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Isaac Lera CastroView profile

Associate Professor

• Computer Architecture
• Performance Evaluation of Computer Systems
• Cloud Computing
• +4 more

Dr. Isaac Lera Castro is an Associate Professor at the University of the Balearic Islands, School of Mathematics and Computer Science, Department of Computer Architecture and Technology. He serves as Deputy Director of the Laboratory of Artificial Intelligence Applications (LAIA) and is a member of the ACSIC (Architecture and Behavior of Computer and Telecommunication Systems) R&D Group. His educational background includes a Ph.D. in Computer Science from the University of the Balearic Islands (2012) and a Computer Engineering degree from the same institution (2006). He has been actively involved in academia since 2005. Dr. Lera Castro's research focuses on computer architecture, performance evaluation of computer systems, cloud computing, edge computing, fog computing, and semantic web. His work has particular emphasis on simulation and modeling of distributed systems, with significant contributions to fog computing architectures and performance assessment methodologies. He has developed YAFS (Yet Another Fog Simulator), a tool for simulating IoT scenarios in fog computing environments that has gained recognition in the research community. His publication record includes multiple papers in JCR-SCI indexed journals, with 11 highly relevant publications (7 in Q1 and 4 in Q2) and 6 relevant publications (3 in Q3 and 3 in Q4) as of 2019. His research spans from early work on semantic web applications to recent contributions in fog computing and IoT simulation, showing a consistent trajectory of innovation in distributed systems. 2019: YAFS simulator for IoT scenarios in fog computing (IEEE Access) 2019: Availability-aware service placement in fog computing (IEEE IoT Journal) 2017: Human mobility pattern analysis using complex networks (PLOS ONE) 2006: Performance-related ontologies and semantic web applications (Science of Computer Programming) Dr. Lera Castro has extensive teaching experience across undergraduate, graduate, and master's programs. He has taught core subjects including Computer Architecture, Current Computer Systems, and Evaluation and Exploitation of Computer Systems, as well as specialized courses like Cloud Computing and Technologies for Big Data Analysis. From 2018 to 2021, he served as co-director of the Master's Degree in Big Data Analysis in Economics and Business. He leads the Laboratory of Artificial Intelligence Applications (LAIA), which focuses on applying AI techniques to distributed systems with particular expertise in performance modeling and resource allocation in cloud, fog, and edge computing environments.

Pankaj MehraView profile

Research Professor

• Memory Systems
• Parallel and Distributed Computing
• Artificial Intelligence
• +7 more

Pankaj Mehra is a Research Professor in the Department of Computer Science and Engineering at The Ohio State University and CEO of Elephance Memory, a company he founded that develops software for disaggregated data center memory optimization. He holds a Ph.D. in Computer Science from The University of Illinois at Urbana-Champaign and has extensive industry leadership experience including SVP/WW CTO at Fusion-io, VP/Senior Fellow roles at SanDisk and Western Digital, and VP positions at Samsung where he led SmartSSD development. His research focuses on memory-semantic fabrics (CXL, UALink), Memory Objects abstraction for data-centric programming, and AI Super Devices (AISDs) for near-data processing in AI workloads. Key interests include optimizing memory systems for Retrieval Augmented Generation (RAG), vector databases, and Approximate Nearest Neighbor Search (ANNS) algorithms. His notable scientific awards include: Samsung R&D Award (2019) for SmartSSD development CES R&D Innovation Award (2021) for SmartSSD Dr. Mehra founded HP Labs Russia and served as Chief Scientist until 2010. He is an active industry contributor to the Open Compute Project and DOE EMC3 initiatives, with scheduled presentations at the 2025 OCP Global Summit on composable memory systems and data-centric computing. His entrepreneurial ventures include Elephance Memory, IntelliFabric, Whodini, and AwarenaaS, with publications spanning 3 books and over 100 papers and patents in memory technologies and distributed systems.

Amelie JuhinView profile

Researcher

• Magnetic Spectroscopy
• Synchrotron Radiation
• Nanoparticles
• +5 more

Amélie Juhin is a Permanent Research Scientist (CR1) at the French National Center for Scientific Research (CNRS) based at the Institut de Minéralogie, Physique des Matériaux et Cosmochimie (IMPMC) within Sorbonne University. She has managed the MIMABADI research team focused on low-dimensional mineralogy and magnetism since 2010. Her expertise centers on magnetic spectroscopies using synchrotron radiation, particularly X-ray Magnetic Circular Dichroism (XMCD) and Resonant Inelastic X-ray Scattering (RIXS-MCD), with applications in molecular magnetism, nanoparticles, and ferrofluids. Her research explores three primary themes: (1) Molecular magnetism and photomagnetism in grafted molecular magnets, (2) Development of hard X-ray magnetic spectroscopies (K-edge XMCD/RIXS-MCD) for bulk-sensitive measurements, and (3) Theoretical modeling of core-level spectroscopies using Ligand Field Multiplet Theory and Density Functional Theory. She has pioneered new methodologies for studying magnetic nanomaterials under extreme conditions using specialized sample environments. Her extensive publication record shows consistent focus on magnetic spectroscopy development and applications in nanomaterials. Recent work demonstrates advanced characterization of magnetic anisotropies in ferrofluids, electronic structure in transition metal oxides, and innovations in RIXS-MCD techniques. Scientific Awards: ESRF Young Scientist Award (2017) CNRS Bronze Medal - Highest distinction for young scientists (2016) Farrel Lytle Prize - International X-ray Absorption Society (2015) CNRS Award of Scientific Excellence (2012) ESRF Best Poster Award (2010) Best Communication Award - International Conference on Defects in Insulating Materials (2008) She leads research activities at the IMPMC laboratory and collaborates internationally with synchrotron facilities including ESRF and SOLEIL. Her team develops experimental methodologies and theoretical frameworks for understanding magnetic phenomena at atomic scales.

Stefan WagnerView profile

Professor

• Software Quality
• AI-Supported Software Engineering
• Empirical Studies
• +3 more

Stefan Wagner is a full professor of software engineering at the Technical University of Munich (TUM), where he leads the Chair of Software Engineering within the Informatics Heilbronn 3 department. He earned his PhD in computer science from TUM and has established himself as a leading researcher in software engineering with a unique interdisciplinary background combining computer science and psychology. Dr. Wagner's research spans multiple areas of software engineering including software quality, human factors, AI-based software engineering, automotive software, and empirical studies. His work often bridges theoretical foundations with practical applications, particularly in the automotive domain and AI-assisted development. He has published over 130 peer-reviewed scientific articles and authored the book 'Software Product Quality Control.' His recent publications demonstrate a growing focus on AI integration in software engineering, with particular attention to large language models, empirical validation of AI-assisted development practices, and the human aspects of these emerging technologies. There's also a strong thread of research on automotive software systems, technical debt, and software quality measurement. 2022 Class of IEEE Computer Society Distinguished Contributors Senior member of IEEE and ACM Best Full Paper Award, ACM/IEEE International Symposium on Empirical Software Engineering and Measurement 2020 Best Paper Award, EAI International Conference on Cognitive Computing and Cyber Physical Systems 2020 Keynote at the International Conference on Software Quality 2020 Google Research Award 2009 Dr. Wagner actively mentors students and early-career researchers, with several frequent co-authors on his publications likely representing his advisees. His research has been supported by various funding sources enabling his work on automotive software, AI in software engineering, and empirical studies. He serves on the editorial boards of IEEE Software, Empirical Software Engineering, and the Journal of Systems and Software, contributing significantly to the academic community. His research group appears to focus on several key areas including AI-assisted software development, automotive software systems, and empirical software engineering methods. The group maintains active collaborations with industry partners, particularly in the automotive sector, and engages in interdisciplinary research bridging computer science with psychology and human factors.

• Medical bioinformatics
• Inflammatory skin diseases
• Multidrug resistance in cancer
• +8 more

Thomas Litman is a Professor in the Department of Immunology and Microbiology at the University of Copenhagen's Faculty of Health and Medical Sciences, where he leads bioinformatics research at the Skin Immunology Research Center. With expertise spanning multiple omics technologies, he applies computational approaches to understand complex biological systems, particularly in the context of inflammatory skin diseases and cancer biology. Dr. Litman earned his PhD from the University of Copenhagen in 1996 with research focused on 'The multidrug resistant phenotype - a comparative study.' His academic journey has positioned him at the intersection of computational biology and medical research. Professor Litman's research centers on medical bioinformatics, with particular emphasis on inflammatory skin diseases including atopic dermatitis, psoriasis, and cutaneous T-cell lymphoma. He investigates multidrug resistance in cancer, utilizing transcriptomics, metabolomics, microbiome analysis, and proteomics to develop integrated 'skinomics' approaches. His work focuses on identifying molecular biomarkers with diagnostic, prognostic, and predictive value, especially for characterizing endotypes of inflammatory skin conditions. Through structural bioinformatics and translational research using cellular models, 3-D models, and clinical data, he bridges computational analysis with real-world medical applications. His recent publication record demonstrates a strong focus on applying multi-omics approaches to dermatological conditions, with significant contributions to understanding chronic hand eczema, basal cell carcinoma, and cutaneous T-cell lymphoma. His work increasingly integrates clinical data with molecular profiling to identify biomarkers and therapeutic targets, reflecting a trend toward more personalized approaches in dermatology and oncology. Professor Litman actively supervises bachelor's, master's, and PhD students in applied bioinformatics, encouraging the next generation of researchers to explore the 'data jungle' through computational analysis. His research is supported by collaborations with LEO Pharma and other industry partners, facilitating translational research from bench to bedside.