جست‌وجوی استاد و پژوهشگر

• Optical Atomic Clocks
• Metrology
• Spectroscopy
• +۶ مورد دیگر

Piotr Ablewski is an Assistant Professor at the Department of Applied Informatics , Institute of Technical Sciences , within the Faculty of Physics, Astronomy and Applied Computer Science at Nicolaus Copernicus University. His research focuses on optical atomic clocks, precision metrology, and dark matter detection through global clock networks. Research Areas: Optical clocks, spectroscopy, quantum metrology, dark matter detection, frequency standards, and atmospheric science. Key Collaborations: Member of the "Biophysics at the Nanoscale" research team. Participates in multi-center work on clock development and dark matter studies. Publications: 31 documented publications with a total impact factor of 33,493 and ministerial score of 577. Instrumentation: Works on VIPA spectrometer calibration, frequency comb spectroscopy, and fiber-optic time/frequency delivery systems. Email: piotra@umk.pl

Matthias Zeisbergerمشاهده پروفایل

پژوهشگر

• Nanophotonics
• Optical Fiber Technology
• 3D Nanoprinting
• +۷ مورد دیگر

Dr. Matthias Zeisberger is a researcher at the Leibniz Institute of Photonic Technology (IPHT) , working in the Fiber Photonics department. His research focuses on advanced photonic device engineering through 3D nanoprinting, with particular expertise in optical fiber functionalization, hollow-core waveguide design, and metasurface integration for enhanced light manipulation. His work addresses critical challenges in Nanophotonics , Optical Fiber Technology , and Integrated Photonics through innovations like: Nanostructured fiber tips for broad-angle light coupling 3D holograms on multicore fibers for remote focus control Optofluidic platforms for nanoparticle tracking Phase-modulated hollow-core waveguides for higher-order mode excitation Key applications span Quantum Technologies , Biophotonics , and Environmental Monitoring . While his publications demonstrate leadership in experimental and computational photonics, no formal advising roles or scientific awards are mentioned in the available texts.

Fehmi Cirakمشاهده پروفایل

استاد

• Computational Mechanics
• Finite Element Analysis
• Structural Engineering
• +۵ مورد دیگر

Professor Fehmi Cirak is a faculty member at the University of Cambridge, Department of Engineering, specializing in Computational Mechanics. He joined Cambridge in 2006 after five years as a Senior Scientist at the California Institute of Technology (Caltech). His research integrates advanced computational methods with structural and materials analysis, emphasizing innovation in finite element techniques and data-informed modeling.

Jayesh Badwaikمشاهده پروفایل

پژوهشگر

• Computational Physics
• High Performance Computing
• Software Engineering
• +۴ مورد دیگر

Dr. Jayesh Badwaik is a Scientific Researcher at the Jülich Supercomputing Center (JSC) within Forschungszentrum Jülich, a leading interdisciplinary research center in Europe. His work is centered in the Accelerating Devices Lab, where he focuses on high-performance computing architectures and computational methods for scientific applications. Dr. Badwaik's research spans multiple disciplines at the intersection of computer science, physics, and mathematics. His primary research interests include: Computational Physics and numerical methods for scientific computing High Performance Computing (HPC) with focus on exascale systems GPU programming models and accelerated computing Software engineering for large-scale scientific applications Lattice Boltzmann Methods for fluid dynamics simulations Parallel numerical algorithms for conservation laws Analysis of Dr. Badwaik's publication record reveals a clear evolution from theoretical numerical methods toward practical implementation on cutting-edge computing architectures. His early work (2016-2020) focused on mathematical foundations of numerical schemes for conservation laws, while his recent publications (2023-2024) demonstrate increasing emphasis on exascale computing challenges. His contributions to the JUPITER benchmark suite represent significant work in evaluating next-generation supercomputing systems. A substantial portion of his research centers on scaling the Lattice Boltzmann Method to exascale platforms, addressing critical challenges in computational fluid dynamics at unprecedented scales. His expertise in GPU programming is evident from his practical overview of programming models, which provides valuable insights for the HPC community. Dr. Badwaik is actively involved in the Accelerating Devices Lab at JSC, contributing to Europe's high-performance computing ecosystem. His work bridges theoretical numerical analysis with practical implementation on advanced computing architectures, making significant contributions to scientific computing at scale. His research has implications for multiple scientific domains that rely on large-scale simulations, including climate modeling, materials science, and computational fluid dynamics.

Zoltan Kocsisمشاهده پروفایل

مدرس

• Mathematical Logic
• Set Theory
• Lattices
• +۲۸ مورد دیگر

Dr. Zoltan Kocsis is a mathematical logician and educator based at the University of New South Wales (UNSW), where he currently holds the position of Adjunct Lecturer. His research spans multiple areas including proof theory, nonstandard analysis, category theory, and computational logic, with a focus on logical verification, degree of satisfiability, and structured decompositions. PhD in Mathematics from the University of Manchester (2019) Adjunct Lecturer at UNSW Work with interactive theorem proving software like Agda Dr. Kocsis' work on degree of satisfiability explores the probability of logical formulas holding in algebraic structures, revealing gaps in equations from Heyting algebras to group theory. His research on structured decompositions and spined categories provides categorical frameworks for fixed-parameter tractability and tree-width generalizations. In formal verification, he contributed to the seL4 kernel on RISC-V architecture. Recent publications include Proof-theoretic methods in quantifier-free definability (2025), Apartness relations between propositions (2024), and Degree of satisfiability in Heyting algebras (2024). Earlier works cover pseudo-random sequences, homology, and nonstandard analysis in group theory. He has received the CSIRO SCS Engineering and Technology award (2021) and the IBM Prize (2018) for his contributions to logical satisfiability. His collaborations include work with Ben Bumpus on spined categories and Jade Master on structured decompositions, alongside teams at CSIRO and Tallinn University of Technology.

Sebastian Ahnertمشاهده پروفایل

دانشیار

• Algorithmic Information Theory
• Network Analysis
• Genotype-Phenotype Maps
• +۴ مورد دیگر

Dr. Sebastian Ahnert is an Associate Professor at the Department of Chemical Engineering and Biotechnology, University of Cambridge, and a Senior Research Fellow at The Alan Turing Institute. He leads the Structural Complexity research group and is a Fellow of King's College, Cambridge. Current Positions: Associate Professor (Cambridge), Senior Research Fellow (Alan Turing Institute), Fellow (King's College) Research Interests: Algorithmic information theory, network analysis, genotype-phenotype maps, interdisciplinary applications in biology, humanities, and food science His work spans the quantification of biological complexity using algorithmic descriptions, including protein quaternary structure classification , RNA sequence-structure maps , and symmetry in evolutionary systems . Network analysis applications extend to historical correspondence (Tudor Networks of Power), food science (flavor compound networks), and connectomes . Recent publications emphasize non-deterministic genotype-phenotype maps , neutral set thermodynamics , and automated phenotyping technologies. Award highlights: 2024 Richard Deswarte Prize in Digital History Shortlisted for 2024 SHARP Book History Prize Current students include PhD candidates in computational biology and plant science, with former advisees contributing to RNA evolution and network analysis studies. Collaborations span quantum physics, plant developmental biology, neuroscience, and digital humanities.

Abdul K. Parchurمشاهده پروفایل

استادیار

• MRI-guided adaptive radiation therapy
• Artificial Intelligence in radiotherapy
• Synthetic CT generation
• +۵ مورد دیگر

Abdul K. Parchur, PhD, is an Assistant Professor in the Department of Radiation Oncology at the University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center. He holds a dual role as a Medical Physicist, specializing in advanced radiotherapy technologies. His academic credentials include: B.Sc. in Physics from Acharya Nagarjuna University, India (2003) M.Sc. in Physics from Dr. Harisingh Gour Central University, India (2005) Ph.D. in Physics from Dr. Harisingh Gour Central University, India (2010) CAMPEP Certificate in Medical Physics from Medical College of Wisconsin (2022) Therapeutic Medical Physics Residency at Medical College of Wisconsin (expected 2025) Dr. Parchur's research integrates artificial intelligence, medical imaging, and nanotechnology to innovate radiation therapy workflows. His primary focus includes developing AI-driven solutions for MRI-guided adaptive radiotherapy, synthetic CT generation, and quality assurance protocols. He pioneers methods to optimize treatment accuracy through automated image analysis and machine learning classifiers. His recent publications demonstrate a strong emphasis on translating nanotechnology into clinical applications, particularly through theranostic nanoparticles for image-guided cancer therapy. Research trends reveal interdisciplinary convergence of medical physics, materials science, and AI, with consistent focus on improving treatment personalization and efficiency in radiation oncology. Dr. Parchur contributes to several collaborative research initiatives at the Greenebaum Comprehensive Cancer Center, focusing on technology development for precision radiation therapy. Current projects involve AI-based treatment planning optimization and nanoparticle-enhanced radiotherapy protocols.

• Cryptography
• Post-Quantum Cryptography
• Cryptographic Protocols
• +۳ مورد دیگر

Kirthivaasan Puniamurthy is a Doctoral Researcher at Aalto University's Department of Mathematics and Systems Analysis. His work focuses on cryptography, particularly post-quantum cryptography and cryptanalytic techniques. Research areas: Cryptography, Security Analysis, Discrete Mathematics Collaborators: Chris Brzuska, Estuardo Alpirez Bock, Milan Šorf Notable Publications include advancements in lattice-based cryptography and secure computation techniques published at top conferences like ACNS and ASIACRYPT.

• Artificial Intelligence
• Theoretical Computer Science
• Fuzzy Logic
• +۳ مورد دیگر

Gégény Dávid is a researcher at the University of Miskolc 's Faculty of Mechanical Engineering and Informatics . His work focuses on fuzzy rough sets, lattice structures, and approximation algorithms. Affiliation: Institute of Mathematics, University of Miskolc Doctoral School: József Hatvany Doctoral School of Informatics (since 2006) Research Interests : Fuzzy Rough Set Theory Lattice and Conceptual Structures Pattern Mining Algorithms Granular Computing Tolerance Relations Mathematical Modeling Publications (2019-2024) span journals like International Journal of Approximate Reasoning , Knowledge-Based Systems , and conferences including IEEE FUZZ-IEEE . Key themes include Optimistic approximations in multigranular systems Rough set applications in image processing Interpolation methods for fuzzy environments Lattice-theoretic foundations for knowledge discovery

Jessica Sorrellمشاهده پروفایل

استادیار

• Machine learning theory
• Algorithms and complexity
• Privacy in machine learning
• +۵ مورد دیگر

Jessica Sorrell is an Assistant Professor in the Department of Computer Science at Johns Hopkins University and a member of the Data Science and AI Institute. Her research focuses on the theoretical foundations of machine learning, emphasizing replicability, privacy, fairness, and robustness. She has contributed to lattice-based cryptography and secure computation. Johns Hopkins University (Assistant Professor, Department of Computer Science) University of Pennsylvania (Postdoctoral Researcher) University of California, San Diego (PhD in Computer Science) Rochester Institute of Technology (Undergraduate in Applied Mathematics) Research Areas: Theoretical machine learning Replicability and reproducibility of statistical algorithms Differential privacy and adaptive generalization Lattice-based cryptography Secure computation protocols Publications highlight her work on replicable reinforcement learning, algorithmic stability, and cryptographic techniques. She previously studied at UCSD under Daniele Micciancio and Russell Impagliazzo. Teaching: Spring 2025: Theory of Replicable Machine Learning (EN.601.774).

Abhi Saxenaمشاهده پروفایل

پژوهشگر ارشد

• Photonics
• Superconducting Optoelectronics
• Nanofabrication
• +۴ مورد دیگر

Abhi Saxena is a Postdoctoral Fellow at the University of Colorado Boulder and a researcher at the National Institute of Standards and Technology (NIST) , Boulder. His academic journey includes a Ph.D. in Electrical & Computer Engineering from the University of Washington, Seattle, under the mentorship of Professors Arka Majumdar and Rahul Trivedi, and a bachelor’s degree in Electrical Engineering from the Indian Institute of Technology (IIT) Delhi. Ph.D., Electrical & Computer Engineering, University of Washington, Seattle B.Tech, Electrical Engineering, Indian Institute of Technology (IIT) Delhi Abhi’s research focuses on the intersection of photonics , superconducting optoelectronics , nanofabrication , and neuromorphic systems . His work involves designing and fabricating photonic devices for quantum simulation, particularly using coupled cavity arrays (CCA) to engineer Hamiltonians. He has contributed to advancements in boundary tomography algorithms, site-controllable CCAs, and improving single-photon sources via nanocavities. His recent publications highlight trends in quantum simulation , integrated photonics , and phase-change materials for non-volatile photonic devices. Key areas include microring arrays , superradiance , and graph-based photonic systems . He also explores computational spectroscopy using meta-optics and silicon photonics with graphene heaters . Currently, Abhi is affiliated with the Quantum Nanophotonics Group at CU Boulder and NIST, where he works on transmitter circuits and integrated photonic systems. His Google Scholar profile lists 15 recent contributions to these fields.

Jose Ladoمشاهده پروفایل

استادیار

• Quantum Materials
• Graphene
• Topological Superconductivity
• +۵ مورد دیگر

Jose Lado is an Assistant Professor at the Department of Applied Physics, Aalto University. His research focuses on exotic quantum states in two-dimensional materials and twisted van der Waals systems, including topological superconductivity, quantum spin liquids, and fractionalized matter. He actively collaborates with experimental groups and leads projects like ULTRATWISTROICS and ERC-funded FQF P4 T30428 . Research Interests : Correlated quantum materials, topological superconductivity, graphene-based heterostructures, and moiré quantum matter Key Themes : Electronic correlations, symmetry-breaking states, quantum engineering of fractional particles, and spin-textured flat bands His recent publications emphasize non-Hermitian topology, Kondo lattice dynamics, and machine learning applications in many-body systems. Awards include three Early Career recognitions (2021-2023). He contributes to UN Sustainable Development Goals through quantum material innovation.

Emily Edwardsمشاهده پروفایل

عضو هیئت علمی

• Science Communication
• Quantum Information Science
• STEM Education
• +۳ مورد دیگر

Emily Edwards is an Associate Research Professor in the Department of Electrical and Computer Engineering at Duke University, affiliated with the Duke Quantum Center. She specializes in science communication and informal STEM education for quantum information science. B.S. in Physics from Appalachian State University (2002) M.S. in Physics from University of Maryland, College Park (2008) Ph.D. in Physics from University of Maryland, College Park (2009) Her research focuses on translating complex quantum engineering concepts into accessible educational materials through: Interactive gamified learning platforms Teacher training programs for quantum curriculum Public engagement initiatives Development of quantum education frameworks Recent publications demonstrate expertise in quantum education tools (2025), program development (2022), and foundational quantum simulation techniques spanning 2010-2025. Scientific Awards APS Fellows (American Physical Society), 2022 She actively bridges quantum research and public understanding through: Collaborative workshop leadership Emerging tech visualization systems Science policy contributions Quantum workforce development

Rizwan Uddinمشاهده پروفایل

استاد

• Nuclear Engineering
• Reactor Physics
• Thermal Hydraulics
• +۷ مورد دیگر

Rizwan Uddin is a Professor and Head of the Department of Nuclear, Plasma, and Radiological Engineering at the University of Illinois at Urbana-Champaign. He holds joint appointments as Professor of Computational Science and Engineering and is affiliated with the Institute for Sustainability, Energy, and Environment. His career spans over two decades, including roles at the University of Virginia prior to his current positions. Ph.D., Nuclear Engineering, University of Illinois (1987) M.S., Nuclear Engineering, University of Illinois (1983) B.S., Mechanical Engineering, Middle East Technical University (1980) His research focuses on Nuclear Engineering , Computational Biology , Nonlinear Dynamical Systems , Reactor Thermal Hydraulics , and Multi-Physics Modeling and Simulation . He specializes in advanced reactor designs, computational methods for reactor physics, and human factors in nuclear systems. Recent publications highlight his work in hybrid numerical methods , turbulence modeling in porous media , and application of digital twins for reactor simulation. His 2024 paper explores XR technologies for human factor studies, while 2022-2021 works refine nodal integral methods and code verification techniques. Scientific Awards : Fellow of the American Nuclear Society (2014), multiple Mark Mills Award advisor recognitions, Best Paper Awards, and teaching honors. Grants and Funding : National Center for Supercomputing Applications (NCSA) Fellow (2008-2009), collaborative projects with Nano Nuclear. He leads the Virtual Education & Research Laboratory and has served on university and departmental committees, including the Computational Science and Engineering Steering Committee.

• Combinatorics
• q-Matroid Theory
• Algebraic Coding Theory
• +۳ مورد دیگر

Rakhi Pratihar is a Postdoctoral Research Fellow at Inria Saclay Centre, France, affiliated with the GRACE research team. Her work bridges combinatorics, algebraic coding theory, and topological structures, focusing on rank metric codes, q-matroids, and shellable simplicial complexes. Research interests include: Decoding algorithms for rank metric codes and their cryptographic applications Generalizations of shellable q-complexes and matroid-like structures Topological and algebraic invariants (e.g., Betti numbers, Euler characteristic) of coding-theoretic objects Her publications span topics like Reed-Muller codes, Gabidulin codes, and Schur squares of Twisted Generalized Reed-Solomon codes, often exploring connections between coding theory and algebraic topology. She employs computational tools like SageMath for algebraic implementations. Rakhi collaborates with researchers such as Alain Couvreur, Sudhir R. Ghorpade, and Trygve Johnsen. Her work has been supported by institutions linked to Inria and the Simons Foundation.