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Hadi SalmasianView profile

Professor

• Lie Groups
• Representation Theory
• Algebra
• +4 more

Hadi Salmasian is a Full Professor in the Department of Mathematics and Statistics at the University of Ottawa, Faculty of Science. He holds a PhD from Yale University and specializes in Lie groups, Lie algebra representations, and related areas of algebra and mathematical physics. Education: PhD in Mathematics, Yale University Research Interests: Dr. Salmasian's research focuses on representation theory of Lie groups and Lie superalgebras, quantum groups, invariant theory, and applications to mathematical physics. His work explores topics such as Capelli eigenvalue problems, spherical functions on supergroups, and polynomiality of faithful dimensions for nilpotent groups. Recent Research Trends: His publications emphasize the interplay between algebraic structures (e.g., Weyl algebras, quantum homogeneous spaces) and representation-theoretic techniques, with applications to quantum computing and cryptography. Notable themes include classification of dual pairs in Lie supergroups and development of hash functions over finite groups. Awards: No awards explicitly mentioned in the provided texts. Advising & Grants: Supervised students include Manal Al-Zahrani, Mengyuan Cao (co-supervised with Monica Nevins), Dene Lepine, and Mitra Mansoori. Postdoctoral researchers include Ali Assem Mahmoud (co-supervised with Anne Broadbent and Monica Nevins). Research activities involve collaboration with groups in algebra and Lie theory. Labs/Teams: Active in research groups focused on algebra, Lie theory, and representation theory within the Department of Mathematics and Statistics at the University of Ottawa.

Suchuan DongView profile

Professor

• Computational and Applied Mathematics
• High-Order Numerical Methods
• Multiphase Flows
• +7 more

Suchuan Dong is a Professor in the Department of Mathematics at Purdue University , affiliated with the Center for Computational and Applied Mathematics . His work bridges Computational Mathematics and Machine Learning , focusing on High-Order Numerical Methods and Multiphase Flows . Academic Background Post-Doc in Applied Mathematics, Brown University (2004) Ph.D. in Mechanical Engineering, SUNY Buffalo (2001) M.S. in Physics, Zhejiang University (1995) B.S. in Aerospace Engineering, National University of Defense Technology (1992) His research centers on Neural Network-Based Numerical Methods and Data-Driven Scientific Computing , with applications to Computational Fluid Dynamics , Contact Line Dynamics , and High-Performance Computing . Publications highlight Physics-Informed Neural Networks , Energy-Stable Schemes , and Extreme Learning Machines for PDEs. The articles reflect trends in Neural Network Applications to Dynamic PDEs , Phase Field Modeling , and High-Dimensional Computing , often combining High-Order Numerical Methods with Interfacial Phenomena . His recent work focuses on Exact Time Integration Algorithms and Hidden-Layer Concatenation for stability and efficiency. He leads research in the Center for Computational and Applied Mathematics , emphasizing Thermodynamically Consistent Modeling and Flow-Structure Interactions . His teaching includes MA-36600: Ordinary Differential Equations (Spring 2025).

Alan EdelmanView profile

Professor

• Julia Programming
• High Performance Computing
• Linear Algebra
• +3 more

Alan Edelman is a Professor at the Massachusetts Institute of Technology (MIT), renowned for his work in high-performance computing, linear algebra, and random matrix theory. He is a co-creator of the Julia programming language, which emphasizes efficiency and versatility for scientific computing. His research integrates mathematics and computer science, focusing on numerical methods, parallel computing, and applications in fields like quantum control and climate modeling. Edelman leads projects such as Oceananigans.jl for geophysical fluid dynamics and Circuitscape for connectivity analysis in conservation biology. His academic contributions span theoretical advancements in matrix theory and practical implementations of computational tools. Edelman collaborates across disciplines, bridging scientific computing with machine learning and quantum physics. His work on differentiable programming frameworks and GPU acceleration has impacted both academic research and industry applications. Key Projects: Julia programming language, Oceananigans.jl, Circuitscape Research Themes: High-performance computing, numerical linear algebra, random matrices, scientific machine learning Affiliations: MIT’s Theory of Computation Community of Research, PI of multiple NSF-funded projects Edelman’s recent work emphasizes interdisciplinary applications, including climate policy modeling and automated materials discovery. His publications reflect a blend of foundational mathematics and cutting-edge computational techniques.

SHEN LeiView profile

Researcher

• Multiscale Modeling and Simulation
• Materials Informatics
• Computational Physics
• +3 more

SHEN Lei is a researcher at the National University of Singapore (NUS), affiliated with the Department of Physics. With a PhD in Physics from NUS, he specializes in Multiscale Modeling and Simulation and Materials Informatics , leveraging machine learning and computational methods for advanced materials discovery. Research Focus: Density functional theory, molecular dynamics, finite element analysis, and data-driven design of materials. Teaching: Modules include Mechanics and Waves (PC1433), Applied Quantum Mechanics (PC2130B), and Mechanical Properties of Materials (ESP2109). His work spans spintronics, ferroelectricity, and energy storage materials, with recent publications on interatomic potentials, sliding heterostructures, and battery anodes. He has received the Teaching Commendation Award and declined the Lee Kuan Yew Postdoctoral Fellowship . Notable Trends: Recent articles emphasize machine learning in materials science, van der Waals heterostructures, quantum transport, and medical image analysis. Subfields include Rashba spin-orbit coupling, piezoelectric tensor modeling, and defect-informed neural networks. Scientific Awards: Teaching Commendation Award (AY15/16; AY16/17) Lee Kuan Yew Postdoctoral Fellowship (2014) (declined)

Kai-Min ChungView profile

Research Fellow

• Quantum Cryptography
• Complexity Theory
• Pseudorandomness
• +3 more

Kai-Min Chung is a Distinguished Research Fellow at the Institute of Information Science (IIS), Academia Sinica, Taiwan. His research focuses on quantum cryptography, complexity theory, and pseudorandomness. Prior to this role, he completed a postdoctoral fellowship at Cornell University (supported by the Simons Foundation) and earned his Ph.D. in computer science from Harvard University under Salil Vadhan. Education Ph.D. in Computer Science, Harvard University (Advisor: Salil Vadhan) Postdoctoral Researcher, Cornell University Research Interests Chung's work bridges quantum computing and cryptography, addressing challenges in secure communication, post-quantum cryptography, and complexity-theoretic foundations. His contributions include groundbreaking results on quantum-resistant protocols, zero-knowledge proofs, and cryptographic primitives resilient to quantum adversaries. Recent research emphasizes the theoretical limits of quantum algorithms and their implications for cryptographic security. Professional Activities Program Committee Chair: Asiacrypt 2024, ITC 2023 Membership on committees for CRYPTO, EUROCRYPT, STOC, FOCS, and others Awards Best Student Paper Award at TCC 2010 Distinguished Paper Award at PLDI 2023 Simons Postdoctoral Fellowship Teaching & Mentoring Chung teaches advanced courses on modern cryptography and advises students in theoretical computer science. He actively recruits postdoctoral researchers and students to his lab, focusing on cutting-edge quantum and classical cryptographic systems.

Marco FarinaView profile

Professor

• Electromagnetic Fields
• Scanning Probe Microscopy
• Nanotechnology
• +4 more

Marco Farina is a Full Professor in Electromagnetics at the Department of Information Engineering, College of Engineering, Polytechnic University of Marche, Italy. His research spans electromagnetic modeling, scanning microwave microscopy, and nanotechnology, with applications in 2D materials, biosensors, and advanced measurement systems. He is a Senior Member of IEEE and actively contributes to Technical Committees on RF Nanotechnology. Laurea and Ph.D. in Electronic Engineering from University of Ancona Research interests focus on quantitative scanning microwave microscopy, electromagnetic analysis of active/passive components, and nanoscale characterization techniques. His work bridges theoretical modeling with practical implementation, including the development of the EM3DS software suite and novel inverted SMM systems. Recent publications highlight interdisciplinary applications in biomedical analysis and semiconductor physics. Scientific recognition includes the 3M-Nano Best Conference Paper Award and grants from US Army Research Laboratory and US Air Force Office of Scientific Research. He holds an ESA-funded patent for VNA calibration and has co-authored a book on planar structure analysis. Collaborative projects emphasize RF device optimization and biological imaging.

Vedhus HoskereView profile

Assistant Professor

• Image Analysis
• Machine Learning
• Artificial Intelligence
• +6 more

Vedhus Hoskere is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Houston. His research focuses on interdisciplinary areas at the intersection of civil engineering, computer science, and robotics, emphasizing automated infrastructure inspection, machine learning, and AI-driven solutions for structural health monitoring. He holds the Liu Huixian Earthquake Engineering Scholarship (2018) for his work on automated post-earthquake building inspections. Key research areas include image analysis, machine learning, robotics, scientific computing, and visualization. His work integrates computer vision with civil infrastructure challenges, such as flood modeling, structural damage assessment, and autonomous inspection systems using drones and robotics. Notable projects include developing digital twin frameworks for bridges, synthetic environment testing for inspection algorithms, and semi-supervised learning for disaster damage analysis. His recent publications highlight advancements in transformer networks for instance segmentation, physics-informed generative models for damage assessment, and AI-driven hurricane resilience strategies. Hoskere collaborates on platforms like InstaDam for automated damage segmentation and explores Bayesian neural networks for quantifying uncertainties in infrastructure monitoring. Key Awards: Liu Huixian Earthquake Engineering Scholarship (2018) Advising & Labs: While no specific student names or grant details are provided, his research group likely focuses on robotics, computer vision, and AI applications in civil engineering. He contributes to open-source tools like the InstaDam platform and collaborates with institutions like the University of Illinois and USACE.

• Cyber-Physical Systems
• Industry 4.0
• Augmented Reality
• +4 more

Thomas Ludwig is a Professor of Information Systems with a focus on Cyber-Physical Systems at the University of Siegen. He holds a PhD (summa cum laude) from the same institution and has led numerous research initiatives in Industry 4.0, digital transformation, and human-centered technology design. His work spans augmented reality (AR), gamification, and AI integration in manufacturing. Ludwig co-founded and coordinates the 'Mittelstand 4.0-Kompetenzzentrum Siegen' to support SMEs in digitalization. He has authored over 50 publications in top-tier journals and conferences, including Computer Supported Cooperative Work (CSCW) and Proceedings of the ACM on Human-Computer Interaction . His research has been recognized with awards such as the IHK Preis 2017 for Best Dissertation and the Artur-Woll-Preis. Education: Diplom-Wirtschaftsinformatiker from University of Siegen (2012), PhD in Information Systems (2016), with a focus on socio-technical systems and mobile/social media research. Research Interests: Cyber-Physical Systems, AR applications, gamification design, AI in production planning, and digital competency frameworks for SMEs. He leads projects like Fusion, KOKOS, and EKPLO, addressing challenges in collaborative work, disaster management, and industrial digitalization. Grants & Projects: Projects include EU-funded EMERGENT, BMBF-funded KOKOS, and the self-acquired EKPLO initiative for APS systems in SMEs. He also coordinates the Zukunftszentren KI NRW and the EDIH Südwestfalen. Awards: 32. IHK Preis 2017, Artur-Woll-Preis, pwc-Preis, and multiple best paper awards at international conferences. Labs/Teams: Part of the Cyber-Physical Systems Lab at University of Siegen and the interdisciplinary team behind the 'Rendezfood' and 'Advanced Planning Systems' initiatives.

Nika AkopianView profile

Associate Professor

• Quantum Photonics
• Nanowire Quantum Dots
• Quantum Networks
• +3 more

Nika Akopian is an Associate Professor and Group Leader at the Quantum Networks Group within the Department of Electrical and Photonics Engineering at the Technical University of Denmark (DTU). His research focuses on quantum nanophotonics, nanowire quantum dots, and multi-qubit photonic devices, with a particular emphasis on hybrid atomic-solid state systems and epsilon-near-zero materials for quantum networks. He leads the MultiQubit project funded by an ERC Consolidator Grant, exploring multi-qubit quantum photonic devices. Education includes a Ph.D. in Physics from the Technion – Israel Institute of Technology (2008), followed by postdoctoral research at Delft and Eindhoven Universities of Technology. Key awards include the ERC Consolidator Grant (2020), Villum Young Investigator Program (2014), and Veni Grant (2008). Research interests span quantum control of nanowire quantum dots, hybrid systems coupling quantum dots to atomic vapors, and epsilon-near-zero materials for integrated quantum networks. Major contributions include demonstrating frequency-locked quantum dot emission to atomic transitions and developing crystal-phase quantum dots in nanowires. Scientific awards highlight his work, including the IUPAP Young Author Award (2006) and Gutwirth Fellowship (2006). His team includes advisees such as A. Srikanth, R. Radhakrishnan, and D. Li. Current projects involve advancing quantum networks and multi-qubit photonic devices.

• New Product Development
• Knowledge Management
• Collaborative Work Environments
• +5 more

Angelo Corallo is an Associate Professor at the Department of Experimental Medicine, University of Salento, specializing in technologies and methodologies for collaborative processes in industrial systems. His research spans Digital Business Ecosystems , Cybersecurity , and Collaborative Product Design , focusing on the interplay between technology and organizational dynamics. He leads interdisciplinary research divisions in Open Networked Business Management , Learning and Innovation , and Collaborative Product Design . Research Interests : Corallo's work integrates Information and Communication Technologies (ICT) with Business Management, particularly in Digital Twins for healthcare and manufacturing Knowledge Modeling and Ontology Engineering Industry 4.0 and Smart Manufacturing Agri-Food Sustainability through digitalization Scientific Contributions : His recent articles explore trends in Cybersecurity for Industrial IoT Metaverse Applications in business models Traceability Systems in food supply chains Collagen-Based Biomaterials from aquaponics

• Mathematical Physics
• Partial Differential Equations
• Probability
• +3 more

Felipe Hernández is an Assistant Professor in the Department of Mathematics at Pennsylvania State University. He is affiliated with the Department of Mathematics, located in McAllister Building, and can be contacted at felipeh@psu.edu. His research interests span Mathematical Physics, Partial Differential Equations, and Probability, with a focus on quantum systems, stochastic processes, and theoretical analysis of complex systems. His work explores topics such as quantum diffusion in disordered systems, decoherence dynamics, and the interplay between classical and quantum mechanics. He also investigates computational methods like neural networks to enhance accuracy in quantum chemistry calculations and explores foundational questions in quantum computing, such as BosonSampling complexity. Recent contributions include studies on Hodge systems, divergence-free vector fields, and endpoint estimates in functional analysis. While no specific awards or grants are listed, his research demonstrates a commitment to advancing mathematical physics and computational methods through rigorous theoretical analysis and interdisciplinary approaches.

Xiaomei YangView profile

Lecturer

• Soil Contamination
• Environmental Monitoring
• Microplastic Fate
• +5 more

Xiaomei Yang is a Lecturer/Researcher at the Soil Physics and Land Management Group of Wageningen University & Research, focusing on soil contaminants including pesticides and microplastics. Her work examines contaminant interactions with soil processes, their environmental fate, and impacts on soil-water-plant systems. She actively contributes to the International Land and Water Management Program (BSc/MSc), mentoring students in thesis research and internships. Key Projects: MINAGRIS: Investigating microplastic sources, fate, and ecosystem impacts in agricultural soils. ISQAPER: Developing interactive soil quality assessments for Europe and China. Soils4Africa: Creating an open-access soil information system for African agricultural resilience. Research Themes: Soil management, ecotoxicology, environmental monitoring, and agroecosystem sustainability. Specific interests include pesticide transport dynamics, microplastic behavior, and ecological risk assessment in agricultural systems. Achievements: Clarivate Highly Cited Scientist (2023) Top 2% Global Scientists (Elsevier/Stanford, 2024) Lead researcher on EU-China collaborative projects (e.g., ISQAPER) Teaching: Oversees MSc thesis supervision, internships, and courses like Sustainable Soil Management: Soil4Life and Land Degradation and Remediation .

Bin LiView profile

Associate Professor

• Quantum Optics
• Quantum Information Science
• Optical Engineering
• +3 more

Bin Li is an Associate Professor and Associate Chair of Actuarial Science in the Department of Statistics and Actuarial Science at the University of Waterloo. He holds a PhD in Applied Mathematical and Computational Sciences (2013, University of Iowa), and master's and bachelor's degrees in Computational Mathematics from Xi’an Jiaotong University (2008 and 2005, respectively). His research focuses on quantum optics and optical engineering, particularly in developing robust laser-driven systems for quantum light sources, solid-state emitters, and trapped ion quantum computing. He has pioneered techniques like Notch-filtered Adiabatic Rapid Passage (NARP) and advanced femtosecond pulse engineering for high-performance quantum systems. His work bridges theoretical quantum physics with experimental optical innovations. Research interests include: Optical driving schemes for quantum emitters Adiabatic inversion and rapid passage methodologies Individual ion addressing in quantum simulators Spin dynamics in 2D perovskite materials Publications span 2018–2025, emphasizing advancements in quantum engineering, ultrafast optics, and atomic-scale systems. While no scientific awards are explicitly listed, his impactful contributions to quantum technologies suggest active recognition in the field. Advising and grants: No specific advisees or grants are documented in the provided texts, though his research activities imply involvement in graduate supervision and funding programs.

• Theoretical Physics
• Quantum Foundations
• Density Functional Theory
• +5 more

Russell Thompson is an Associate Professor at the University of Waterloo, affiliated with the Waterloo Institute for Nanotechnology. His research focuses on theoretical physics, with expertise in self-consistent field theory, density functional theory, quantum foundations, and atomic physics. He holds a Doctorate in Theoretical Physics and Applied Mathematics from the University of Western Ontario (1998), complemented by a BSc (Honours Physics) from the University of Ottawa (1994) and an MSc in Physics from the University of Regina (1994). Thompson teaches advanced courses such as NANO 600 (Introduction to Nanotechnology), NE 216/217 (Advanced Calculus and Numerical Methods), and PHYS 234 (Quantum Physics 1). His recent publications (2020–2025) explore quantum foundations, polymer physics, and materials science, with a focus on integrating theoretical frameworks like DFT and SCFT into nanotechnology applications. His articles highlight advancements in quantum entanglement visualization, polymer foaming models, and atomic shell structure predictions. He has no listed scientific awards or grants in the provided data but remains active in interdisciplinary research at the intersection of quantum theory and polymer science.

• Model Engineering
• Web Engineering
• Process Engineering
• +9 more

Gerti Kappel is a full professor at the Institute of Information Systems Engineering at TU Wien, affiliated with the Business Informatics Group (BIG). Since 2020, she has served as Dean of the Faculty of Informatics at TU Wien, previously holding the role of Dean’s team member responsible for research, diversity, and financial affairs (2016–2019). She previously held a full professorship in computer science (database systems) and led the Department of Information Systems at Johannes Kepler University Linz (1993–2001). Her research focuses on Model Engineering, Web Engineering, and Process Engineering, particularly in cyber-physical production systems. She has co-authored influential works such as UML@Work (2005), UML@Classroom (2015), and Web Engineering (2006). Key projects include leadership roles in Vienna Informatics Living Lab (2018–2019), MPM4CPS (2014–2019), and ARTIST (2012–2015), addressing topics like model versioning, cloud architecture modeling, and inter-organizational systems. Her recent articles explore circular systems engineering, IoT-based simulation environments, and model-driven approaches for time-series analytics and cloud applications. She actively contributes to academic governance, including managing the Office of the Dean (E199-01) and overseeing faculty services. Her work emphasizes bridging theory and practice through collaborative frameworks like ERPEL and TROPIC . Grants: Projects funded by Austrian Research Promotion Agency, European Cooperation in Science and Technology, Vienna Business Agency, and others. Advising: Supervised over 15 graduate theses, including recent works on model-driven techniques for railway planning, debugging frameworks for modeling tools, and cloud-based IDEs. Labs/Teams: Leads research within the Business Informatics Group (BIG) and collaborates with the Vienna Informatics Living Lab for applied systems engineering.