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Poman SoView profile

Associate Professor

• Multiscale Modeling
• Biomedical Engineering
• Microwave CAD
• +5 more

Poman So is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Victoria, Canada. He is a Professional Engineer (P.Eng) registered in British Columbia and holds memberships in IEEE (Senior Member), ACES, and CMBES. Dr. So co-founded Faustus Scientific Corporation, creator of MEFiSTo electromagnetic field modeling software. Prior to joining UVic in 1998, he worked as senior scientific staff at MDA in Quebec. Education: Ph.D. in Electrical Engineering (University of Victoria) M.A.Sc. and B.A.Sc. in Electrical Engineering (University of Ottawa) B.Sc. (University of Toronto) Research Interests: Focuses on multiscale electromagnetic field modeling, biomedical electromagnetics and instrumentation, time-domain microwave circuit analysis, and open-source computational electromagnetics (CEM) tools. His work integrates GPU-based parallel computing and meta-material applications in microwave CAD. Professional Activities: Administers the Talbot Memorial Fund Awards, established to honor engineering students based on academic excellence, community service, and leadership. Since 2007, the fund has awarded two $2500 scholarships annually. Teaching: Instructs courses including ECE 216 (Electricity and Magnetism), ECE 335 (Biosensors and Instrumentation), and ECE 521 (Computational Electromagnetics). Labs/Teams: Leads research in biomedical engineering instrumentation and microwave circuit design through Faustus Scientific’s MEFiSTo platform, emphasizing open-source software development.

• Model-Based Systems Engineering
• Software Development
• Aerospace Engineering
• +4 more

Konstantinos KANAVOURAS is a Doctoral Researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) within the University of Luxembourg, specifically in the Space Systems Engineering research group (SpaSys). He is advised by Prof. Andreas Hein and focuses on model-based systems engineering, software development, and aerospace engineering applications in satellite systems. His research integrates agile methodologies and machine learning for spacecraft design and anomaly detection. Kanavouras holds a Master’s degree from Aristotle University of Thessaloniki (2021) and contributed as an avionics engineer to ESA’s AcubeSAT nanosatellite project under the Fly Your Satellite! program. His work emphasizes lightweight data management tools, PocketQube missions like POQUITO, and fractionated satellite systems for planetary observation. His publications highlight trends in small satellite development, including agile systems engineering practices, thermal anomaly detection via machine learning, and adapting space projects to remote collaboration (e.g., during the pandemic). Key projects include the University of Luxembourg’s first PocketQube mission (POQUITO) and lean approaches to spacecraft subsystems. Current affiliations include the SpaSys group at SnT, with a focus on interdisciplinary collaboration between systems engineering and software development. No scientific awards are listed, but his work aligns with cutting-edge space technologies and mission design.

• Numerical Linear Algebra
• Numerical Nonlinear Algebra
• Parallel Computing
• +7 more

Prof. Zhong-Zhi Bai is a Professor of Computational Mathematics at the Institute of Computational Mathematics and Scientific/Engineering Computing, part of the Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, Beijing. He is based at the State Key Laboratory of Scientific/Engineering Computing, a leading institution in applied mathematics and high-performance computing in China. His research spans a broad range of topics in computational mathematics, with a strong emphasis on numerical linear and nonlinear algebra , parallel computations , numerical optimization , and sparse matrix techniques . He has made significant contributions to the development and analysis of preconditioners and numerical methods for differential-algebraic equations and partial differential equations . His work is foundational in advancing iterative solvers and large-scale scientific simulations. The available publications, including the notable book Milestones in Matrix Computation (2007), reflect a long-standing engagement with matrix computation and numerical algorithms. The research trends indicate a deep focus on theoretical and practical aspects of numerical methods, particularly in the context of high-performance and scientific computing environments. Prof. Bai serves on the editorial boards of several leading journals in the field, including: Applied Numerical Mathematics Communications on Applied Mathematics and Computation Computational and Applied Mathematics East Asian Journal on Applied Mathematics Electronic Transactions on Numerical Analysis Journal of Computational and Applied Mathematics Journal of Mathematical Study Journal of Scientific Computing Numerical Algorithms Numerical Linear Algebra with Applications He has advised students and mentored researchers, though specific names are not listed. His work is supported by institutional affiliations and likely national research grants, given his position in a State Key Laboratory. He has developed software tools and delivered lecture series, contributing to both research and education in computational mathematics. Prof. Bai is actively involved in the numerical linear algebra community and maintains a comprehensive academic presence, including publications, editorial service, and software contributions. He leads or participates in research teams focused on advancing computational methods within the State Key Laboratory framework.

• Scientific Computing
• Numerical Analysis
• Applied Mathematics
• +5 more

Eirik Valseth is an Associate Professor of Scientific Computing at the Norwegian University of Life Sciences (NMBU), Department of Data Science. He holds concurrent roles as a research associate at the Oden Institute, University of Texas at Austin, and an affiliated researcher at Simula Research Laboratory (Department of Numerical Analysis and Scientific Computing). His expertise lies in advanced finite element methods for PDEs with applications in flood modeling and hydropower systems. Current Affiliation: NMBU (Norwegian University of Life Sciences) Secondary Affiliations: Oden Institute (UT Austin), Simula Research Laboratory Research interests span numerical methods for challenging PDE systems, including: Stabilized finite element formulations Hurricane storm surge and riverine flood modeling Hydropower infrastructure analysis Computational mechanics and applied mathematics His recent publications (2024–2025) emphasize flood risk assessment (compound flooding, dam breaks, dredging impacts), advanced numerical methods (isogeometric analysis, stochastic finite elements, graph-grammar algorithms), and environmental applications (pollution transport, pathogen distribution, mosquito population dynamics after hurricanes). Key trends include cross-disciplinary integration of physics-aware machine learning and robust hydrodynamic simulation tools. Valseth's work extends to software development (e.g., WAVEx for spectral wave models, SWEMniCS for coastal circulation) and large-scale modeling frameworks like the ADCIRC unstructured mesh model for US coasts. Collaborative projects involve institutions such as University of Texas at Austin, Simula, and NOAA.

• Computational Materials Science
• 2D Materials
• High-Entropy Ceramics
• +5 more

Dr. Rico Friedrich is a computational materials scientist leading the "Autonomous Materials Thermodynamics - AutoMaT" research group, jointly operated by the Chair of Theoretical Chemistry at Technische Universität Dresden and the Helmholtz-Zentrum Dresden-Rossendorf (HZDR). His work focuses on data-driven computational design of advanced materials for information technology and energy applications through the DRESDEN-concept research alliance. His research spans several cutting-edge areas: Discovery and design of 2D non-van der Waals materials with novel electronic and magnetic properties Data-driven modeling of high-entropy ceramics based on entropy maximization principles Development of computational methods for accurate thermodynamic stability prediction, particularly the coordination corrected enthalpies (CCE) method Applications of artificial intelligence in materials design Dr. Friedrich's publication record shows a strong trend toward computational materials discovery, with significant contributions to understanding non-van der Waals 2D materials and high-entropy ceramics. His work bridges theoretical developments with practical applications, resulting in publications in high-impact journals including Nature, Nano Letters, and Advanced Electronic Materials. His key scientific contributions include: Development of the coordination corrected enthalpies (CCE) method for accurate formation enthalpy calculations Creation of the AFLOW-CCE module implemented in the AFLOW software ecosystem Discovery of novel 2D non-van der Waals materials with ultra-low exfoliation energies Formulation of the disordered enthalpy-entropy descriptor (DEED) for high-entropy ceramics Dr. Friedrich actively mentors the next generation of materials scientists, currently supervising PhD students and postdoctoral researchers in his AutoMaT lab. His research group collaborates extensively within the DRESDEN-concept research alliance, leveraging computational resources and expertise across multiple institutions to advance materials science and engineering.

Mayank GoelView profile

Assistant Professor

• Mobile Computing
• Sensing
• Signal Processing
• +7 more

Mayank Goel serves as an Assistant Professor in the Software and Societal Systems Department (S3D) at Carnegie Mellon University's School of Computer Science. His research bridges computer science and societal impact through practical sensing systems that leverage existing environmental devices for health monitoring and human-computer interaction without requiring hardware modifications. Dr. Goel specializes in mobile computing, signal processing, and machine learning to develop unobtrusive health technologies applicable to real-world scenarios. His core research areas include passive activity recognition for chronic disease management (particularly multiple sclerosis), privacy-preserving acoustic sensing, smartwatch-based clinical interventions for post-operative care, and equitable healthcare systems for global development contexts. He emphasizes end-to-end solutions through close collaboration with medical professionals and designers to ensure immediate deployability outside laboratory environments. Analysis of his 2024-2025 publications reveals a strong interdisciplinary focus spanning computer science, biomedical engineering, and clinical practice. Key trends include longitudinal digital phenotyping for neurological conditions, on-device privacy preservation in activity recognition, and multimodal procedural assistance systems. His work consistently addresses real-world challenges in sensor placement flexibility, user adoption barriers, and equitable access to medical technologies. No scientific awards were mentioned in the available documentation. Information regarding student advising, research grants, or laboratory affiliations was not specified in the provided materials, though his publication record indicates active collaboration with medical professionals and bio-engineers for clinical validation of health technologies.

• Software Engineering
• Societal Computing
• Privacy Engineering
• +3 more

Andrew Ilyas serves as an Assistant Professor in the Software and Societal Systems Department (SSSD) within Carnegie Mellon University's School of Computer Science, holding a core faculty position focused on the societal dimensions of software systems development and deployment. His research spans critical interdisciplinary domains at the software-society interface: Foundational software engineering principles Societal computing frameworks Privacy-preserving system design Security policy integration Human-centered interaction models Ethical implications of computational systems Analysis of the departmental context indicates emerging work in secure societal infrastructure, though specific publication trends cannot be determined from available data. No scientific awards or student advising relationships were documented in the source material.

Claire Le GouesView profile

Associate Professor

• Software Engineering
• Programming Languages
• Program Analysis
• +9 more

Claire Le Goues is an Associate Professor in the School of Computer Science at Carnegie Mellon University , affiliated with the Software and Societal Systems Department (formerly Institute for Software Research). She holds a Ph.D. and M.S. in Computer Science from the University of Virginia and a B.A. in Computer Science from Harvard College. Her research focuses on software engineering with emphasis on program analysis , transformation , and search-based repair . She leads the squaresLab group and co-directs the REUSE@CMU summer program. Her work spans automated program improvement (stochastic/formal approaches), software assurance, quality metrics, and systems from open source to robotics. Recent scientific awards include the ACM FSE 2025 Test of Time Award Honorable Mention and the Presidential Early Career Award for Scientists and Engineers (PECASE) . She mentors students in software engineering and actively collaborates on projects like SearchRepair and GenProg , supporting empirical benchmarks such as ManyBugs and IntroClass . She teaches software engineering and program analysis at undergraduate, master’s, and doctoral levels, addressing challenges in scaling modern systems. Her lab focuses on software repair , code transformation , and AI-driven testing .

Bradley SchmerlView profile

Researcher

• Software Engineering
• Software Architecture
• Self-Adaptive Systems
• +5 more

Bradley Schmerl serves as a Principal Systems Scientist in the Software and Societal Systems Department (S3D) within Carnegie Mellon University's School of Computer Science. His research advances software engineering practices for modern challenges in distributed heterogeneous systems, self-adaptation, and cyber-physical integration. He leads the ABLE research group and actively mentors students in the Masters in Software Engineering program while teaching core courses like Software Architecture and Software Engineering Practicum. Dr. Schmerl's work addresses critical challenges in composing continuously evolving software systems, including components from untrusted third parties and on-the-fly recomposition for environmental changes. His research develops reusable, analyzable tools for software composition with emphasis on model-based adaptation, uncertainty management, and cross-language integration. Key projects include Rainbow for runtime architecture reflection, Acme for formal architectural foundations, and Cyber-physical Systems research linking software models with physical dynamics. Analysis of his 2023-2025 publications reveals intensifying focus on robotics software architecture (particularly ROS-based systems), explainable AI for architectural tradeoff analysis, and configuration management in adaptive systems. Trends show growing integration of machine learning for auto-tuning, empirical studies of misconfigurations, and dimensionality reduction techniques for visualizing design spaces—consistently bridging theoretical rigor with practical tool development for real-world applications. Scientific Awards: No specific awards were documented in the source materials. Dr. Schmerl serves as Practice Area Lead and mentor in CMU's Masters in Software Engineering program, guiding client projects including Rainbow UI for self-adaptive framework interfaces, CoBot UI for telepresence robots, and Educational Telepresence Tasking Language development. His research receives support through ABLE group projects funded by grants targeting software architecture foundations, adaptation mechanisms, and cyber-physical system validation. As a core member of the ABLE research group, he directs investigations into architecture-based self-adaptation with active projects spanning Rainbow (runtime architecture models for dynamic adaptation), Acme (formal architectural styles and tools), and Cyber-physical Systems (software-physical model integration). The group also maintains legacy work in End-User Architecting, Architecture Evolution, and service-oriented platforms for intelligence analysis through SORASCS.

• Biosecurity
• Synthetic Biology
• Conservation Biology
• +7 more

Stephen Turner is an Associate Professor of Data Science and Assistant Dean for Research at the University of Virginia School of Data Science . His work bridges genomics, data science, and national security , focusing on biosecurity, synthetic biology, conservation, and bioinformatics applications in human health . Previously, he was a faculty member in the UVA School of Medicine’s Department of Public Health Sciences (2011–2019) and directed the UVA Bioinformatics Core . Ph.D., Human Genetics, Vanderbilt University M.S., Applied Statistics, Vanderbilt University B.S., Biology, James Madison University Turner’s research spans computational approaches to biosecurity, biodiversity conservation, and human health . Recent publications highlight tools like the qqman and kgp R packages, PLANES for epidemiological modeling, and biorecap for bioRxiv preprint summarization. His work integrates large-scale sequencing, genome editing, and machine learning in conservation biotechnology and public health forecasting. Scientific contributions include applications in infectious disease forecasting , forensic genomics , and maternal-fetal biology . He has mentored interdisciplinary students and collaborated on NIH-funded research , while advising biotech startups at the intersection of academia, industry, government, and policy .

Bineet GhoshView profile

Assistant Professor

• Artificial Intelligence
• Autonomous Vehicles
• Deep Learning
• +5 more

Bineet Ghosh is an Assistant Professor in the Department of Computer Science at The University of Alabama's College of Engineering . He leads the Trustworthy Autonomy Lab , focusing on safety verification for autonomous systems with timing uncertainties. His educational background includes a PhD from UNC Chapel Hill (2023), an M.Sc. from Chennai Mathematical Institute, and a B.Sc. (First Class First with Gold Medal) from Ramakrishna Mission Vidyamandira. PhD in Computer Science (UNC Chapel Hill, 2023) M.Sc. in Computer Science (Chennai Mathematical Institute, 2016) B.Sc. (First Class First with Gold Medal) in Computer Science (Ramakrishna Mission Vidyamandira, 2014) His research spans Artificial Intelligence, Autonomous Vehicles, Deep Learning, Embedded Systems, Robotics, and Cyber-Physical Systems , with a focus on statistical verification methods and safety-aware scheduling. Recent publications analyze neural architecture sizing, GPU partitioning, and uncertainty-aware monitoring in autonomous systems. Scientific awards include the Chateaubriand Fellowship (2021), Best Presentation Award at ACM SIGBED (2022), and Best Paper Candidate at RTCSA (2022). He previously worked as a research intern at Tata Research Labs and software developer at Oracle.

Maximilian SchreieckView profile

Associate Professor

• Digital platform ecosystems
• Platform governance
• Digital platforms for social causes
• +3 more

Maximilian Schreieck is an Associate Professor for Information Systems at the Department of Information Systems, Production and Logistics Management, University of Innsbruck. He earned his PhD at Technical University of Munich (2020) and completed habilitation at University of Innsbruck (2025). Previously a DFG Walter Benjamin Fellow at Wharton School (2021-2022). Education: PhD in Information Systems, Technical University of Munich (2020) Habilitation in Information Systems, University of Innsbruck (2025) His research focuses on digital platform ecosystems, platform governance, digital platforms for social causes, and digital transformation of established companies. He has published extensively in top journals like MIS Quarterly, Information Systems Journal, and Electronic Markets. Recent publications address generative AI ecosystems, EU digital regulation impacts, cloud platform adoption, and multi-platform strategies. His work combines technical platform analysis with organizational and regulatory implications. Scientific awards include: Best Paper Award, AIS SIG Grounded Theory Methodology (2021) Paper of the Year Award, AIS SIG Electronic Markets (2020) His research has practical applications in automotive, banking, and refugee integration platforms, with collaborations at SAP, BMW, and EU policy contexts. Teaching activities include master's theses supervision and courses on digital platform management.

Moe MojtahediView profile

Senior Lecturer

• Construction Management
• Urban and Regional Planning
• Operations Research
• +8 more

Dr Moe Mojtahedi is a Senior Lecturer at the School of Built Environment, University of New South Wales (UNSW). He earned his PhD in 2014 from the School of Civil Engineering at the University of Sydney. As a certified Project Management Professional (PMP) and Professional Engineer (PEng) accredited by Engineers Australia, Dr Mojtahedi bridges academic research with practical application in construction management and disaster risk reduction. PhD (University of Sydney, 2014) MEngSc (University of New South Wales) B.E. (Industrial), Professional Engineer (Australia) His research focuses on the intersection of construction management , urban resilience , and disaster risk reduction , particularly examining: Climate change adaptation in infrastructure Post-disaster recovery frameworks Lean construction methodologies Decision support systems for risk management Evacuation planning optimization Resilient hospital infrastructure Recent publications analyze trends in disaster science using computational modeling, prefabricated construction for industrial buildings, and AI/ML applications in aged care facility evacuation. His 2025 ChemistryOpen article explores sustainable reaction media for chemoselective processes, demonstrating interdisciplinary reach. Scientific recognition includes: Research Excellence Awards (Engineers Australia, 2012 & 2013) Best Conference Paper (ICES, Salford, 2017) Elsevier Outstanding Contribution Award (International Journal of Project Management, 2017) Learning and Teaching Excellence (UNSW, 2017) As a supervisor, he guides 7 PhD candidates and has mentored 4 graduates, including Mahmoud Ershadi (project management office effectiveness) and Kamyar Kabirifar (construction waste management). He contributes to policy discussions on aligning National Construction Code with UN Sendai Framework and advocates for disaster science integration in built environment practices. His media contributions examine hospital flood risks and climate change adaptation in Australia.

• Model-Based Design
• Design Automation
• Optimization
• +4 more

Marc C.W. Geilen is an Associate Professor at the Electronic Systems group , Eindhoven University of Technology. He leads the Model-Based Design Lab and contributes to the CompSOC Lab and High Tech Systems Center . His work focuses on model-based design methods, design automation, and optimization for real-time and embedded systems. Research Keywords: Cyber-Physical Systems, Real-Time Systems, Embedded Systems, Performance Analysis, Design Automation Key Collaborations: EU ECSEL TRANSACT project, SAM-FMS project, Arrowhead Tools initiative His recent publications address weakly-hard timing constraints in server-based systems, hybrid performance modeling for cyber-physical systems, and neural network optimization for communication. Article trends span Real-Time Scheduling , Trustworthy Modeling , Neural Network Efficiency , and Resource Allocation in distributed environments. Scientific Awards : Partial-Order Reduction for Performance Analysis (2018) Teaching activities include courses in Computational Modeling , Embedded Signal Processing , and Discrete Mathematics . He collaborates across projects like TRANSACT, SAM-FMS, and Arrowhead Tools, focusing on flexible manufacturing and cloud-to-edge transitions.

• Creative processes in conflict contexts
• Cultural transfers
• Digital humanities
• +7 more

Fatiha Idmhand is a Professor at the University of Poitiers , specializing in Contemporary Hispanic Literature and Digital Humanities. She leads the Archivos CRLA team and contributes to the Multilingualism, Translation, Creation Team . Her research examines creative processes under situational constraints (wars, exiles, imprisonments), focusing on cultural transfers and digital humanities methodologies. She is currently a researcher in residence at the Musée national Picasso Paris (2023-2024). PI of 10 projects (2013-2025), including Pablo Picasso en toutes lettres (2018-present) and Archivos 3.0 (2019-2022) 2023: Deputy Coordinator, Consortium ARIANE (HumaNum) 2021-2023: President, Humanistica association Her digital humanities work integrates computer science with text analysis, developing tools like e-Man and CHispa for Hispanic manuscript digitization. She advocates for FAIR data principles in author corpus management. Major publications appear in Digital Humanities Quarterly , La Gazette des Archives , and Word and Text . She actively participates in international conferences like DH and Humanistica , with recent presentations on AI-humanities collaboration.