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Sylvain ArlotView profile

Professor

• Statistical Learning
• Non-Parametric Statistics
• Data-Driven Tuning of Learning Algorithms
• +5 more

Sylvain Arlot is a Professor at the Mathematics Department of Université Paris-Saclay, affiliated with the Probability and Statistics team at Laboratoire de Mathématiques d'Orsay. He leads the Celeste INRIA Saclay project-team and is a junior member of the Institut Universitaire de France (IUF) since 2020. His research focuses on statistical learning theory, non-parametric methods, model selection, and change-point detection. Arlot has contributed to foundational work on cross-validation, penalization techniques, and random forests. He co-organizes the Séminaire Palaisien and serves as an associate editor for the Annales de l'Institut Henri Poincaré B. Education: PhD in Mathematics from Université Paris-Sud (2007), HDR (Habilitation) from Université Paris Diderot (2014). Research Interests: Core areas include statistical learning theory, resampling methods (e.g., cross-validation and bootstrap), and applications in high-dimensional data analysis. His work bridges theoretical guarantees with practical algorithm design, emphasizing data-driven model selection and robust estimation techniques. Grants & Projects: Leads the PEPR IA Project Causali-t-AI (2023–2028) and was a member of the ANR Fast-Big project (2018–2023). He coordinates the math-AI program under Labex Mathématique Hadamard. Awards: Junior IUF membership (2020–2025). Labs/Teams: Heads the Celeste team at INRIA Saclay, collaborating on statistical machine learning and data science challenges.

S. Alireza BehnejadView profile

Associate Professor

• Design and Construction of Spatial Structures
• Formex Configuration Processing
• Structural Performance of Bamboo
• +4 more

Dr. S. Alireza Behnejad is an Associate Professor in the Department of Civil and Environmental Engineering at the University of Surrey, UK. He holds a PhD in Geometry of Spatial Structures (2018) and serves as Director of the Spatial Structures Research Centre founded in 1963. His roles include Programme Leader for Undergraduate Civil Engineering and member of the University Ethics Committee. Behnejad is Editor-in-Chief of the International Journal of Space Structures and a key member of the International Association for Shell and Spatial Structures (IASS), including organizing the 2020/21 virtual IASS conference. Behnejad’s research focuses on spatial structures, bamboo engineering, and pedagogical methods. Notable projects include the Bamboo For Sustainable Construction initiative (with global partners) and the DAD Project , promoting hands-on learning through physical models. He has been awarded the Vice-Chancellor's Teacher of the Year (2021) for enhancing student learning. His work bridges historical architectural forms (e.g., Iranian Karbandi vaults) with modern engineering challenges, emphasizing sustainability and education. Behnejad collaborates with institutions worldwide, including Brazil’s University of São Paulo and China’s Southwest Jiaotong University. He supervises postgraduate students on topics like spatial structure conceptual design and leads efforts to improve engineering education through full-scale physical models and international student exchanges.

Rajan JagpalView profile

Researcher

• Composite Materials
• Manufacturing Processes
• Hydrogen Storage Technologies
• +3 more

Rajan Jagpal is a Researcher in the Department of Chemical Engineering at the University of Bath, affiliated with the Centre for Integrated Materials, Processes & Structures (IMPS), The Foundry Centre for Digital Manufacturing & Design, and the Centre for Sustainable Energy Systems (SES). He holds a PhD in Automated Composite Manufacturing (2022) supervised by Prof. Evangelou, Prof. Loukaides, and Dr. Butler. His research focuses on composite materials processing, hydrogen storage technologies, UAV photogrammetry applications, and sustainable manufacturing systems. Key research contributions include optimizing non-crimp fabric preforming via magnetic clamping and Bayesian algorithms, developing freeze-cast porous composites for hydrogen storage, and advancing UAV-based manufacturing quality control. He collaborates on projects like the High Speed Microtomography initiative (2022–present) investigating carbon fabric deformation mechanisms. His work addresses UN Sustainable Development Goals related to affordable clean energy and industry innovation. He actively engages in public outreach, contributing to school engagement activities from 2018–2019. Jagpal is currently accepting doctoral students for research aligned with his expertise in advanced manufacturing and materials science.

Ilya ShpitserView profile

Associate Professor

• Causal Inference
• Missing Data
• Graphical Models
• +5 more

Ilya Shpitser is a John C. Malone Associate Professor in the Department of Computer Science at Johns Hopkins University (JHU), within the Whiting School of Engineering. He is also a member of the Malone Center for Engineering in Healthcare and the Data Science and AI Institute. His research focuses on causal inference, missing data, graphical models, algorithmic fairness, and semi-parametric inference, with applications in healthcare, public health, and criminal justice. Shpitser holds a BA in Computer Science and Mathematics from UC Berkeley (1999), and MS (2004) and PhD (2008) in Computer Science from UCLA. Postdoctoral work included Harvard University and the University of Southampton. He has received awards such as the Causality in Statistics Education Award (2017) and the NSF CAREER Award (2020). His work addresses disparities in algorithmic bias, causal pathway analysis, and high-dimensional observational data. Key contributions include developing causal inference methods for missing data and fairness, as well as software tools like Ananke. He serves as an associate editor for the Journal of Causal Inference and the American Journal of Epidemiology. His research is funded by NSF, NIH, DARPA, and the Office of Naval Research. Shpitser advises numerous PhD students, many of whom have transitioned to academic and industry roles. His interdisciplinary collaborations span biostatistics, computer science, and public health, emphasizing real-world applications of causal methods.

Yudi PawitanView profile

Professor

• Bioinformatics
• Statistical Genetics
• Genomics
• +2 more

Yudi Pawitan is Professor at the Department of Medical Epidemiology and Biostatistics at Karolinska Institutet, where he leads the research group on Statistical and Bioinformatics Analyses of High-Throughput Molecular Data. His work focuses on developing statistical methods for genomic studies including SNP/RNA arrays and next-generation sequencing. Education includes BSc in Statistics (Bogor Agriculture Institute, 1982), MSc in Statistics (UC Davis, 1984), and PhD in Statistics (UC Davis, 1987). Research interests span bioinformatics, cancer genomics, and statistical genetics with emphasis on high-dimensional data analysis, genetic correlations, and neural cell biology. His group addresses fundamental questions in genomic data interpretation and neurodegenerative processes. Publications demonstrate strong focus on genetic epidemiology, single-cell analytics, and statistical methodologies. Recent works explore machine learning applications in longitudinal data visualization, neural cell characterization, and cancer biomarker discovery. Awards: Not documented in provided texts. Supervises doctoral candidates including Linda Lindström and Ralf Kuja-Halkola. Manages the Live Imaging Facility at St. Vincent's Centre for Applied Medical Research. Research funded by Swedish Research Council and Swedish Cancer Society grants. Leads interdisciplinary collaborations through the Statistical and Bioinformatics research group, integrating computational biology with experimental neuroscience.

• Computer Architecture
• Embedded Systems
• High-Performance Computing
• +9 more

Zapater Sancho Marina is an Associate Professor at the ReDS Institute (Institute of Reconfigurable and Embedded Digital Systems) within the School of Engineering and Management Vaud (HEIG-VD), part of the University of Applied Sciences and Arts Western Switzerland (HES-SO). She holds dual master's degrees in Electronic and Telecommunication Engineering from Universitat Politècnica de Catalunya (2010) and a PhD in Computer Science from Universidad Politécnica de Madrid (2015). Her career includes postdoctoral work at EPFL (2016-2020) and assistant professorship at Universidad Complutense de Madrid (2015-2016). Education BSc & MSc in Electronic Engineering (UPC 2010) PhD in Computer Science (UPM 2015) Research Focus spans cross-layer optimization of heterogeneous architectures for performance and energy efficiency, with emphasis on: Embedded systems (IoT/edge computing) High-performance compute architectures Analog in-memory computing for AI Thermal/power management in 3D chips Cloud-edge AI workload orchestration Publication Trends show expertise in RISC-V simulation frameworks, analog computing tiles for CNNs, virtual memory redesign, and AI-driven cloud performance prediction. Her recent work explores thermal-aware 3D chip management, hybrid-cache reliability optimization, and open-source teaching platforms for radio theory. Awards include a Spanish government PhD fellowship. She has led 4 European H2020 projects since 2016 and currently serves as PI for 4 industrial collaborations (Facebook/Intel/Huawei), Innosuisse projects, and HES-SO initiatives. Labs & Teams include the ReDS Institute, EPFL's Embedded Systems Laboratory, and collaborations with Yale/Edinburgh. She co-developed the ALPINE simulation framework and SO3 operating system modifications for Midgard project validation.

Martha Godina RodriguezView profile

Researcher

• Sustainability in construction
• Circular economy in built environment
• Material reuse and flows
• +3 more

Martha Godina Rodriguez is a Postdoctoral Research Associate at the University of Cambridge , affiliated with the Centre for Natural Material Innovation within the Department of Architecture . Her current work focuses on the WOODCIRCLES project, funded by Horizon Europe, which explores circular material flows of wood in construction. She holds a PhD in structural engineering from the University of Cambridge, with earlier degrees in architecture and lightweight roof structures. Education: Bachelor's degree in Architecture Master’s degree in Lightweight Roof Structures PhD in Structural Engineering (Thesis: Design Methodology for Bamboo Structures – A Study of Bamboo Reciprocal Structures ) Research Interests: Martha’s work bridges sustainability, material innovation, and structural engineering. She investigates strategies for salvaging timber from existing buildings, digital design tools for natural materials, and the interplay between geometry/material properties and structural performance. Her interdisciplinary approach combines fieldwork, computational modeling, and industry collaboration. Awards & Projects: Lead researcher on Horizon Europe-funded WOODCIRCLES (Circular Potential of Wood Construction) Recipient of 2021 Sustainability Scholarship (Worshipful Company of Constructors) Prior research collaboration with Elliott Wood Partnership, CIOB, and UCEM on timber salvage strategies Labs/Teams: Active member of the Centre for Natural Material Innovation , a multidisciplinary group advancing sustainable construction materials and practices.

Göran KauermannView profile

Professor

• Nonparametric Models
• Semi- and nonparametric analysis
• Generalized Linear Models
• +2 more

Prof. Dr. Göran Kauermann is a Full Professor of Statistics at the Ludwig-Maximilians-University Munich , holding the Chair of Applied Statistics in Social Sciences, Economics and Business . His research spans nonparametric models, generalized linear models, and network data analysis, with applications in economics, epidemiology, and data science. Education: Diplom in Economic Mathematics (1991, TU Berlin), PhD in Statistics (1994), Habilitation (Venia Legendi) in Statistics (2000) Kauermann’s research interests focus on penalized regression , network analysis , and statistical modeling in economics, social sciences, and public health. Recent work explores label uncertainty in machine learning , spatio-temporal conflict diffusion , and dynamic network models for economic and social data. Scientific trends in his publications include penalized splines for nonlinear modeling, network flow estimation in social and economic contexts, and label variation analysis in machine learning. His collaborations span climate zone classification , Covid-19 mortality modeling , and smart city parking analytics . Scientific Awards: Bruce Russett Award (2020) for political network research Leadership Roles: He served as Dean of the Faculty of Mathematics, Informatics and Statistics (2019–2021), Speaker of the Elite Master Program in Data Science (2016–2026), and Chair of the German Statistical Society (2005–2013). He also held editorial roles in journals like AStA Advances in Statistical Analysis and Statistical Modelling .

Ehsan KamelView profile

Associate Professor

• Building Energy Modeling
• Sustainable Architecture
• Renewable Energy Infrastructure
• +4 more

Ehsan Kamel is an Associate Professor in the Department of Energy Management at the New York Institute of Technology's College of Engineering and Computing Sciences. He joined the university in 2017 after earning his Ph.D. in Civil Engineering from Pennsylvania State University. His research focuses on building energy modeling, sustainable construction materials, and extraterrestrial habitat design for Mars. He directs the Energy and Green Technologies Laboratory (EnTech Lab), fostering student hands-on experience in energy and green technologies. Kamel has secured over $575,000 in grants from organizations like the National Science Foundation and NYSERDA, advancing energy efficiency and sustainability initiatives. His work bridges academia with industry, addressing real-world challenges in energy systems and climate resilience. Education: Ph.D. in Civil Engineering (Pennsylvania State University, 2017); M.S. in Civil Engineering; Certified Energy Manager (CEM). Research Interests: Building energy modeling integrates physics-based simulations and machine learning to optimize energy use in buildings and urban systems. He explores climate change impacts on energy systems, low-income housing energy burdens, 3D-printed construction, and sustainable materials. His extraterrestrial research models habitats for Mars using Martian climate data and locally sourced materials. Recent Projects: Urban-scale energy modeling with HPC systems, energy burden analysis in low-income households, and Mars habitat simulations. His work has been recognized with awards including the inaugural Trailblazers in Clean Energy (2024) and AEE Energy Innovator of the Year (2023). Grants and Collaborations: Principal investigator for NYSERDA grants ($500,000) and ASHRAE-funded projects. Collaborates with universities globally and energy firms on building efficiency solutions. Manages a research portfolio totaling $575,000 since 2017. Labs/Teams: Directs EnTech Lab, advises ASHRAE student branch, and leads interdisciplinary teams on energy-smart buildings and digital twin technologies.

• Interior Architecture
• Architectural Design Pedagogy
• Virtual Reality Applications in Design
• +5 more

Uğur Efe Uçar is a Researcher at the Department of Interior Architecture, Faculty of Architecture, Istanbul Technical University. He holds a PhD in Informatics in Architectural Design (2021) and has been a Research Assistant since 2019. His academic journey includes a Master's in Interior Architecture Design International (2018–2020) and a Bachelor's in Interior Architecture (2015–2018), all from Istanbul Technical University. His research focuses on integrating technology into architectural education and design practices, particularly through virtual reality (VR) applications, computational frameworks, and phenomenological studies of interior spaces. Key areas include generative design pedagogy, anthropometric measurements using VR, and earthquake-resistant interior design. He has explored topics like the implicit meanings of domestic elements (e.g., beds, water systems) and flexible shelter designs for emergency scenarios. Uçar has authored over a dozen peer-reviewed articles since 2021, consistently advancing interdisciplinary approaches at the intersection of technology, human behavior, and space. His work emphasizes both theoretical exploration and practical applications in sustainable and resilient design. No scientific awards are listed, but his contributions reflect a strong commitment to academic innovation and pedagogical development.

• Causal Inference
• Precision Medicine
• Mendelian Randomization
• +5 more

Yunan Wu is an Assistant Professor at the Yau Mathematical Sciences Center, Tsinghua University (since September 2024). Previously, he served as an Assistant Professor at the University of Texas at Dallas (2020–2024) and completed a postdoctoral fellowship in Biostatistics at Yale University’s School of Public Health (2019–2020). He earned his PhD in Statistics from the University of Minnesota (2015–2019), supervised by Prof. Lan Wang, and holds a bachelor’s degree in Mathematics and Physics from Tsinghua University (Beijing, China). His research focuses on **causal inference in precision medicine**, **Mendelian randomization**, **non-parametric/semi-parametric methods**, and **high-dimensional statistical analysis**. He also explores robust machine learning techniques and incorrupted data methodologies. His work bridges theoretical advancements with practical applications in healthcare and biomedical research. Key contributions include the development of tuning-free robust regression approaches (e.g., the TFRE method) and inference frameworks for optimal treatment regimes. His GitHub repositories reflect these efforts, including implementations of robust regression and treatment regime estimation algorithms. He is affiliated with the Yau Mathematical Sciences Center, where he contributes to interdisciplinary research at the intersection of statistics, machine learning, and biomedical sciences. His email is wuyunan@mail.tsinghua.edu.cn , and his office is located in Shuangqing Complex Building A504.

Anil MisraView profile

Professor

• Engineering Mechanics
• Materials Science
• Geotechnical Engineering
• +3 more

Dr. Anil Misra is the Chair and Professor in the Department of Civil and Environmental Engineering at Florida International University (FIU), Miami. Previously, he served as the Glenn L. Parker-James L. Tyson Professor of Engineering Mechanics at the University of Kansas (KU) and Associate Director of KU's Institute for Bioengineering Research. He also held faculty positions at the University of Missouri-Kansas City (UMKC) from 1990 to 2007. He holds a bachelor’s degree in civil engineering from the Indian Institute of Technology (IIT), Kanpur, India (1985), and M.S. and Ph.D. degrees from the University of Massachusetts Amherst (1988 and 1991). His teaching focuses on engineering mechanics, materials engineering, computer methods, and geotechnical engineering. Dr. Misra’s research bridges mechanics and materials science, emphasizing granular micromechanics, biomaterials, and geotechnical engineering. His work includes pioneering the granular micromechanics approach (GMA) to model granular materials and metamaterials. He has authored over 350 publications, co-edited four books, and guest-edited six journal special issues. His research has been funded by governmental agencies and industry. He has received the 2017 Eugenio Beltrami Senior Scientist Prize for contributions to granular micromechanics and a 2018 Fulbright Specialist award. He actively serves on editorial boards, technical committees, and provides industry consulting. His lab explores interdisciplinary topics like dental adhesives, metamaterials, and computational mechanics.

• Composite Materials
• Structural Mechanics
• Fracture Mechanics
• +5 more

Dr. Muni Rami Reddy Rasappagari is a casual academic staff member at the University of Southern Queensland (UniSQ) , Australia, within the School of Engineering . He holds a Diploma in Civil Engineering from SV Govt Polytechnic Tirupati, a Bachelor of Technology from Nagarjuna University, a Master of Science in Civil Engineering from Indian Institute of Technology (IIT), and a PhD from the University of Madras . His research spans composite materials , structural mechanics , fracture mechanics , and nanomaterials , with a particular focus on graphene-reinforced composites , functionally graded materials , and delamination modeling . His work integrates finite element analysis , fractal methods , and vibration analysis to address complex structural integrity problems. Dr. Rasappagari's recent publications (2018–2022) emphasize graphene nanoplatelet (GPL) reinforcement in composite plates, exploring free and forced vibration , flexural behavior , and boundary condition effects . Earlier work (2007–2009) centered on fractal finite element methods for crack sensitivity analysis and stress intensity factor computation in anisotropic and multi-crack systems . Contact: 📧 muniramireddy.rasappagari@unisq.edu.au

Hendrik UlbrichtView profile

Professor

• Quantum Mechanics
• Gravitation Physics
• Nanotechnology
• +3 more

Professor Hendrik Ulbricht is a Professor of Physics at the University of Southampton's Department of Physics & Astronomy. His research focuses on experimental tests of quantum mechanics and gravitation in macroscopic systems, including levitated opto-mechanics and nanoparticle interferometry. He leads the Quantum Nanophysics and Matterwave Interferometry group, pioneering studies on quantum superposition and gravity interactions using trapped nanoparticles. Education: PhD (Dr. rer. nat.) from Free University of Berlin and Max Planck Society (2003) Undergraduate degree (Dipl.-Phys.) from Technical University Berlin and Max Planck Institute for Gravitational Physics (2000) Research Interests: Experimental quantum mechanics, quantum-gravity interplay, levitated systems, nanoparticle trapping, and non-classical states. His group explores foundational physics through table-top and space-based experiments to test quantum theory limits. Key Projects: EPSRC-funded studies on quantum superposition tests Leverhulme Trust projects on modified gravity and dark matter detection PhD Supervision: Advising 9 current students in Physics and related fields. Awards: Max Kade Fellowship (postdoctoral period).

Yudhi AriadiView profile

Teaching Professor

• Additive Manufacturing
• 3D Printing
• Mass Customization
• +4 more

Dr. Yudhi Ariadi is a Teaching Professor in Engineering Design at the University of Warwick's School of Engineering. With a background in Mechanical Engineering from Universitas Brawijaya, Indonesia, he holds an MSc from Lancaster University and a PhD from Loughborough University. His career spans industry (ISUZU Astra Motor Indonesia, FUJI Technica Indonesia) and academia, including roles at Coventry University and the University of Birmingham's High Temperature Research Centre. He specializes in Additive Manufacturing (AM), 3D Printing, CAD tools for mass personalization, and engineering design education. Education: Bachelor's in Mechanical Engineering, Universitas Brawijaya, Indonesia MSc in Engineering (Research), Lancaster University PhD in CAD Tools for Public 3D Printing Access, Loughborough University Research focuses on democratizing AM through accessible CAD tools, customization strategies, and AM applications in automotive and biomedical fields. Recent work includes distortion prediction in selective laser melting and ergonomic medical device design. His projects are funded by Rolls-Royce, EU, and the Higher Education Funding Council for England. Teaching emphasizes CAD software (SolidWorks, Siemens NX), design thinking, and AM integration in engineering curricula. He advises on SME innovation through the University of Derby's Institute for Innovation in Sustainable Engineering. Labs/Teams: Part of the High Temperature Research Centre (Birmingham) and collaborates with global automotive brands (Toyota, Ford, Geely) through past industry roles.