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Work with thought leaders and academic experts in Mathematical Physics

Companies can greatly benefit from working with experts in the field of Mathematical Physics. These researchers possess a unique skill set that can be applied to various industries. They excel in data analysis, optimization, and problem-solving. By collaborating with a Mathematical Physics expert, companies can enhance their research capabilities, gain insights into complex systems, and improve decision-making processes. Whether it's developing advanced algorithms, optimizing supply chains, or analyzing large datasets, a Mathematical Physics expert can provide valuable expertise and innovative solutions.

Researchers on NotedSource with backgrounds in Mathematical Physics include Michael Sebek, Nicolangelo Iannella, Dr. Gerald Cleaver, Ph.D. Physics, Vladislav Zakharov, PhD, Ekwevugbe Omugbe, PhD, Dario Javier Zamora, and Dmitry Batenkov, Ph.D..

Michael Sebek

Boston, Massachusetts, United States of America
Northeastern University
Most Relevant Research Expertise
Mathematical Physics
Other Research Expertise (6)
network science
food science
electrochemistry
nonlinear dynamics
Applied Mathematics
And 1 more
About
Michael Sebek is a highly educated and experienced chemist with a passion for research and teaching. He received his Bachelor of Science in Chemistry from Truman State University in 2012, where he conducted undergraduate research in the field of analytical chemistry. He then went on to earn his Masters and Ph.D. in Chemistry from Saint Louis University by 2017, where his research focused on the interplay between network science and electrochemistry. After completing his Ph.D., Michael continued his research as a Post-Doctoral Researcher at Northeastern University, where he works in food science, network medicine, and AI/ML. His work has been published in several peer-reviewed journals and has been presented at national and international conferences.
Most Relevant Publications (4+)

21 total publications

Synchronization of three electrochemical oscillators: From local to global coupling

Chaos: An Interdisciplinary Journal of Nonlinear Science / Apr 01, 2018

Liu, Y., Sebek, M., Mori, F., & Kiss, I. Z. (2018). Synchronization of three electrochemical oscillators: From local to global coupling. Chaos: An Interdisciplinary Journal of Nonlinear Science, 28(4). https://doi.org/10.1063/1.5012520

Revival of oscillations from deaths in diffusively coupled nonlinear systems: Theory and experiment

Chaos: An Interdisciplinary Journal of Nonlinear Science / Jun 01, 2017

Zou, W., Sebek, M., Kiss, I. Z., & Kurths, J. (2017). Revival of oscillations from deaths in diffusively coupled nonlinear systems: Theory and experiment. Chaos: An Interdisciplinary Journal of Nonlinear Science, 27(6). https://doi.org/10.1063/1.4984927

Plasticity facilitates pattern selection of networks of chemical oscillations

Chaos: An Interdisciplinary Journal of Nonlinear Science / Aug 01, 2019

Sebek, M., & Kiss, I. Z. (2019). Plasticity facilitates pattern selection of networks of chemical oscillations. Chaos: An Interdisciplinary Journal of Nonlinear Science, 29(8). https://doi.org/10.1063/1.5109784

Finding influential nodes in networks using pinning control: Centrality measures confirmed with electrochemical oscillators

Chaos: An Interdisciplinary Journal of Nonlinear Science / Sep 01, 2023

Bomela, W., Sebek, M., Nagao, R., Singhal, B., Kiss, I. Z., & Li, J.-S. (2023). Finding influential nodes in networks using pinning control: Centrality measures confirmed with electrochemical oscillators. Chaos: An Interdisciplinary Journal of Nonlinear Science, 33(9). https://doi.org/10.1063/5.0163899

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Nicolangelo Iannella

Oslo
Senior Research fellow, The University of Oslo, Faculty of Mathematics and Natural Sciences
Most Relevant Research Expertise
Mathematical Physics
Other Research Expertise (18)
Neuromorphic circuits
Neural networks, Neural learning and applications
Theoretical and Mathematical neuroscience
Computational neuroscience
Artificial Intelligence
And 13 more
About
Following pre-doctoral studies in Mathematics and Theoretical Physics, I received a PhD in Computational Neuroscience from the University of Electro-Communications, Japan in 2009. From 2009, I was a Postdoctoral Researcher in RIKEN BSI. In 2010, I won the prestigious Australian Research Council (ARC) Australian Postdoctoral Award (APD) fellowship, based at the University of Adelaide from 2010–2014. In 2012 he completed a Graduate Certificate in Education (Higher Education) (GCEHE) from the University of Adelaide. From 2014–2017 he was an adjunct research fellow at the University of South Australia. From 2016–2018, he was a Cascade (Marie Curie) Research Fellow in Mathematical Sciences at the University of Nottingham. From 2018- a research fellow at the University of Oslo. His research interests include AI, Artificial and spiking neural networks and learning algorithms, synaptic plasticity, neuronal dynamics, and neuromorphic engineering. Dr. Iannella is a member of SFN and a Senior member of the IEEE.
Most Relevant Publications (1+)

47 total publications

Time As a Geometric Property of Space

Frontiers in Physics / Nov 17, 2016

Chappell, J. M., Hartnett, J. G., Iannella, N., Iqbal, A., & Abbott, D. (2016). Time As a Geometric Property of Space. Frontiers in Physics, 4. https://doi.org/10.3389/fphy.2016.00044

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Dr. Gerald Cleaver, Ph.D. Physics

Waco, Texas, United States of America
Professor of Physics, Baylor University
Most Relevant Research Expertise
Mathematical Physics
Other Research Expertise (8)
String Theory
Cosmology
Quantum Gravity
Nuclear and High Energy Physics
Astronomy and Astrophysics
And 3 more
About
Dr. Gerald B. Cleaver is a highly skilled and experienced problem solver. He especially enjoys projects simultaneously requiring large- and small-scale analysis, wherein logic meets creativity, and abstract thinking is applied to real-world situations. Cleaver is a dedicated leader with over 22 years of management experience of research groups, and is an eloquent communicator with more than 24 years of teaching experience. He directs the Early Universe Cosmology and Strings (EUCOS) division of Baylor University's Center for Astrophysics, Space Physics, and Engineering Research (CASPER) and has advised the dissertation research of 20 M.S. & Ph.D. students (13 graduated, 8 current). During his 2013 to 2022 tenure as Physics Graduate Program Director, Cleaver coordinated the graduate programs of over 100 students and managed the \~ $700K teaching assistantship budgets. Working with faculty colleagues, he doubled the physics graduate student enrollment from 25 in 2013 to the present 52. Cleaver was written over 85 peer-reviewed research journal articles and 25 conference proceedings. He has spoken at more than 70 conferences and workshops. Cleaver is co-author of one physics textbook and has authored six book chapters and an encyclopedia entry.
Most Relevant Publications (2+)

91 total publications

Aspects of fractional superstrings

Communications in Mathematical Physics / Jan 01, 1995

Cleaver, G. B., & Rosenthal, P. J. (1995). Aspects of fractional superstrings. Communications in Mathematical Physics, 167(1), 155–182. https://doi.org/10.1007/bf02099356

Casimir energy and brane stability

Journal of Geometry and Physics / Mar 01, 2011

Obousy, R., & Cleaver, G. (2011). Casimir energy and brane stability. Journal of Geometry and Physics, 61(3), 577–588. https://doi.org/10.1016/j.geomphys.2010.11.006

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Vladislav Zakharov, PhD

Stony Brook, New York, United States of America
Stony Brook University
Most Relevant Research Expertise
Mathematical Physics
Other Research Expertise (6)
AMO & nuclear experiment
Atomic and Molecular Physics, and Optics
Electrical and Electronic Engineering
Nuclear Energy and Engineering
Nuclear and High Energy Physics
And 1 more
About
Vladislav Zakharov has earned a PhD in physics from Stony Brook University after working for professor Thomas K. Hemmick to help design and build a new Time Projection Chamber (TPC) for the sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Lab (BNL). His dissertation focused on a technique to suppress Ion Back-Flow (IBF) in a TPC.
Most Relevant Publications (1+)

7 total publications

The effects of a passive Bi-Polar Grid (BPG) on Ion Back-Flow (IBF) and resolution

Journal of Instrumentation / Jun 01, 2023

Zakharov, V., Shulga, E., Garg, P., Hemmick, T., & Milov, A. (2023). The effects of a passive Bi-Polar Grid (BPG) on Ion Back-Flow (IBF) and resolution. Journal of Instrumentation, 18(06), C06024. https://doi.org/10.1088/1748-0221/18/06/c06024

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Ekwevugbe Omugbe, PhD

Owerri
Lecturer II, Physics department at University of Agriculture and Environmental Sciences, Umuagwo
Most Relevant Research Expertise
Mathematical Physics
Other Research Expertise (4)
General Physics
Quantum mechanics
Particle Physics
Material Physics
About
Dr. Ekwevugbe Omugbe is a highly accomplished physicist with a PhD in Theoretical and Mathematical Physics from the Federal University of Petroleum Resource Effurun. He also holds a Master of Science in Electronics from the University of Benin and a Bachelor of Science in Physics with Electronics from the University of Port Harcourt. With over 5 years of teaching experience, Dr. Omugbe has worked as a Lecturer II at the University of Agriculture and Environmental Sciences, Umuagwo, as well as an Assistant Lecturer at Nigeria Maritime University and a Lecturer at Delta State Polytechnic, Otefe. He has a strong passion for teaching and has been recognized for his excellent teaching skills and ability to engage students. Dr. Omugbe's research interests include theoretical and mathematical physics, as well as Condensed matter physics and theoretical particle Physics. He has published several papers in reputable journals and has presented his research at various national and international conferences. Aside from his academic pursuits, Dr. Omugbe is also actively involved in community service and outreach programs, using his knowledge and skills to make a positive impact in society. He is a dedicated and passionate scientist, always seeking to expand his knowledge and contribute to the advancement of the field of physics.

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Dario Javier Zamora

Ph.D. in physics with expertise in Statistical Physics, Complex Systems, Machine Learning, Data Analysis, and Information Theory
Most Relevant Research Expertise
Mathematical Physics
Other Research Expertise (15)
Statistical Mechanics
Information Theory
Complex Systems
Statistical and Nonlinear Physics
Statistics and Probability
And 10 more
About
Dr. Dario Javier Zamora is a highly educated and experienced physicist. He received his Ph.D. in Physics from the National University of La Plata in 2020. Throughout his academic career, he has focused on conducting research in various areas of physics, including quantum mechanics, astrophysics, and statistical physics. After completing his doctoral studies, Dr. Zamora continued his research as a postdoctoral researcher at the Brazilian Centre for Physics Research. He then moved on to become a researcher at the University of Insubria in Italy, where he studied the properties of bacteria mobility and stochastic processes through simulations. Dr. Zamora has also held research positions at the National University of Tucuman and the National Scientific and Technical Research Council in Argentina. During this time, he worked on projects related to the dynamics of complex systems and the behavior of solar wind. In addition to his research work, Dr. Zamora has also been actively involved in teaching and mentoring students. He has served as a lecturer at the National University of La Plata, where he taught courses on statistical mechanics and information theory. He also worked as an Undergraduated Teaching Assistant at the National University of Tucuman, where he helped students with their coursework and lab experiments. He continues to be actively involved in research and teaching, and his work has been published in numerous prestigious scientific journals.
Most Relevant Publications (1+)

17 total publications

Classical Partition Function for Non-Relativistic Gravity

Axioms / Jun 16, 2021

Hameeda, M., Plastino, A., Rocca, M. C., & Zamora, J. (2021). Classical Partition Function for Non-Relativistic Gravity. Axioms, 10(2), 121. https://doi.org/10.3390/axioms10020121

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Dmitry Batenkov, Ph.D.

New York City, New York, United States of America
A highly experienced applied mathematician working in academia (faculty) and industry (consulting), with 15+ years of research and teaching expertise in inverse problems, signal processing, and data science.
Most Relevant Research Expertise
Mathematical Physics
Other Research Expertise (30)
Applied Harmonic Analysis
Sparse Representations
Numerical Analysis
Approximation Theory
Inverse Problems
And 25 more
About
I am passionate about solving big problems with scientific and computational tools. A highly experienced applied mathematician working in academia (faculty) and industry (consulting), with 15+ years of research and teaching expertise in inverse problems, signal processing, and data science. A highly-skilled software engineer and analyst/architect with 6+ years of experience as a technical lead in professional software development.
Most Relevant Publications (2+)

50 total publications

Moment inversion problem for piecewise D -finite functions

Inverse Problems / Sep 16, 2009

Batenkov, D. (2009). Moment inversion problem for piecewise D -finite functions. Inverse Problems, 25(10), 105001. https://doi.org/10.1088/0266-5611/25/10/105001

Stable soft extrapolation of entire functions

Inverse Problems / Dec 07, 2018

Batenkov, D., Demanet, L., & Mhaskar, H. N. (2018). Stable soft extrapolation of entire functions. Inverse Problems, 35(1), 015011. https://doi.org/10.1088/1361-6420/aaedde

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Example Mathematical Physics projects

How can companies collaborate more effectively with researchers, experts, and thought leaders to make progress on Mathematical Physics?

Algorithm Development for Financial Modeling

A Mathematical Physics expert can develop advanced algorithms for financial modeling, enabling companies to make accurate predictions and optimize investment strategies.

Optimization of Supply Chain Networks

By applying mathematical optimization techniques, a Mathematical Physics expert can help companies streamline their supply chain networks, reducing costs and improving efficiency.

Data Analysis for Drug Discovery

Mathematical Physics experts can analyze large datasets in the field of drug discovery, identifying patterns and optimizing drug design processes.

Simulation of Complex Systems

Using mathematical modeling and simulation, a Mathematical Physics expert can simulate and analyze complex systems, such as traffic flow or weather patterns, providing valuable insights for urban planning or risk assessment.

Optimization of Energy Systems

Mathematical Physics experts can optimize energy systems, such as power grids or renewable energy networks, maximizing efficiency and reducing environmental impact.