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Frederick E. SpadaView profile

Researcher

• Data Security
• Magnetic Materials
• Thin Film Technology
• +3 more

Fred Spada is an Associate Research Scientist at the Center for Magnetic Recording Research (CMRR) at the University of California, San Diego (UCSD). He holds a Ph.D. in Physical Chemistry from UCSD (1983) and previously worked at Eastman Kodak Research Laboratories (1983–1989). His research focuses on secure data erasure via bulk degaussing methods, structure-property relationships in magnetic materials (thin films and nanoparticles), and chemical aspects of wear. His work spans magnetic recording media, nanomaterial synthesis, and surface characterization. Education: Ph.D. in Physical Chemistry, UCSD, 1983 Research Interests: Evaluation and standardization of bulk degaussing techniques Magnetic material properties (anisotropy, magnetoresistance, phase transformations) Nanoparticle synthesis via spark erosion Surface treatments for enhanced magnetic performance Recent Research Trends: Recent publications emphasize secure data erasure in solid-state drives and high-density storage media, alongside continued exploration of magnetic thin films and nanomaterial characterization. His work bridges fundamental material science with applied technologies in data storage and magnetic devices. Awards & Grants: No scientific awards listed. Active in collaborative research with industry partners like Eastman Kodak and academic institutions. Lab & Team: Leads CMRR research group with lab assistant Joanne Shin, focusing on magnetic materials and data security applications.

Christian CachinView profile

Professor

• Cryptography
• Blockchain Technology
• Distributed Systems
• +5 more

Prof. Dr. Christian Cachin is a Professor at the Institute of Computer Science of the University of Bern, Switzerland. He leads the Cryptology and Data Security research group and serves as Deputy Director of the Institute. His work focuses on cryptography, blockchain technology, and distributed systems, with particular emphasis on consensus protocols, privacy-preserving technologies, and secure multi-party computation. He has contributed to foundational research in threshold cryptography, transaction graph models, and DAG-based consensus mechanisms. Prof. Cachin's research spans theoretical and applied aspects of distributed systems, including blockchain scalability, consensus mechanisms (e.g., Avalanche, Proof-of-Stake), and privacy-enhancing technologies like secure aggregation and untraceable payments. His group develops practical implementations, such as the Thetacrypt threshold cryptography service and analyses of protocols like FastPay and Inter-Blockchain Communication. He has authored over 150 publications in top venues, including the 2021 Principles of Distributed Computing Doctoral Dissertation Award. His work bridges academic theory and real-world applications, addressing challenges in decentralized systems, smart contract security, and blockchain interoperability.

• Power Systems Engineering
• Integrated Energy Systems
• Cyber-Physical Systems
• +3 more

Dr. Suhan Zhang is a Researcher in the School of Electrical and Electronic Engineering at the University of Sheffield, specializing in power systems engineering and integrated energy systems. His research focuses on optimizing cross-sector energy systems, cybersecurity in cyber-physical infrastructure, and developing advanced simulation and optimization methods for gas-electricity coupling, multi-timescale security analysis, and distributed energy resource management. He leads projects on fast gas flow calculation, dynamic energy flow analysis, and AI-driven approaches for energy storage system vulnerabilities. His work bridges theoretical advancements with practical applications in smart grid technologies and energy market mechanisms. Key research areas include: Integrated electricity-gas-heating systems Cyber-physical interdependence analysis Optimization under uncertainty Physics-informed machine learning Energy storage system security Multi-scale energy market design Recent contributions highlight novel methods like semi-implicit simulation approaches for fault propagation analysis, physics-informed neural networks for gas flow modeling, and truthful combinatorial auctions for regulation reserve aggregation. His work is published in top-tier journals and conferences, addressing both foundational and applied challenges in energy systems engineering.

• Toxicology
• Environmental Health
• Risk Assessment Methodology
• +4 more

Annika Hanberg is a Professor of Toxicology at the Institute of Environmental Medicine at Karolinska Institutet, Sweden. She serves as Programme Director for the Global Master's Programme in Toxicology since 2006 and has been a leading figure in health risk assessment for national agencies, EU bodies, and the WHO since the 1980s. Her work focuses on methodological advancements in risk assessment, including systematic reviews, mixture toxicity, endocrine disruptors, and dose-response evaluation. She co-leads the Health Risk Assessment Methodology Group under Anna Beronius and is a key member of the Horizon Europe-funded PARC (Partnership for Risk Assessment of Chemicals) initiative. Research & Expertise: Her expertise spans experimental toxicology, risk assessment method development, and regulatory support. She has pioneered frameworks for evaluating non-monotonic dose responses and chemical mixtures. She organizes international training courses in risk assessment methodologies and has contributed to EFSA guidelines on uncertainty analysis and weight-of-evidence approaches. Grants & Collaborations: Active in major projects such as PARC (2022–2029) and SciRAP (Swedish Research Council), focusing on improving risk assessment tools and transparency. She has secured funding for studies on gender-specific chemical risks and the implementation of alternative toxicology methods. Professional Roles: Dr. Hanberg is an European Registered Toxicologist , Orcid-linked researcher, and LinkedIn-profiling academic. She advises on regulatory science and participates in global initiatives to strengthen chemical risk analysis capacities, particularly in Nordic regions.

Alexander L. WolfView profile

Professor

• distributed systems
• networking
• software engineering
• +3 more

Alexander L. Wolf is the Dean of the Baskin School of Engineering and a Distinguished Professor of Computer Science and Engineering at the University of California, Santa Cruz. He holds a B.A. in Geology and Computer Science from Queens College (CUNY), and M.S./Ph.D. degrees from the University of Massachusetts Amherst. His career includes foundational roles at AT&T Bell Laboratories, the University of Colorado (where he held the Charles Victor Schelke Chair), the University of Lugano (founding the Faculty of Informatics), and Imperial College London. Wolf's research bridges distributed systems , networking , and software engineering , with recent projects in cloud computing, data-center networking, and mobile ad hoc networks (MANETs). His work emphasizes scalable architectures, fault tolerance, and adaptive service deployment. Key projects include HARNESS (hardware-enhanced cloud systems) and SERECA (secure cloud enclaves). His publications focus on optimizing networked systems, fault localization, and adaptive resource management. Trends include rigorous simulation-based validation, cross-layer optimization (e.g., integrating GPUs/networking), and practical applications in geosciences (Reverse-Time Migration) and machine learning (Bing's AdPredictor). Awards: ACM/IEEE/AAAS Fellow; Royal Society-Wolfson Research Merit Award; Two-time ACM SIGSOFT Research Impact Award; ACM SIGSOFT Outstanding Research & Distinguished Service Awards. Wolf leads major grants (e.g., EU H2020 SERECA, EPSRC NaaS) and has chaired ACM's Executive Committee. He founded ACM's Europe Council and contributed to seminal tools like the Siena publish/subscribe system. His team develops experimental platforms (e.g., Weevil for distributed testbeds) and collaborates with industry (AT&T, Microsoft Bing).

• Biomaterials Engineering
• Peptide Self-Assembly
• Hydrogel Design
• +5 more

Aline Miller is a Professor of Biomolecular Engineering at The University of Manchester, serving as Associate Dean for Business Engagement and Innovation within the Faculty of Science and Engineering, and Chief Scientific Officer of Unit M. She leads the NW Industrial Biotechnology Innovation Catalyst (£5m flagship program) and previously co-founded Manchester BIOGEL, a biotech startup acquired by Cell Guidance Systems in 2023. Her roles include Director of the Bio-Based and Biodegradable Industries Association and Elected Trustee of the Royal Society of Chemistry. Education: B.Sc. Chemistry (Strathclyde University), PhD in Polymer Science (Durham University), postdoctoral work at Cavendish Laboratory (Cambridge) Affiliations: Royal Society of Chemistry Biomaterials Committee (2008–14), Institute of Physics Polymer Physics Group (2009–20) Research Interests: Peptide self-assembly, biomaterial design, tissue engineering, and industrial biotechnology applications Her research focuses on peptide/protein self-assembly across length scales for material design, with key themes in therapeutic biomaterials, ice-crystallization control at interfaces, and biopharmaceutical applications. Recent work includes developing PeptiGels® hydrogels for organoid culture and drug delivery systems. Over 80 peer-reviewed articles highlight her contributions to biomaterials science. Awards include the Royal Society of Chemistry MacroGroup UK Medal (2025), Northern Power Women’s Award (2025), and Philip Leverhulme Prize (2014). She has secured £4M+ in venture funding for Manchester BIOGEL, which ranked among Europe’s top biotech startups (2021). Leadership roles span academic-commercial partnerships, innovation programs, and industry advisory boards. Current projects include bioelectronics networks, robotics-AI initiatives, and regenerative medicine platforms.

Priyanka SinghView profile

Lecturer

• Cyber Security
• Digital Forensics
• Privacy and Security Aspects
• +5 more

Dr. Priyanka Singh is a Lecturer in Cyber Security at the School of Electrical Engineering and Computer Science, University of Queensland. She holds a PhD in Image Forensics and has conducted postdoctoral research at SUNY Albany and Dartmouth College, collaborating with Prof. Hany Farid. Her research focuses on Cyber Security, Digital Forensics, Privacy, Homomorphic Encryption, and Cloud Computing applications. Key contributions include real-time child pornography detection and privacy-preserving frameworks for digital authentication. Education: PhD in Image Forensics (university unspecified), postdoctoral work at SUNY Albany and Dartmouth College. Notable collaborations include a talk invitation at MIT by Prof. Ramesh Raskar. Research Interests: Cyber Security mechanisms, Digital Forensics techniques, Privacy-Preserving algorithms, Homomorphic Encryption protocols, and Cloud Security solutions. Recent Articles: Focus on AI ethics (e.g., FakeFaceDiscriminator), privacy-preserving biometrics (e.g., IRIS-SAFE), and secure anomaly detection (e.g., SADHE). Her work spans 42 conference papers and 22 journal articles, addressing challenges like encrypted video tampering detection and federated learning resilience. She advocates for technology's societal impact through explainable AI and ethical AI use cases.

• Power Systems Operation and Optimisation
• Power System Operation and Planning
• Grid Integration of DER
• +2 more

Ahmad Attarha is a Research Fellow at the School of Computing , College of Engineering and Computer Science , Australian National University (ANU). He recently submitted his PhD thesis and holds a B.Sc. and M.Sc. in Electrical Engineering from Semnan University, Iran (2012 and 2015). Education: B.Sc. (2012), M.Sc. (2015) in Electrical Engineering Current Role: Research Fellow in Power Systems and Smart Grids His research focuses on power systems operation and optimisation , with specific emphasis on Grid Integration of Distributed Energy Resources (DER) , Distributed Optimisation , and Robust Optimisation techniques for distribution networks. Publications highlight trends in DER aggregation , shaped operating envelopes , and robust optimization for distribution systems. Key areas include voltage regulation , network security constraints , and price-sensitive bidding strategies in energy markets. He is affiliated with the Smart Grid group at ANU and contributes to projects related to grid flexibility , distributed battery storage , and renewable energy integration .

Matthew J. RobbinsView profile

Professor

• Operations Research
• Artificial Intelligence
• Stochastic Optimization
• +9 more

Dr. Matthew J. Robbins is a Professor of Operations Research in the Department of Operational Sciences at the Air Force Institute of Technology (AFIT). His research focuses on advancing operations research and artificial intelligence techniques for solving computational stochastic optimization problems, particularly in defense applications. He holds a Ph.D. in Industrial Engineering from the University of Illinois (2010) and has received numerous awards, including the 2024 Distinguished Teaching Professor and 2019 Best Paper Award in Omega. He serves as an associate editor for Military Operations Research and Naval Research Logistics, and on the council of the INFORMS Military and Security Society. Education: Ph.D., Industrial Engineering, University of Illinois, 2010 M.S., Operations Research, AFIT, 2005 (Distinguished Graduate) B.S., Computer Systems Engineering, University of Arkansas, 1999 Research Interests: Approximate dynamic programming and reinforcement learning for large-scale decision-making Medical evacuation dispatching and military logistics optimization Autonomous systems control and asset management Stochastic optimization and simulation-based modeling Awards: 2024 Distinguished Teaching Professor, AFIT 2018 Richard H. Barchi Prize (Military Operations Research Society) 2011 Pritsker Doctoral Dissertation Award (1st Place) Advising & Grants: Advised over 20 MS/PhD students in operations research and defense applications Recipient of research grants in military logistics, healthcare systems, and AI applications Labs/Teams: Part of AFIT's Operational Sciences research group Collaborates with military and defense organizations on applied research

Shyh Wei TengView profile

Associate Professor

• Image Processing
• Machine Learning
• Bioinformatics
• +3 more

Assoc Prof Shyh Wei Teng is an Associate Professor and Deputy Dean at Federation University Australia's Institute of Innovation, Science and Sustainability (IISS). He holds a Bachelor of Computing (First-class Honours) and PhD in Information Technology from Monash University (2004), and a Graduate Certificate in Higher Education (2008). His research focuses on image processing, machine learning, bioinformatics, and computer vision, with notable contributions to LiDAR-based building extraction, SIFT algorithm optimization, and multimodal image registration. He has secured significant grants, including an Australian Research Council (ARC) Discovery Project (2013). Prof Teng has supervised numerous PhD and master’s students, contributing to advancements in image retrieval, clustering algorithms, and biomedical applications. His work has been published in top-tier journals like Pattern Recognition and Neurocomputing , and he actively reviews for IEEE conferences. He taught courses in database systems, project management, and systems analysis, receiving teaching and community engagement nominations. Research interests span computational techniques for medical imaging, contour-based corner detection, and machine learning applications in remote sensing. His labs and collaborations include projects on augmented reality for education and ecological data analysis.

Rebecca FrankView profile

Assistant Professor

• Digital Curation
• Digital Preservation
• Digital Repositories
• +6 more

Rebecca Frank (she/her) is an Assistant Professor at the University of Michigan School of Information and holds affiliations with the Einstein Center Digital Future (Berlin) and the Inter-university Consortium for Political and Social Research. Her research examines how risk is socially constructed in digital repository certification processes, focusing on open data, digital preservation, and ethical information management. She teaches graduate courses in digital curation and preservation. PhD, University of Michigan School of Information (2018) MSI, University of Michigan (2012) BA, Organizational Studies, University of Michigan (2010) Her work addresses social and ethical barriers to digital information preservation, sharing, and reuse through projects like SCoR-TDR (Social Construction of Risk in Trustworthy Digital Repositories) and Citizen-Based Monitoring for Peace & Security (analyzing satellite imagery for conflict verification). Current research with the InfraLab Berlin investigates risk perception in public infrastructure data work. Recent publications (2024-2025) explore CoreTrustSeal certification, satellite image analysis for citizen monitoring, and qualitative method reporting standards. Her 2024 Journal of Documentation article develops frameworks for repository risk assessment, while 2025 conference papers examine feminist data approaches and collaborative syllabus development. Supported by grants from the National Science Foundation (US), German Foundation for Peace Research, Einstein Center Digital Future, and Australian Academy of Science, Frank collaborates with international institutions including Princeton University, Berliner Hochschule für Technik, and Humboldt-Universität zu Berlin. She organizes workshops on data feminism and digital preservation ethics.

Nelson VilloriaView profile

Associate Professor

• International Trade
• Agricultural Policy Analysis
• Global Land Use
• +4 more

Nelson B. Villoria is an Associate Professor in the Department of Agricultural Economics at Kansas State University . His research focuses on the intersections of international trade, development, and environmental sustainability, particularly addressing climate impacts on global agricultural systems and land-use policy. He holds a B.S. in Agronomist from Universidad Central de Venezuela (1995), M.S. in Agricultural Economics from Cornell University (2000), and Ph.D. from Purdue University (2009). Major research areas include climate-driven cropland changes, trade frictions and food price stability, and policies to mitigate deforestation. His work emphasizes spatially explicit data analysis, leveraging tools like GTAPShape and FlexAgg2.0 for geospatial modeling. Recent studies explore how technological progress and trade policies influence global land-use patterns and food security. Publications highlight themes such as yield variability under climate change, land supply elasticity, and the leverage of trade agreements (e.g., EU policies on Brazilian deforestation). His contributions bridge theoretical frameworks with applied policy analysis, often using computable general equilibrium (CGE) models and geospatial data infrastructure. Villoria has held roles like Associate Director for Educational Outreach at Purdue’s Center for Global Trade Analysis. His research consistently addresses global sustainability challenges through interdisciplinary approaches, integrating economics, environmental science, and geospatial technologies.

Bala VenkateshView profile

Professor

• Power Systems Analysis
• Optimization
• Fuzzy Optimization
• +4 more

Dr. Bala Venkatesh is a Professor in the Department of Electrical and Computer Engineering and Academic Director of the Centre of Urban Energy at Toronto Metropolitan University. He has held academic positions at institutions including Ryerson University (2008–present), the University of New Brunswick (2005–2007), Multimedia University, Malaysia (2001–2004), and Anna University, India (1994–2000). His research focuses on Power Systems Analysis, Fuzzy Optimization, and renewable energy integration. He has authored over 100 refereed papers and secured research grants exceeding $10 million. Dr. Venkatesh is a Senior Member of IEEE and a registered Professional Engineer in Ontario. Education and Professional Experience: Postdoctoral work at Crompton Greaves, Mumbai (1993) Lecturer, Anna University, India (1994–2000) Associate Professor, Multimedia University, Malaysia (2001–2004) Associate Professor, University of New Brunswick (2005–2007) Research Interests: Dr. Venkatesh specializes in fuzzy optimization applications to power systems, distribution network analysis, and energy storage integration. His work emphasizes practical solutions for grid stability, renewable energy utilization, and transactive energy systems. Recent projects include DER aggregation models, smart grid optimization, and fault diagnosis in microgrids. Grants and Recognition: He leads the Power and Energy Analysis Research Lab at Toronto Met and has secured substantial funding for projects in smart grids and energy systems. Notable awards include IEEE Senior Membership and Professional Engineer licensure in Ontario. His work has been applied in consulting projects across India and Canada.

Heidi WebberView profile

Professor

• Climate Risk Assessment
• Crop Modeling
• Plant Stress Physiology
• +3 more

Prof. Heidi Webber is a leading agricultural scientist at the Leibniz Centre for Agricultural Landscape Research (ZALF), serving as Co-Head of Program Area 3 'Agricultural Landscape Systems' and Head of the 'Integrated Crop Production Systems Analysis' working group. Her research focuses on climate risk assessment, crop stress modeling, and sustainable agronomic systems. She holds a Diplom-Agraringenieurin degree and has extensive experience in interdisciplinary studies combining biophysical and socio-economic analyses. Her expertise includes modeling plant growth under abiotic stresses and developing resource-efficient cultivation strategies. Notable contributions involve the AgMIP-Wheat initiative, high-yielding trait experiments, and climate-resilient crop systems in diverse regions like West Africa, South Korea, and Europe. She co-leads international projects addressing climate change impacts on agriculture and leads modeling efforts for crop diversification and adaptation strategies. Key research themes include: Climate risk assessment frameworks Multi-model ensemble approaches for crop yield prediction Abiotic stress tolerance mechanisms in cereals Climate-smart agricultural practices Agroecological transition in smallholder farming systems Her work bridges field experiments with advanced computational models, emphasizing data-driven solutions for sustainable intensification. Current projects explore index-based crop insurance, soil carbon dynamics, and the transformation of farming systems toward silicon-enhanced resilience.

Reda BELLAFQIRAView profile

Researcher

• Federated Learning
• Homomorphic Encryption
• Data Security
• +3 more

Reda BELLAFQIRA is an Enseignant Chercheur (Researcher) at IMT Atlantique's Data Science Department, based in Brest. His work focuses on securing sensitive data processing in distributed systems, combining cryptography with machine learning techniques. Key areas include federated learning, homomorphic encryption, and watermarking for intellectual property protection. He has contributed to privacy-preserving frameworks in healthcare and IoT applications, emphasizing secure collaborative data analysis without compromising confidentiality. Research Interests: Secure federated learning architectures and robustness against adversarial attacks Cryptography applications in AI, including homomorphic encryption for encrypted data processing Watermarking techniques for model integrity and ownership in distributed environments Privacy-preserving methods for healthcare data (e.g., EHRs, genomics) IoT cybersecurity and embedded system security for medical devices Key Contributions: His 2025 work on blockchain-enhanced watermarking for federated learning and 2023 research on automated EHR de-identification exemplify his focus on practical security solutions. Recent trends show increasing emphasis on interdisciplinary approaches merging cryptography with healthcare informatics and IoT systems. Labs/Teams: Active in IMT Atlantique's Data Science Department research groups, collaborating on EU-funded projects related to federated learning in healthcare and secure IoT ecosystems.