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Satarupa ChakrabartiView profile

Research Fellow

• Biomedical Engineering
• Signal Processing
• Machine Learning
• +3 more

Satarupa Chakrabarti is a Digital Futures Postdoctoral Research Fellow at KTH Royal Institute of Technology, based in the Computational Brain Science group within the Division of Computational Science and Technology. She holds a PhD in Computer Science from KIIT Deemed to be University, India, and previously worked as a Junior Research Fellow with DST-SERB, India. Her research focuses on biomedical engineering, signal processing, machine learning, and space physics, with a particular emphasis on developing brain activity-based biomarkers for Parkinson’s disease diagnosis and prognosis. Her academic background includes interdisciplinary projects on biomedical signal analysis, pediatric epilepsy detection, and power system fault localization. She collaborated with multidisciplinary teams at KTH, contributing to innovations in healthcare technology and smart societal solutions. Her postdoc project (2020–2022), funded by Digital Futures, aimed to extract temporal features from brain activity to improve PD diagnosis, leveraging machine learning advancements. Supervised by Professors Arvind Kumar and Saikat Chatterjee, her work bridges computational science and clinical applications. Publications span biomedical engineering (e.g., pediatric seizure detection), electrical engineering (HVDC fault localization), and space physics (ionospheric plasma analysis). Her contributions highlight machine learning applications across diverse domains. No scientific awards were explicitly mentioned. She is affiliated with Digital Futures, a cross-disciplinary center jointly established by KTH, Stockholm University, and RISE.

Rajendran ParthibanView profile

Professor

• Optical Networks
• Visible Light Communication
• Vehicular Communication
• +4 more

Professor Rajendran Parthiban is a Professor and Deputy Dean (Education) in the Department of Electrical and Computer Systems Engineering at Monash University. He holds a PhD and Bachelor of Engineering from the University of Melbourne (Australia). His academic leadership roles include Deputy Head of School (Education) and leadership in photonics and communications research groups. He has extensive teaching experience, achieving top evaluations in five undergraduate and one postgraduate subjects. Education: PhD in Electrical and Electronic Engineering, University of Melbourne (2004) Bachelor of Engineering (First Class Honours), University of Melbourne (1997) Research Interests: Focuses on optical networks, visible light communications (VLC), vehicular communication, and educational technologies like VR/AR integration. His work addresses challenges such as energy-efficient optical architectures, high-speed VLC systems, and technology-enhanced learning frameworks. Recent projects include developing traffic management frameworks and green vehicle routing strategies. Grants & Funding: Secured over RM2 million in external grants, including projects on Li-Fi systems, AR/VR in engineering education, and green vehicular networks. Notable grants include collaborations with the Australian Digital & Telecom Pty Ltd and Monash-Warwick Alliance. Awards: Pro-Vice Chancellor’s Award for Excellence in Research (2011, 2012) Pro-Vice Chancellor’s Award for Excellence in Teaching (2007–2010) Australian Learning and Teaching Council Citation (2008) Supervision: Guided eight PhD and one Master’s students, with ongoing supervision in areas like credit risk forecasting, vehicular networks, and seamless learning frameworks. Professional Activities: Senior member of IEEE, with affiliations to IEEE Communications Society, Photonics Society, and multiple engineering organizations. Active in research groups and international collaborations.

Michael G. KayView profile

Associate Professor

• Logistics Network Design
• Metaheuristics
• Freight Transportation
• +4 more

Michael G. Kay is an Associate Professor in the Edward P. Fitts Department of Industrial and Systems Engineering at North Carolina State University's College of Engineering. Since joining in 1992, he has served as Director of the Integrated Manufacturing Systems Engineering graduate program and as Co-Director of the Operations Research Program. His educational background includes a Ph.D. in Industrial Engineering from NC State University (1992), an MS in Industrial Engineering from the University of Florida (1984), and a BA in Economics from the University of Florida (1981). Kay's research focuses on logistics engineering, particularly the design of public logistics networks using driverless delivery vehicles. His work explores innovative solutions for freight transportation, warehousing, and production system design, with applications ranging from military logistics to sustainable supply chains. Key research areas include metaheuristic optimization, material handling systems, and multimodal transportation networks. Analysis of Kay's recent publications reveals a strong interdisciplinary focus spanning operations research, logistics engineering, and supply chain innovation. His work increasingly incorporates emerging technologies like blockchain and additive manufacturing to solve complex industrial problems. Research trends demonstrate consistent application of stochastic optimization methods to real-world challenges in transportation, manufacturing, and military logistics. Throughout his career, Kay has developed significant software tools including: Logjam (Julia package for logistics engineering) Matlog (Logistics Engineering Matlab Toolbox) Lgpy (Logistics Engineering Python Package) GAOT (Genetic Algorithm Optimization Toolbox)

Yang LiuView profile

Senior Lecturer

• Data Security
• Privacy-Preserving Computing
• Federated Learning
• +3 more

Dr. Yang Liu is a Senior Lecturer in the Department of Computer Science at Swansea University's Faculty of Science and Engineering. He holds a D.Phil. in Computer Science from the University of Oxford and specializes in data security, privacy-preserving computing, and blockchain technologies. Research Focus: Dr. Liu's work centers on secure computation frameworks with specific expertise in: Federated learning systems optimization Privacy-preserving smart contract design Blockchain security and regulation Cryptographic techniques for data protection Secure machine learning applications Recent publications demonstrate methodological innovations in adaptive federated learning algorithms, regulatable blockchain architectures, privacy-enhanced recommendation systems, and security vulnerability analysis in Ethereum networks. His research bridges theoretical cryptography with practical applications in cloud/edge computing environments.

Katherine DavisView profile

Associate Professor

• Cyber-Physical Systems
• Power Systems Operation and Control
• Smart Grid Security
• +3 more

Katherine Davis is an Associate Professor in the Department of Electrical and Computer Engineering at Texas A&M University, part of the College of Engineering. Her research focuses on cyber-physical systems, power grid security, and resilient energy infrastructure. She holds a Ph.D., M.S., and B.S. in Electrical Engineering from the University of Illinois Urbana-Champaign and the University of Texas at Austin. Her work addresses challenges such as cyber-physical attack detection, smart grid resilience, and integration of renewable energy systems. Education: Ph.D., Electrical Engineering (Power and Energy Systems), University of Illinois Urbana-Champaign, 2011 M.S., Electrical Engineering (Power and Energy Systems), University of Illinois Urbana-Champaign, 2009 B.S., Electrical Engineering (High Honors), University of Texas at Austin, 2007 Research interests include: - Operation and control of power systems - Cyber-physical security and situational awareness - Data-driven analysis of coupled infrastructure - Interactions between computer and power networks - False data injection attack detection using machine learning Her recent publications emphasize scalable tools for cyber-physical systems, AI-driven grid optimization, and resilient energy management. Notable trends include leveraging graph neural networks for anomaly detection, blockchain for secure data exchange, and multi-agent frameworks for distributed energy resources. Dr. Davis’s work has been applied to real-world scenarios such as wildfire response optimization and geomagnetic disturbance analysis. She collaborates on interdisciplinary projects involving cybersecurity, power systems engineering, and environmental resilience.

Mladen KezunovicView profile

Professor

• Power Systems
• Protective Relaying
• Computational Intelligence
• +5 more

Mladen Kezunovic is a Distinguished Professor, Regents Professor, and Eugene E. Webb Professor in the Department of Electrical and Computer Engineering at Texas A&M University. He leads the Power Engineering Research Center (PSerc) and specializes in protective relaying, computational intelligence, and smart grid technologies. With over 600 publications and 10 books, his work bridges academic research with industry applications through his consulting firm XpertPower™. Affiliations: College of Engineering, PSerc Consortium, IEEE Life Fellow, CIGRE Fellow Educations: Ph.D. (1980), M.Sc. (1977), and Dipl. Ing. (1974) in Electrical Engineering from University of Kansas and University of Sarajevo His research focuses on data-driven grid resilience , including machine learning for outage prediction, synchrophasor analytics, and smart grid cybersecurity. Recent projects address weather-related outages, transformer life-cycle management, and hybrid energy system integration. Key awards include membership in the US National Academy of Engineering (2022), IEEE Life Fellowship (2017), and global collaborations as a Guest Professor at Tsinghua University (2018–2021). Grants & Advising: Over $10M in sponsored research, advisor to 50+ industry projects, mentor to visiting scholars from Brazil, China, and Europe Labs: Power Systems Engineering Research Center (PSERC), Synchrophasor Analytics Lab, Smart Grid Cybersecurity Initiative

• Sustainability
• Climate Resilience
• Geospatial Technologies
• +4 more

Patricia Solís, PhD, is the Executive Director of the Knowledge Exchange for Resilience at Arizona State University (ASU), leading efforts to align community needs with research innovations. She holds the rank of Research Professor of Geography in the School of Geographical Sciences and Urban Planning. Her work focuses on sustainability, resilience, and geospatial technologies, particularly through initiatives like YouthMappers, a global consortium of student-led mapping chapters. She previously served as Co-Director at the Center for Geospatial Technology at Texas Tech University and Deputy Director at the American Association of Geographers. Education: PhD in Geography (University of Iowa, 2002), MA in Geography (Kansas State University, 1996), BS in Physics and BA in German (Kansas State University, 1994). She also studied at ETH Zurich (1992–1993). Research interests include geospatial technologies for humanitarian and development goals, community-engaged scholarship, and youth empowerment. Her work has been recognized with awards such as the 2024 AAG Media Achievement Award and the 2023 ASU President’s Global Engagement Award. Key roles include President of the PanAmerican Institute of Geography and History (OAS), Fulbright Specialist, and editorial board member of Professional Geographer . She has authored over 75 publications, including the 2023 Springer book Open Mapping for the Sustainable Development Goals .

Lee T. MurrayView profile

Professor

• Atmospheric Chemistry
• Climate Science
• Air Quality Modeling
• +3 more

Dr. Lee T. Murray is a Professor at the University of Rochester, leading the Atmospheric Chemistry & Climate Group within the Department of Earth & Environmental Sciences. His research focuses on the interplay between atmospheric composition and climate systems, employing advanced global models and observational data to address air quality, climate change, and big data challenges. The group uses interdisciplinary approaches combining chemistry, physics, and computational methods to understand human impacts on Earth's atmosphere. Research interests include reducing uncertainties in air quality predictions, quantifying climate change drivers, and optimizing computational methods for handling large datasets. Dr. Murray’s work spans observational studies (e.g., aircraft measurements, satellite data) and model development (e.g., GEOS-Chem, GISS-E2.1). His team collaborates across departments, including Physics & Astronomy and the Goergen Institute for Data Science. Recent publications emphasize tropospheric ozone dynamics, nitrate chemistry in the northeastern U.S., and methane emissions from landfills. The group actively promotes diversity in geosciences and recruits students through interdisciplinary Ph.D. programs. Dr. Murray’s office is in Hutchison Hall 479, with labs in Hutchison Hall 130B.

Georgios J. FakasView profile

Associate Professor

• Big Data
• Keyword Search
• Spatial Databases
• +9 more

Georgios J. Fakas is an Associate Professor (Docent) in the Department of Information Technology at Uppsala University, Sweden, where he leads the Uppsala DataBase Laboratory (UDBL). He has held academic positions at prestigious institutions including the Hong Kong University of Science and Technology, EPFL, UMIST, University of Cyprus, and Manchester Metropolitan University, where he served as a Senior Lecturer. Education: Ph.D. in Computation, UMIST, Manchester, UK (1998) M.Phil. in Computation, UMIST, Manchester, UK (1996) B.Sc. in Computation, UMIST, Manchester, UK (1995) His research spans big data, keyword search on structured and graph data, spatial databases, web and geo-social search, workflow management, and data summarization . He also explores applications in educational technologies, distance learning, and health informatics. His work emphasizes efficient, user-centric data access and intelligent querying paradigms. The 15 most recent publications highlight a sustained focus on keyword search, object summarization, spatial and semantic data, and ranking , published in top venues like SIGMOD, VLDBJ, IEEE TKDE, and PVLDB. His work integrates algorithmic innovation with practical database applications. Scientific Awards: International Sabbaticals grant from Teknat (2023), hosted by Boston University Fellowship 'Hosting of Experienced Researchers from Abroad' from RPF, Cyprus (2009) ERCIM Fellowship (2001), hosted by EPFL, Switzerland He is actively involved in PhD supervision and grant leadership. He currently serves as Principal Investigator for an eSSENCE-funded project on Data-intensive analytics for discovering critical minerals using Machine Learning , in collaboration with industry partners. He has supervised multiple PhD students to completion, including Georgios Kalamatianos, Khalid Mahmood, Zhi Cai, and Ben Cawley. He is a frequent reviewer for leading journals and serves on program committees of major conferences such as ACM SIGMOD and PVLDB. He leads the Uppsala DataBase Laboratory (UDBL) , a research group focused on advanced data management systems, where he mentors students and drives innovation in database technologies.

• Applied Artificial Intelligence
• Machine Learning
• Computer Vision
• +13 more

Christos Tachtatzis is a Professor in Applied Artificial Intelligence in the Department of Electronic and Electrical Engineering at the University of Strathclyde. He rejoined the university in 2011, was awarded a Chancellor’s Fellow in 2016, promoted to Senior Lecturer in 2018, Reader in 2021, and Professor in 2024. He leads key strategic initiatives including the Measurement, Digital and Enabling Technologies (MDET) Strategic Theme, co-directs the Laboratory for Innovation in Autism, and serves as Strathclyde lead for the UKRI AI CDT SUSTAIN. He is also a member of the HealthTech Cluster and advises The Data Lab and the Scottish Government on AI applications in agriculture and natural resources. Research Interests: His research spans applied AI with focus on computer vision, multimodal learning, domain adaptation, and explainability. These are applied to sustainable agri-food systems (livestock and arable), digital health, advanced manufacturing, and cybersecurity. His technical expertise includes deep learning, time series analysis, anomaly detection, remote sensing, hyperspectral imaging, and edge/cloud computing analytics. Recent Research Trends: His recent publications reflect a strong trend toward interdisciplinary AI applications, including environmental monitoring via satellite imagery inpainting, urban CO2 emission modeling, synthetic data generation for power grids, infant behavioral analysis, and precision livestock farming using monocular depth estimation. These works highlight his focus on real-world, data-driven solutions across environmental, health, and industrial domains. Scientific Awards: Innovate UK KTP Engineering Excellence Award (2021) Finalist, Herald Higher Education Awards – Outstanding Business Engagement (2022) Strathclyde Team Medal for Innovation in Autism (2018) SIN 2014 Best Paper Award Advising and Grants: He is actively involved in supervising research and leading externally funded projects from UKRI, InnovateUK, and H2020. He is Principal Investigator on multiple grants including Deep Learning for Woodland Soil Biodiversity, FLORA-SAGE (federated learning in agriculture), and the UKRI AI CDT SUSTAIN. He is a co-investigator on projects in digital dairy, infant interaction, and species assessment. He welcomes PhD students and regularly advertises opportunities through SUSTAIN and his professional networks. Labs and Teams: He co-directs the Laboratory for Innovation in Autism and leads the MDET Strategic Theme. He is embedded in the SUSTAIN CDT and collaborates extensively with the HealthTech Cluster, contributing to interdisciplinary research at the intersection of AI, engineering, and societal challenges.

Dujuan YangView profile

Assistant Professor

• Urban Planning
• Smart Cities
• Energy Systems
• +5 more

Dujuan Yang is an Assistant Professor in the Department of the Built Environment at Eindhoven University of Technology (TU/e). Her research focuses on Travel Behavior and Energy Effects, Urban Infrastructure Management, Energy Neutral City Development, and Decision Support Systems in Smart Cities. She leads the TU/e Smart Cities program's Urban Data & Data Platform initiative and has expertise in quantitative methods for urban sustainability. Dr. Yang holds a Ph.D. from TU/e (2013 Prestige Grant recipient), MSc from Harbin Institute of Technology, and BSc from Southeast University. She has co-authored over 50 peer-reviewed articles in journals like Transportation Research Part C and Applied Energy , and led projects like Triangulum and DESENT. She serves as Guest Editor for Urban Planning and reviewer for 15+ journals. Her research bridges urban data analytics with policy impact, emphasizing digital twins for energy efficiency, evacuation safety, and occupant comfort. Notable contributions include frameworks for sustainable urban energy systems and methodologies for analyzing household energy adaptation strategies under policy changes. Key Projects: Triangulum (Smart Cities Implementation), DESENT (Decision Support Systems) Awards: WCTR Prestige Grant (2013) Grants: €2.5M+ secured through EU Horizon 2020 and Dutch funding Dr. Yang's work integrates smart technologies with human-centric design, addressing challenges like climate resilience and equitable urban development through data-driven solutions.

• Computer Science
• Knowledge Acquisition
• Fault Detection
• +3 more

Dr Blair David Brown is a Researcher in Electronic And Electrical Engineering at the University of Strathclyde. His work focuses on predictive monitoring systems, fault detection in industrial plants, and renewable energy grid security. He leads projects such as the AI Utilisation Practices review for ScottishPower and SF6 Escape Prediction for National Grid Electricity Transmission. Collaborations include work on transfer learning approaches for asset management and surrogate models for grid stability analysis. Research Interests: His expertise spans knowledge acquisition systems, data-centric engineering, and application of machine learning to industrial challenges. He co-supervises doctoral research in nuclear asset lifecycle management and has contributed datasets for structural health monitoring validations. Projects: Currently active in 6 research projects including strategic AI applications and grid security. Recent activities include participation in Applied AI Workshops and Generative AI in Financial Services events. Advising: Supervised PhD candidate Jennifer Blair's thesis on nuclear asset analytics. Involved in interdisciplinary collaborations across engineering and data science domains.

• Machine Learning
• Signal Theory and Communications
• Structural Engineering
• +4 more

César Peláez Rodríguez is an Assistant Professor at the Department of Signal Theory and Communications, University of Alcalá. He is affiliated with the GHEODE research group (Modern Heuristics and Network Design Research Group) within the School of Electrical Engineering. His research focuses on machine learning applications in structural engineering, weather forecasting, and optimization. He earned his PhD from the University of Valladolid in 2024, with a thesis on machine learning for non-deterministic actions in slender structures. Key research areas include data-driven modeling of extreme events, hybrid machine learning systems for energy grids, and spatio-temporal analysis of climate phenomena. His work combines AI techniques with domain-specific challenges in civil engineering and renewable energy. Recent contributions address resilience to wind extremes, heatwave drivers, and fog-related low-visibility prediction using ensembles and fuzzy logic. Publications highlight innovations in autoencoder frameworks for forecasting, stochastic pedestrian modeling, and explainable AI approaches for hospital emergency predictions. Collaborations span academia and industry, emphasizing practical implementations of machine learning solutions.

• Industrial Engineering
• Engineering Management
• Lean Manufacturing
• +13 more

M. Affan Badar is a tenured Professor in the Department of Applied Engineering & Technology Management at the Bailey College of Engineering & Technology, Indiana State University (ISU). He has held key leadership roles including Director of the PhD in Technology Management (since 2022), Interim Associate Dean (2014–2015), and Department Chair (2010–2014). He also served as Professor and Chair at the University of Sharjah (UAE) from 2016 to 2018. His research spans critical domains such as Lean Six Sigma, Sustainable Supply Chain Management, Quality Engineering, Cost of Quality, Industry 4.0, and Data Analytics in higher education and healthcare. His work integrates industrial engineering principles with real-world applications in public policy, education finance, and health systems optimization. The recent publications highlight a strong trend toward interdisciplinary research, combining machine learning with quality assurance, blockchain in healthcare, and policy analysis of energy and education systems. His scholarly output includes numerous journal articles, book chapters, and conference proceedings, with a focus on practical problem-solving and systemic improvement. IEOM Fellow Award (2022) Theodore Dreiser Distinguished Research/Creativity Award (2023) National Award for Excellence in Education 2024 (AMP, India) Multiple Best Paper and Leadership Awards from IEOM Society Marquis Who’s Who Lifetime Achievement and multiple listings Dr. Badar has secured significant research funding from NSF, Lilly Foundation, SBA, and internal grants, supporting projects in technology education, healthcare modeling, and innovation. He actively mentors students and serves as faculty advisor for the IEOM student chapter. His service extends to ABET accreditation as a commissioner and leadership in professional societies. He leads and contributes to major collaborative research initiatives, especially in data-driven decision-making for public institutions and sustainable operations. His lab and team activities are strongly oriented toward experiential learning and community engagement, particularly through NSF-funded educational projects like CULMINATE and STARS.

Max KilgerView profile

Professor

• Motivations of malicious online actors
• Equivalency of kinetic and cyber attacks
• Terrorism and cyberterrorism
• +3 more

Max Kilger, Ph.D., is a Professor of Practice with joint appointments in the Management Science & Statistics Department and the Department of Information Systems & Cyber Security at the University of Texas at San Antonio (UTSA). He is a core faculty member of the UTSA School of Data Science and currently serves as the Academic Director of the UTSA IC CAE Critical Technology Studies Program, which prepares students for careers in the U.S. Intelligence Community. He holds a Ph.D. in Social Psychology from Stanford University and has over 20 years of expertise in information security, focusing on social and psychological factors influencing malicious online actors, hacking groups, and cyberterrorists. Education: Ph.D. in Social Psychology, Stanford University M.A., Stanford University B.A., Oregon State University Research Interests: Dr. Kilger’s work explores motivations behind malicious online activities, cyberterrorism, the equivalence of kinetic and cyber attacks, data fusion, and national security policy in the cyber domain. He emphasizes interdisciplinary approaches to understanding and mitigating cyber threats, particularly through behavioral analysis and policy frameworks. Professional Contributions: He co-authored influential books like Reverse Deception and Deception in the Digital Age , and contributes to national and international cybersecurity initiatives. He is a founding board member of The Honeynet Project, a member of NATO’s Science for Peace and Security Program, and a speaker for the U.S. State Department’s SUSI program. His research spans NATO counterterrorism training, digital transformation challenges during crises, and emerging cyber threats. Teaching & Leadership: He teaches courses on national security policy, cyber-human interactions, and statistical methods in business. His leadership roles include directing the Master in Data Analytics program and advising on critical infrastructure protection strategies.