mathematics and Computer Science from the University of Sydney. Her roles include involvement in the Data Horizons Research Centre and Future Communications Research Centre, alongside professional casual appointments in academic computing. Her research focuses on the mathematical foundations of data privacy, particularly differential privacy and its applications in natural language processing and machine learning. She develops privacy-preserving systems and tools using quantitative information flow techniques rooted in information theory. Key areas include privacy analyses for financial systems (e.g., Open Banking), API privacy, and optimizing utility in privacy pipelines. Fernandes has led or contributed to five research projects, including work on privacy analyses for financial transaction protocols and UAV-based machine learning systems. She received the 2021 John Makpeace Bennett Award for her doctoral research on differential privacy in metric spaces. Her academic journey combines industry experience as a backend software engineer with rigorous academic contributions, spanning over 21 peer-reviewed publications and collaborations across cybersecurity and privacy engineering domains.

Yan WangView profile

Professor

• Trust Management
• Recommender Systems
• Social Networks
• +7 more

Yan Wang is a Full Professor in the School of Computing at Macquarie University, Australia. He obtained his PhD from Harbin Institute of Technology (HIT), China, and has been at Macquarie since 2003 following a postdoctoral fellowship at the National University of Singapore. His research focuses on trust management, recommender systems, social networks, and services computing, with a strong emphasis on applications in cyber security and data analytics. Wang has published extensively in top-tier venues like AAAI, IJCAI, and IEEE Transactions, and has led over 25 research projects, including current initiatives like Trust-Oriented Data Analytics in Online Social Networks (DP230100676) and Combating Fake News on Social Media (2020–2023). He has received prestigious awards such as the IEEE TCSVC Outstanding Service Award (2017) and the Vice-Chancellor’s Excellence in Research Supervision Award (2014). He serves on editorial boards of journals like IEEE Transactions on Services Computing and has organized major conferences including IEEE ATC2013 and IEEE CLOUD2017. His work bridges theoretical advancements in machine learning and practical challenges in social computing, edge computing, and federated learning. Affiliations: School of Computing, Data Horizons Research Centre, Frontier AI Research Centre Key Projects: Trust-Oriented Data Analytics in Online Social Networks (2023–2026) Combating Fake News on Social Media (2020–2023) Research Themes: Recommender systems, graph learning, fake news detection, and trust management in distributed systems. Wang’s recent work explores causal representation learning, cross-domain recommendations, and privacy-preserving techniques in edge computing environments.

• Distributed/Parallel Computing
• Information Visualization
• Fault-Tolerant Communication Mechanisms
• +4 more

Philippas Tsigas is a Professor at the Department of Computer Science and Engineering at Chalmers University of Technology. He leads the Distributed Computing and Systems Research Group and has held roles as co-leader of research initiatives such as the PEPPHER project. His research spans distributed/parallel computing, information visualization, and fault-tolerant communication mechanisms. He has supervised numerous PhD students, including Yi Zhang, Håkan Sundell, and Farnaz Moradi. Research interests include lock-free data structures, multicore algorithms, secure network services, and visualization tools like Lydian and DataMeadow. Notable awards include Best Paper Awards at IPDPS 2003 and SNS 2012. His work has been published in top venues like IEEE Transactions on Parallel and Distributed Systems and ACM Journal of Experimental Algorithmics. Awards highlight contributions to lock-free algorithms and network modeling. Students have contributed to projects like NBmalloc (memory reclamation) and GPU Quicksort. Collaborations with institutions like SSF and VR have supported his research. Tsigas is also involved in teaching distributed systems and mentoring early-career researchers.

Marwa ChafiiView profile

Associate Professor

• Wireless Communications
• Integrated Sensing and Communication
• Machine Learning for Wireless Communications
• +3 more

Marwa Chafii is an Associate Professor of Electrical Engineering at New York University (NYU) Abu Dhabi and an associated faculty member at the NYU Tandon School of Engineering. She joined NYU Abu Dhabi in 2021 after holding roles as a research group leader at TU Dresden (Germany) and an associate professor at ENSEA (France) with a Chair of Excellence in AI. Her research focuses on advanced waveform design, integrated sensing and communication (ISAC), machine learning for wireless communications, and localization . Education: PhD and Master’s in Electrical Engineering from CentraleSupélec, France. Visiting researcher stints at institutions including Poznan University of Technology, University of York, and University of Oxford. Awards & Recognition: IEEE ComSoc Best Young Researcher Award (EMEA region) Best Editor Award for IEEE Communications Letters (2020) Nominated Top 10 Rising Stars in Computer Networking & Communications (2020) French National Council of Universities (CNU 61) AI Excellence Chair (2018–2022) Best PhD in France (Signal, Image & Vision) Professional Roles: Vice-chair of IEEE ComSoc ETI on Machine Learning for Communications Education Lead for IEEE ComSoc ETI on Integrated Sensing & Communications Associate Editor for IEEE Transactions on Communications and IEEE Communications Letters Research Contributions: Over 50+ publications in top-tier journals/conferences (IEEE Transactions, Globecom, ICC) Active in ISAC, 6G waveform design, and AI-driven communication systems Leading the NYU Wireless Research Lab focused on ISAC and future wireless systems

James B D JoshiView profile

Professor

• Cybersecurity
• Privacy-Preserving Technologies
• Access Control
• +5 more

James B D Joshi is a Professor in the Department of Informatics and Networked Systems (DINS) at the University of Pittsburgh’s School of Computing and Information (SCI). He joined Pitt in 2003 after earning his PhD from Purdue University. From 2019 to 2023, he served as a Program Director for the NSF’s Secure and Trustworthy Cyberspace (SaTC) program. Currently, he is an intermittent Expert in NSF’s TIP Directorate and led the NSF PDaSP program. His research focuses on cybersecurity and privacy, including access control, AI/ML security, cloud/edge security, and privacy-preserving techniques. Education: PhD, Computer Engineering, Purdue University (2003) MS, Computer Science, Purdue University (1998) BE, Computer Science & Engineering, Motilal Nehru NIT, India (1993) Research Interests: Privacy, security, trust, attribute-based encryption, cloud security, insider threat detection, and privacy-preserving AI/ML. His work emphasizes trustworthy systems and secure distributed computing environments. Recent Contributions: His articles span privacy-preserving federated learning, insider threat mitigation, and secure edge computing. Recent projects include PPFL-RDSN (2025), TAPFed (2024), and blockchain-based transparency frameworks (2022). Awards & Honors: NSF Director’s Award (2023), IEEE Fellow (2023), ACM Distinguished Member (2017), NSF CAREER Award (2006), and SIRI Research Leadership Award (2018). Service & Leadership: Founding director of LERSAIS lab, co-chair of IEEE conferences (TPS, CIC, CogMI), and former Editor-in-Chief of IEEE Transactions on Services Computing. Active in NSF and NITRD policy initiatives, including privacy and digital assets R&D strategies.

• Distributed Systems
• Cloud Computing
• Fault Tolerance
• +3 more

Rodrigo Miragaia Rodrigues is a full professor at the Instituto Superior Técnico (ULisboa) and a researcher at INESC-ID since 2015. He previously held roles as an associate professor at Universidade Nova de Lisboa, tenure-track faculty at MPI-SWS, and completed his PhD at MIT in 2005 under Barbara Liskov. Education: PhD in Computer Science, MIT, 2005 Research Interests: Focuses on distributed systems, fault-tolerant computing, cloud infrastructure, and consistency models. His work bridges theoretical foundations and practical implementations, addressing challenges in geo-replication, secure analytics, and resource allocation in serverless environments. He emphasizes scalable systems and resilient data management. Awards: Best Paper Award at SOSP ERC Starting Grant Google Faculty Research Award Advising & Grants: Has advised 7 PhD students as main advisor, with graduates in top institutions like Purdue, TU Munich, and USTC. Secured funding from the European Research Council (ERC) and Google, focusing on projects like DependableCloud (ERC Grant 307732). Labs & Teams: Leads research at INESC-ID and previously directed the Dependable Systems Group at MPI-SWS. Active in academic leadership roles, including President of the Scientific Council at IST.

Manuela ColombiniView profile

Associate Professor

• Gender-based violence
• Health systems strengthening
• Health policy analysis
• +4 more

Dr. Manuela Colombini is an Associate Professor in Health Systems, Policy, and Gender-Based Violence at the London School of Hygiene & Tropical Medicine (LSHTM), within the Department of Global Health and Development and the Faculty of Public Health and Policy . She co-directs LSHTM’s Gender Violence and Health Centre (GVHC) and leads the gender-based violence theme at the Centre for Maternal Adolescent and Child Health (MARCH) . Her work focuses on health systems responses to gender-based violence (GBV), particularly in low- and middle-income countries (LMICs), integrating feminist theories and health policy frameworks. Her research explores how health systems can better address violence against women (VAW) through service integration, policy implementation, and intervention design. Notable projects include evaluating One Stop Crisis Centres (WHO collaboration), assessing the impact of lockdowns on VAW service provision in South Africa, and studying intersections between VAW and violence against children in the Middle East. She has led studies in Brazil, Palestine, Nepal, Sri Lanka, South Africa, Kenya, and Malaysia. Dr. Colombini’s teaching roles include Project Content Director for the Distance Learning Master in Health in Humanitarian Crises and Module Organiser for courses on Health Policy, Process and Power . She also contributes to training programs for tropical nursing and gender-based violence research. Her professional engagements include advisory roles with the WHO, UNICEF, and the Sexual Violence Research Initiative. Awards include Honorary Fellow (2018–2024) and Honorary Lecturer (2017–2019). Her work emphasizes translating evidence into actionable policies, with a focus on vulnerable populations and health equity.

Ansgar WohlschlegelView profile

Associate Professor

• Law & Economics
• Applied Microeconomics
• Industrial Organization
• +4 more

Dr. Ansgar Wohlschlegel is an Associate Professor of Economics at Swansea University, affiliated with the Faculty of Humanities and Social Sciences and the School of Social Sciences. His expertise lies in Applied Microeconomics, Law & Economics, and Industrial Organization. Prior to Swansea, he held academic positions at the Universities of Portsmouth, Bonn, and Aachen, and worked in the private sector at PricewaterhouseCoopers. His research focuses on the economic analysis of legal systems, including enforcement agency incentives, legal procedure design, and tort law impacts. He employs applied game theory, empirical methods, and laboratory experiments. Notable real-world applications include policy projects for the Food Standards Agency and contributions cited in Westminster debates. His teaching spans Microeconomics specializations like industrial organization, contract theory, and the economics of crime, alongside introductory economics courses. His recent publications address topics ranging from bank regulation to litigation incentives, reflecting a blend of theoretical rigor and policy relevance. Dr. Wohlschlegel is actively involved in postgraduate supervision and maintains research links via ORCID and Google Scholar.

Sadia NawazView profile

Lecturer

• AI in Education
• Learning Analytics
• Educational Technology
• +6 more

Sadia Nawaz is a Lecturer at the Department of Human Centred Computing at Monash University, with expertise in AI in education, learning analytics, and educational technology. She holds a PhD in Computing and Information Systems from the University of Melbourne (2015–2021), an MSECE from Purdue University (2010–2011), and prior degrees in Electronics Engineering and Telecommunication. Her research focuses on AI ethics, simulation-based learning, and the integration of psychometric techniques with learning analytics. She has contributed to projects like the 2025 ICT initiative on EDI in curriculum development. Her recent work emphasizes ethical AI adoption in education, curriculum analytics, and VR applications. She has published widely on topics such as student perceptions of AI, embodied learning in VR, and the impact of workplace bullying. Sadia actively contributes to academic journals and conferences, including the International Journal of Artificial Intelligence in Education and IEEE Transactions on Education . Key projects include leading a 2025 initiative to integrate equity, diversity, and inclusion into ICT education using GenAI. Her work aligns with UN Sustainable Development Goals related to quality education. She is also engaged in teaching and supervising students, emphasizing hands-on approaches and adaptive learning strategies.

Cevdet AykanatView profile

Professor

• Parallel Computing
• High-Performance Computing
• Graph and Hypergraph Partitioning
• +4 more

Prof. Cevdet Aykanat is a Professor of Computer Engineering at Bilkent University, Ankara, Turkey. He earned his BS/MS in Electrical Engineering from METU and PhD from Ohio State University as a Fulbright scholar. His research focuses on parallel computing, sparse matrix algorithms, graph partitioning, and high-performance computing for big data. He has been affiliated with Bilkent since 1989 and has held roles like Associate Provost. Education: BSc/MSc (METU Electrical Engineering), PhD (Ohio State University Electrical & Computer Engineering). Research interests include parallel scientific computing, combinatorial optimization, distributed systems, and large-scale data analysis. His work spans over 100 publications in top journals like IEEE Transactions and SIAM, with 5,500 citations and an H-index of 40. Awards: 1996 TUBITAK Investigator Award, 2007 METU Parlar Science Award. He led 6 TUBITAK projects and participated in EU-funded projects like PRACE-1IP to PRACE-6IP. Publications emphasize efficient parallel algorithms for sparse computations, graph partitioning, and distributed systems. His work addresses latency reduction, load balancing, and scalable data processing in HPC environments. Grants: Funded by TUBITAK, Intel SSD, and EU programs. Academic service includes editorial roles at IEEE Transactions on Parallel and Distributed Systems.

Tianqi HongView profile

Assistant Professor

• Power Systems
• Power Electronics
• Renewable Energy Integration
• +4 more

Dr. Tianqi Hong is an Assistant Professor at the University of Georgia, affiliated with the School of Electrical & Computer Engineering and the Department of Electrical and Computer Engineering. He holds a B.Sc. from Hohai University (2011), an M.Sc. from Southeast University and NYU (201?), and a Ph.D. from NYU (2016). Prior to his academic role, he served as a Principal Energy System Scientist at Argonne National Laboratory and a Senior Research Scientist at Unique Technical Services, LLC. His research focuses on power systems, power electronics, renewable energy integration, and AI-driven solutions for smart grids. Dr. Hong’s work emphasizes cybersecurity for power infrastructure, nonlinear dynamics in microgrids, and advanced control strategies. He actively contributes to IEEE Transactions across multiple journals and chairs the IEEE IAS Industrial Power Converters Committee. His recent publications address topics like AI-based photovoltaic inverter modeling, cyberattack mitigation in smart grids, and voltage regulation using distributed optimization. He has authored over 60 peer-reviewed articles, spanning from 2014 to 2025, with a focus on energy system stability, renewable integration challenges, and data-driven methodologies. His professional service includes editorial roles in top-tier journals and leadership in industry-research collaborations.