جست‌وجوی استاد و پژوهشگر

Navid Bahraniمشاهده پروفایل

دانشیار

• Mining Geomechanics
• Rock Mechanics
• Underground Excavation Support Design
• +۳ مورد دیگر

Dr. Navid Bahrani is an Associate Professor and Graduate Coordinator in the Department of Civil and Resource Engineering at Dalhousie University's Faculty of Engineering in Halifax, Nova Scotia, Canada. With over 10 years of professional experience in mining geomechanics, he brings both academic expertise and practical industry knowledge to his teaching and research. Dr. Bahrani's educational background includes: Bachelor of Science in Mining Engineering from Azad University, Tehran, Iran (2006) Master of Science in Mining Engineering from University of Alberta, Edmonton, Canada (2009) Doctor of Philosophy in Natural Resources Engineering from Laurentian University, Sudbury, Canada (2015) Post-Doctoral Fellowship at the University of Toronto's Lassonde Institute of Mining (2015-2017) Dr. Bahrani's research focuses on mining geomechanics , with particular emphasis on rock mechanics, underground excavation support design, numerical modeling in geotechnical engineering, brittle fracture phenomena, and rock slope stability. His work bridges theoretical understanding with practical applications in mining and civil engineering projects. He employs advanced computational methods to simulate rock behavior under various loading conditions, with special attention to the mechanical response of jointed and defected rock masses. His research has significant implications for mine design, ground support systems, and slope stability analysis in both mining and civil engineering contexts. Analysis of Dr. Bahrani's publication record reveals a strong focus on the application of numerical modeling techniques to solve complex rock mechanics problems. His work demonstrates evolving expertise from fundamental rock mechanics characterization to sophisticated 3D modeling of mining-induced stress changes and support system behavior. A notable trend in his research is the development and validation of grain-based models that bridge the gap between continuum and discontinuum approaches in rock mechanics simulation. His publications consistently address practical engineering challenges while advancing theoretical understanding of rock mass behavior. Dr. Bahrani has received recognition for his scholarly contributions: Peter Cundall Honorable Mention Award for paper: 'Bahrani N. and Kaiser P.K. 2016. Integrated grain-based-DFN model for simulation of defected rock, Proceedings of the 4th Symposium on Applied Numerical Modeling, Peru.' As Graduate Coordinator for the Department of Civil and Resource Engineering, Dr. Bahrani oversees graduate programs and advises students in mining and geotechnical engineering. His research has been supported by collaborations with industry partners including MIRARCO's Geomechanics Research Centre and various mining operations across North America. He has been involved in numerous projects related to in situ stress measurement, rock mass deformation monitoring, laboratory testing, and numerical modeling for practical mining applications. Dr. Bahrani maintains active professional affiliations with several organizations including the International Society for Rock Mechanics (ISRM), Canadian Rock Mechanics Association (CARMA), Canadian Geotechnical Society (CGS), International Society of Explosives Engineers (ISEE), and The Canadian Institute of Mining, Metallurgy and Petroleum (CIM). His work connects with broader research communities focused on rock mechanics and geotechnical engineering applications in mining contexts.

• Contrast Enhanced Medical Imaging
• Medical Imaging and Therapy
• Ultrasound Imaging
• +۷ مورد دیگر

Dmitry Grishenkov is an Associate Professor at KTH Royal Institute of Technology, working at the Division of Biomedical Imaging within the Department of Biomedical Engineering and Health Systems. He serves as Program Director of the M.Sc. Programme in Innovative Technology for Healthy Living (TIHLM) and is Vice Director of the Jonasson Centre for Medical Imaging. His research lab is located at KTH Campus Flemingsberg. Dr. Grishenkov's research focuses on Contrast Enhanced Medical Imaging and Therapy, with particular emphasis on characterization of structural and physical properties of multimodal contrast agents, investigation of sonoporation and cavitation mechanisms, and understanding dynamics of multiphase media in biomedical applications. His recent work has been dedicated to high frequency ultrasound imaging and photoacoustic imaging in vivo using small and medium laboratory animals, developing novel methods for visualization and quantification of multimodal contrast agents. His publication record shows a strong focus on microbubble and droplet-based contrast agents, with recent articles exploring hydrodynamic cavitation-on-a-chip platforms, cellulose nanofiber-coated droplets, and advanced ultrasound imaging techniques. The research spans biomedical engineering, fluid dynamics, and nanotechnology with applications in thrombolysis, drug delivery, and environmental remediation. As an educator, Dr. Grishenkov teaches and examines courses including Artificial Intelligence within Biomedical Engineering, Medical Engineering Advanced Course, Ultrasound, and Medical Technologies in Digital Healthcare Transformation. He has been instrumental in establishing the KTH-SJTU Summer School in Interdisciplinary Biomedical Research. His research group collaborates extensively with the Karolinska Institute on novel contrast agents for tissue-specific diagnostics and localized drug delivery, and with KTH's Department of Applied Physics on microfluidic studies of microbubble behavior. This interdisciplinary approach has positioned his work at the forefront of innovative medical imaging technologies with both diagnostic and therapeutic applications.

• Mathematical Methods in Signal Processing
• Data Science
• Dynamical Systems
• +۵ مورد دیگر

Nada Sissouno is a Professor of Mathematics and Didactics of Mathematics at the Faculty of Electrical Engineering, Media and Informatics at Amberg-Weiden University of Applied Sciences since November 2023. She also serves as Vice Dean and Co-head of the Competence Center Grundlagen (CCG). Additionally, she maintains a position as a guest researcher at the Research Group: Applied and Numerical Analysis and Optimization and Data Analysis at the Technical University of Munich (TUM). Her educational background includes a Doctorate in Mathematics (Dr. rer. nat.) from TU Darmstadt (2007-2011) and a Diplom in Mathematics with a minor in psychology from TU Darmstadt (2000-2007). She has completed further education as a Diversity Manager in 2021 and holds certificates in teaching in higher education from the Bavarian Universities (2014-2016). Professor Sissouno's research focuses on mathematical methods in signal and image processing, data science, dynamical systems, numerical simulation, and approximation theory. Her work particularly emphasizes spline functions on domains, wavelets and frames, and evidence-based development of teaching methodologies. Her recent publications demonstrate strong expertise in mathematical imaging, phase retrieval problems, and approximation theory, with applications spanning ptychographic imaging, variational inpainting methods, and structural sparsity in multiple measurements. Her collaborative research bridges theoretical mathematics with practical applications in signal processing and image analysis, with a particular focus on developing robust numerical algorithms for complex data analysis problems. She has published in prestigious journals including Advances in Computational Mathematics, Journal of Fourier Analysis and Applications, IEEE Transactions on Signal Processing, and Inverse Problems. Referentin für Talentmanagement & Diversity at TUM (2022-2023) Deputy spokesperson of Research Associates' Council of the TUM (2019-2023) Gender equality officer of Department of Mathematics (2019-2022) Professor Sissouno teaches mathematics courses for engineering and computer science students, with a focus on making mathematical concepts accessible and relevant to practical applications. She has been involved in teacher training and the evidence-based development of teaching methodologies, demonstrating her commitment to both research excellence and educational innovation.

• Combustion Theory
• Turbulent Flame Propagation
• Hydrogen and Ammonia Combustion
• +۵ مورد دیگر

Francesco Creta serves as Associate Professor in the Department of Aeronautical and Space Engineering at Sapienza University of Rome's School of Engineering. His research focuses on advanced combustion phenomena with emphasis on hydrogen and ammonia fuels for decarbonization applications. His primary research interests include thermodynamic instability in premixed flames , turbulent combustion modeling , and rocket propulsion systems . Creta investigates fundamental flame behaviors through direct numerical simulation (DNS) and develops data-driven models for thermodiffusively unstable flames, particularly examining hydrogen-ammonia mixtures for sustainable energy applications. His work bridges theoretical combustion physics with practical engineering solutions for gas turbines and liquid rocket engines. Analysis of his 15 most recent publications reveals a strong trend toward hydrogen-ammonia combustion for decarbonization, with significant focus on flame instability mechanisms (particularly Darrieus-Landau and thermodiffusive effects), data-driven modeling approaches , and rocket engine applications . His research increasingly integrates machine learning techniques with traditional combustion modeling to address complex flame behaviors under high-pressure conditions. Creta maintains active research collaborations with leading combustion scientists across Europe, evidenced by co-authorship on high-impact publications in Proceedings of the Combustion Institute , Combustion and Flame , and Physics of Fluids . His work receives consistent recognition through publication in top combustion venues and presentation at major international conferences including the European Combustion Meeting and AIAA SciTech Forum. His research group conducts advanced numerical simulations of combustion systems, with particular expertise in liquid rocket engine modeling, transcritical flows, and flame instability analysis. Current projects focus on enabling hydrogen and ammonia combustion for gas turbine retrofitting and next-generation propulsion systems, addressing critical challenges in flame stability and pollutant formation.

Clint Dawsonمشاهده پروفایل

استاد

• Computational Mechanics
• Partial Differential Equations
• Numerical Analysis
• +۶ مورد دیگر

Clint Dawson serves as Department Chair and Professor in the Department of Aerospace Engineering & Engineering Mechanics at The University of Texas at Austin, holding the John J. McKetta Centennial Energy Chair in Engineering and directing the Computational Hydraulics Group at the Oden Institute for Computational Engineering and Sciences. Education: Bachelor of Arts in Mathematics, Texas Tech University, 1982 Master of Science in Mathematics, Texas Tech University, 1984 Ph.D. in Mathematical Sciences, Rice University, 1988 Research Interests: Dr. Dawson's work centers on Computational Mechanics and Partial Differential Equations, with deep expertise in Numerical Analysis, Numerical Methods, and Parallel Computing. His research delivers critical applications in Flow in Porous Media, Shallow Water Systems, and coastal modeling, culminating in a globally deployed simulation code for hurricane storm surge prediction that earned the 2024 UT President's Research Impact Award. Scientific Awards: National Science Foundation Postdoctoral Fellow (1988-1990) Institute for Computational Engineering and Sciences Distinguished Research Excellence Award (2011) Society for Industrial and Applied Mathematics Geosciences Career Prize (2013) Fellow of the Society for Industrial and Applied Mathematics (2016) The University of Texas President's Research Impact Award (2024) Dr. Dawson leads the Computational Hydraulics Group and contributes to the Center for Scientific Machine Learning. His professional service includes chairing the SIAM Geosciences Activity Group (2001), serving as managing editor of Computational Geosciences, and extensive participation in editorial boards and national review panels throughout his prolific 200+ publication career.

• Thermal Energy Storage
• Phase Change Materials
• Process Engineering
• +۴ مورد دیگر

Professor Ludger Josef Fischer is a faculty member at the Lucerne University of Applied Sciences and Arts (HSLU) in the School of Engineering & Architecture. He serves as Co-Head of the Competence Center for Thermal Energy Storage (CCTES) within the Institute of Mechanical and Energy Engineering (IME). Additionally, he is a guest lecturer at the University of the Arts in London (UAL) and ZHAW, Wädenswil for cosmetic manufacturing technologies, and has been an affiliated researcher at MIT since 2019. Dr. Fischer graduated in Mechanical and Process Engineering at RWTH Aachen and completed his PhD at Karlsruhe Institute of Technology (KIT). Before joining academia in 2013, he held significant industrial positions including head of R&D and sales at Kühni AG, managing director of Ekato Unimix, and various leadership roles within the AC Serendip group across Switzerland, Germany, and China. His primary research focuses on thermal energy storage, particularly Phase Change Materials (PCM) and Phase Change Dispersions (PCD). He investigates applications of these technologies in seasonal thermal storage, building applications, and industrial processes. His work spans fundamental research on material properties to applied engineering solutions. Additionally, he has significant expertise in mixing, dispersing, and emulsification technologies, with applications in the cosmetic industry and interface thermodynamics. His teaching portfolio includes Fluid Mechanics and Thermodynamics courses, Environmental Technology, Process Engineering, and specialized courses on Cosmetic Manufacturing Technologies. Professor Fischer's recent publications demonstrate a strong focus on thermal energy storage systems, particularly examining phase change materials and their applications. His work spans from fundamental material characterization to practical implementation in energy systems. There's a clear emphasis on decarbonization of energy infrastructure through innovative storage solutions, with significant contributions to both seasonal storage systems and industrial applications. Appointed Member of ProcessNet committee Heat and Mass Transfer Co-author of VDI Wärmeatlas Program Manager of Innovation Booster 'Energy Lab' funding 52 startups with approximately 2.1 MCHF As Program Manager of the Innovation Booster 'Energy Lab,' Professor Fischer has successfully guided numerous startups in the energy sector. His industrial experience translates directly into practical research and teaching, with numerous patents filed and granted under his guidance. His leadership extends to multiple significant research projects including SWEET PATHFNDR, SWEET LANTERN CCTES, and SCCER Storage initiatives. Professor Fischer co-leads the Competence Center for Thermal Energy Storage (CCTES) and is actively involved in the Swiss competence center for future energy efficient building & districts as Deputy Head. His research team conducts cutting-edge work on thermal energy storage systems, with particular focus on Phase Change Materials applications, seasonal storage solutions, and industrial process integration. The center maintains strong industry partnerships and collaborates with international institutions including MIT.

• Chemical Process Control
• Biodiesel Production
• Distillation Modeling
• +۴ مورد دیگر

Adel Mhamdi is a Professor at RWTH Aachen University's Department of Chemical Engineering within the Faculty of Mechanical Engineering. His research focuses on process systems engineering with emphasis on nonlinear model predictive control, hybrid modeling, and sustainable process design for chemical and biochemical systems. He leads research in electrified biodiesel production, distillation optimization, and polymerization process control. His research interests span chemical process control, biodiesel production optimization, distillation modeling, hybrid mechanistic-data-driven approaches, polymerization processes, and heat transfer optimization. Mhamdi develops advanced control strategies including economic NMPC, distributed control architectures, and chance-constrained optimization to address challenges in flexible operation of energy-intensive processes. His work integrates computational fluid dynamics with process modeling for reactor design and optimization. Analysis of his recent publications reveals strong trends in electrification of chemical processes, particularly biodiesel production with heat integration. His research increasingly incorporates machine learning for hybrid modeling and employs advanced computational techniques like Bayesian optimization for reactor geometry design. Key application areas include renewable energy systems, polymer manufacturing, and separation processes. Mhamdi actively supervises doctoral researchers including M. El Wajeh, J.M. Faust, and P.J. Joy who appear as first authors on multiple publications. His research group collaborates extensively with the Mitsos group at RWTH Aachen, securing publications in top journals including Industrial & Engineering Chemistry Research and Computers & Chemical Engineering . Current projects focus on real-time optimization of electrified processes and development of open-source modeling platforms like HybridML.

Sukesh Agharaمشاهده پروفایل

استاد

• Nuclear Security
• Nuclear Safeguards
• Nuclear Nonproliferation
• +۴ مورد دیگر

Sukesh Aghara is a Professor and Associate Dean of Graduate Studies and Research at the Francis College of Engineering, University of Massachusetts Lowell, where he directs the Nuclear and Chemical Engineering program and leads the Integrated Nuclear Security and Safeguards Laboratory (INSSL). He also serves as a Nuclear Security Fellow with the Center for Terrorism and Security Studies (CTSS) and co-director of the IAEA-funded Intercontinental Nuclear Institute (INI) for international nuclear training. His educational background includes a Ph.D. in Mechanical Engineering (2003) and M.S. in Mechanical Engineering (2001) with Nuclear and Radiation Engineering focus from the University of Texas at Austin, plus M.S. (1999) and B.A. (1996) in Environmental Engineering from Vanderbilt University. His academic journey reflects a transition from environmental to nuclear engineering specialization. Dr. Aghara's research centers on nuclear nonproliferation, security, and safeguards using experimental and computational approaches. His work characterizes radiation fields, evaluates reactor fuel inventories, and models cyber-physical nuclear systems. Current projects address cybersecurity vulnerabilities in nuclear plants, safeguards inspection effectiveness, and nuclear reactor applications for decarbonization. His laboratory INSSL focuses on practical solutions for global nuclear security challenges through radiation transport modeling and safeguards verification technologies. Analysis of his recent publications reveals a strong trajectory toward securing next-generation nuclear systems, particularly small modular reactors (SMRs). His work integrates cybersecurity with physical safeguards, develops robotic inspection platforms, and applies stochastic modeling for verification. Key themes include optimizing security architectures for advanced reactors while reducing operational costs and enhancing decarbonization potential through nuclear energy. Best Presentation and Paper Award (American Nuclear Society/European Nuclear Society) Outstanding Achievement in Teaching Award (UT Austin) NASA Administrator's Fellow (Cohort 11, 2014) Visiting Scientist at NASA Langley and Oak Ridge National Laboratory President of American Nuclear Society UT Chapter Outstanding Research Award (Roy G. Perry College of Engineering) As Principal Investigator, Dr. Aghara manages multiple federally funded projects including robotic security platforms for nuclear facilities (NNSA/BNL, 2020-present), advanced reactor operational considerations (INL/UTK, 2019-2023), and cybersecurity incident response planning (INL, 2017-2021). His grants consistently address national priorities in nuclear security infrastructure and next-generation reactor safeguards, with a focus on practical implementation and international capacity building through the INI program. The Integrated Nuclear Security and Safeguards Laboratory (INSSL) operates as a multidisciplinary hub collaborating with national laboratories (ORNL, INL), the IAEA, and international partners. It develops radiation detection systems, cybersecurity frameworks, and training protocols while maintaining close ties with the Center for Terrorism and Security Studies (CTSS) for cross-disciplinary threat analysis. Current projects deploy robotic platforms like the Spot robot for automated inspections and model advanced reactor security architectures.

Martin Fedaمشاهده پروفایل

پژوهشگر

• Radiosity
• Photorealistic Image Synthesis
• Parallel Graphics Algorithms
• +۱ مورد دیگر

Martin Feda is an Associated Researcher at the Institute of Computer Graphics, Vienna University of Technology, where he previously served as Assistant Professor. His research focuses on advancing radiosity methods for photorealistic image synthesis, with significant contributions to algorithmic efficiency and visual quality in global illumination rendering. Feda's primary research interests include radiosity, photorealistic image synthesis, and parallel graphics algorithms. He has pioneered techniques for stochastic radiosity, progressive refinement, and parallel implementations to accelerate computation. Key innovations involve hierarchical subdivision algorithms, methods for reducing shadow leaks without explicit meshing, improvements to intermediate radiosity images through directional light, and overshooting techniques to speed up progressive radiosity. His work consistently bridges theoretical advancements with practical applications for handling highly complex scenes. Analysis of his 1991-1997 publication record reveals a clear evolution in radiosity research: early work established parallel implementations on transputers and foundational radiosity algorithms, while later contributions developed sophisticated stochastic and hierarchical methods. The trajectory shows increasing emphasis on Monte Carlo techniques and computational optimizations to achieve greater efficiency and visual fidelity in global illumination, with consistent publication in top-tier graphics venues like Eurographics and Computer Graphics Forum.

• Structural Dynamics
• Structural Health Monitoring
• Renewable Energy
• +۵ مورد دیگر

Dr. Vikram Pakrashi is an Associate Professor in Mechanical Engineering and Director of the Dynamical Systems and Risk Laboratory (DSRL) at University College Dublin. He specializes in structural dynamics, structural health monitoring (SHM), vibration control, and renewable energy systems. His work bridges industry and academia, focusing on infrastructure resilience and emerging technologies. Education: BEng (1st Class Hons) from Jadavpur University; PhD from Trinity College Dublin. Research interests include dynamical systems, risk analysis, and smart structures. He leads interdisciplinary projects funded by industry and agencies like SEAI and the EU. Recent research trends emphasize renewable energy infrastructure (e.g., offshore wind, wave energy devices) and innovative SHM techniques using machine learning and sensor networks. His articles highlight advancements in wave measurement, defect detection algorithms, and structural fragility analysis. Awards: Engineering Laboratory of the Year 2018 (Irish Laboratory Awards). Grants: Includes projects like SISdATA (Atlantic aquaculture systems) and FlOWDyn (dynamic cable analysis for floating offshore wind). Lab Leadership: Directs DSRL, fostering industry collaboration and applied research.

• Geomagnetism
• Paleomagnetism
• Geophysics
• +۳ مورد دیگر

Dr. Lennart de Groot is an Associate Professor at Utrecht University's Faculty of Geosciences, Department of Earth Sciences, leading the Paleomagnetic Laboratory at Fort Hoofddijk. His academic journey includes a BSc (2007), MSc (2008), PhD (2013, Cum Laude), and postdoctoral research at Utrecht University. Specializing in geomagnetism and paleomagnetism, his work focuses on understanding rapid fluctuations in Earth's magnetic field using advanced techniques like micromagnetic tomography and multi-method paleointensity approaches. Research Interests: Geomagnetic field dynamics, paleointensity determination, rock magnetism, and micromagnetic analysis. Key Projects: Development of pymaginverse for geomagnetic modeling, study of Mid-Miocene geomagnetic reversals, and analysis of Devonian volcanic records. His articles highlight innovations in paleomagnetic measurement techniques and their applications to ancient geomagnetic field behavior. Notable awards include the ERC Starting Grant (2019), NWO-Vidi (2019), and the William Gilbert Award (2018). He advises on grants and mentors researchers in geophysics and rock magnetism, contributing to the UN Sustainable Development Goals through Earth science research. Lab affiliations include the Paleomagnetic Laboratory Fort Hoofddijk, where cutting-edge equipment enables high-resolution studies of magnetic minerals and their paleoenvironmental records.

Sharon Guniمشاهده پروفایل

استادیار

• Artificial Intelligence
• Intelligent Transportation Systems
• Reinforcement Learning
• +۶ مورد دیگر

Dr. Sharon Guni is an Assistant Professor in the Department of Computer Science & Engineering at Texas A&M University, affiliated with the College of Engineering. She directs the PiStar laboratory, focusing on advancing artificial intelligence (AI) theory and its practical applications, particularly in transportation systems and multi-agent coordination. Her research integrates reinforcement learning, combinatorial optimization, and game theory to address real-world challenges such as traffic congestion and autonomous vehicle management. Ph.D. in Information Systems Engineering, Ben-Gurion University (2015) M.S. in Information Systems Engineering, Ben-Gurion University (2012) B.S. in Information Systems Engineering, Ben-Gurion University (2011) Dr. Guni’s research interests span AI, intelligent transportation systems, reinforcement learning, and multiagent systems. Notable contributions include socially optimal traffic tolling mechanisms, conflict-based search algorithms for multi-agent pathfinding, and agent-based models for epidemiological inference. She has received prestigious awards, including the NSF CAREER Award (2023) and the AAAI Outstanding Paper Award (2016). Her lab’s work on self-optimizing traffic signal controllers has been featured in WIRED Magazine and multiple news outlets. Recent projects include socially optimal non-discriminatory policies for continuous-action games and curriculum generation for reinforcement learning. Awards: Bergmann Memorial Research Award (2024), Wilson Memorial Lecture (2025), AIJ Prominent Paper Award (2020) Grants: NSF CAREER Award, Texas A&M grants supporting traffic optimization and AI research PiStar collaborates on interdisciplinary projects, including autonomous driving demonstrations with Houston high schools and pandemic mitigation strategies via agent-based modeling. The lab hosts a dynamic team of graduate students and researchers advancing AI’s societal impact.

Savin Ivanمشاهده پروفایل

دانشیار

• economics of innovation
• environmental economics
• climate policy
• +۴ مورد دیگر

Savin Ivan is an Associate Professor of Quantitative Analytics at ESCP Business School's Madrid Campus, where he teaches Advanced Statistics, Machine Learning, and Innovation and Business Ideas courses. He also directs the Master in Management (MiM) specialization in 'AI and Robotics,' contributing significantly to the school's quantitative analytics curriculum and research initiatives. Education: PhD in Economics (2011) from Justus Liebig University of Giessen (Chair of Econometrics) Habilitation (2017) at KIT with thesis titled 'Applications of Evolutionary Optimization and Modelling in Economics' Savin Ivan's research spans multiple interconnected fields at the intersection of economics, environmental policy, and computational methods. His primary focus centers on the economics of innovation, where he examines how technological change and creative processes drive economic development. He has made significant contributions to environmental economics, particularly regarding climate policy effectiveness and implementation challenges. His work on complex systems applies evolutionary and agent-based modeling approaches to understand economic dynamics that traditional models cannot capture. His research on evolutionary economics explores how economic systems evolve through processes analogous to biological evolution, with particular attention to innovation diffusion and technological trajectories. His methodological expertise in machine learning and computational linguistics enables sophisticated analysis of large datasets related to climate policy and economic behavior. His recent publications reveal a clear trend toward interdisciplinary climate policy research that combines computational linguistics with environmental economics. A significant portion of his work analyzes the content of international climate commitments using text mining techniques. He increasingly investigates the social dimensions of climate policy, examining public opinion, cultural factors, and behavioral responses to different policy instruments. His research also demonstrates growing interest in the intersection of AI and climate policy, including comparing expert recommendations with AI-generated advice. Many of his papers employ agent-based modeling to simulate complex policy scenarios that traditional economic models cannot adequately address. Savin Ivan has built a substantial research portfolio with over 75 articles published in JCR-indexed international journals, including prestigious outlets such as Nature Sustainability, Nature Communications, Proceedings of the National Academy of Sciences, and numerous field-specific journals in innovation economics and climate policy. His work appears consistently in Q1 and D1 ranked journals, demonstrating both academic rigor and relevance to pressing societal challenges. Prior to joining ESCP, Ivan held postdoctoral positions at ICTA-UAB working on the ERC project EVOCLIM, where he studied climate policy effectiveness using public and expert surveys combined with artificial intelligence methods. He previously contributed to the KIT-BETA project on general-purpose technologies, creativity, and sustainability, and served as a postdoctoral researcher at Friedrich Schiller University in the Graduate College 'The Economics of Innovative Change.'

• Multi-scale granular material behavior
• Experimentally validated discrete element method (DEM) models
• Laboratory testing of granular materials
• +۵ مورد دیگر

Michelle Barry is an Associate Professor at the University of Arkansas , affiliated with the College of Engineering and the Department of Civil Engineering . She holds a Ph.D. and is a licensed Professional Engineer (P.E.) . Her research focuses on granular material behavior, discrete element method (DEM) modeling, and geotechnical applications in infrastructure safety and historic preservation. Ph.D., Texas A&M University (2013) M.S., Texas A&M University (2009) B.S., Texas A&M University (2008) Dr. Barry’s research interests include: Multi-scale granular material behavior Experimentally validated DEM models Laboratory testing of granular materials Applications of engineering in historic preservation Her teaching areas encompass Soil Mechanics , Numerical Modeling in Geotechnical Engineering , and Soil Dynamics . She has contributed to publications in journals such as Transportation Geotechnics , Geotechnical Testing Journal , and Engineering Geology . No specific scientific awards or student advisement details were listed in the provided materials.

• Light Scattering
• Radiative Transfer
• Optical Modeling
• +۳ مورد دیگر

Per Edström is a Professor at the Department of Engineering, Mathematics and Science Education (IMD) within Mid Sweden University . His research focuses on mathematical modeling of light scattering in paper and print , particularly addressing challenges in optical interactions and radiative transfer . Education: Doctoral thesis (2007) and Licentiate thesis (2004) on light scattering in paper, both from Mid Sweden University. Research Interests: Edström’s work spans radiative transfer theory , fluorescence modeling , and computational methods for simulating optical properties in turbid media. He has developed advanced models like DORT2002 to improve accuracy in paper industry applications , focusing on phenomena such as dot gain , goniochromism , and edge effects in halftone printing . Recent Publications: His studies (2013–2015) explore Monte Carlo simulations , particle dynamics , and high-speed nanofilm deposition , contributing to fields like optical measurement techniques and color prediction models . Labs and Teams: Affiliated with the FSCN (Fibre Science and Communication Network) at Mid Sweden University, he collaborates on projects involving microroughness analysis , inverse radiative transfer problems , and open-source simulation platforms .