Work with thought leaders and academic experts in Statistical and Nonlinear Physics

Companies can greatly benefit from working with experts in Statistical and Nonlinear Physics. These researchers have a deep understanding of complex systems, data analysis, modeling, and prediction. By collaborating with them, companies can enhance their data-driven decision-making processes, optimize their operations, and gain a competitive edge. Statistical and Nonlinear Physics experts can help companies in various industries, such as finance, healthcare, energy, transportation, and manufacturing, by providing insights into complex phenomena, developing advanced algorithms, and improving predictive models. Their expertise can also be valuable in risk assessment, anomaly detection, optimization of processes, and understanding market dynamics. Partnering with these experts can lead to innovative solutions, improved efficiency, and better strategic planning.

Researchers on NotedSource with backgrounds in Statistical and Nonlinear Physics include N. S. Vidhyadhiraja, Michael Sebek, Dario Javier Zamora, Anirudha Menon, Parvin Bayati, Baidurya Bhattacharya, Ehsan Barati, PhD, Denys Dutykh, AHMAD SALMANOGLI, Enrico Capobianco, Shiang-Yi Han (韓相宜）, Ph.D., and Moji Ghadimi.

N. S. Vidhyadhiraja

Bengaluru
23 Years Experience
Professor of theoretical and computational condensed matter physics, Theoretical Sciences Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore, India
Education

Indian Institute of Science Bangalore

Ph.D., Theoretical Condensed Matter Physics / February, 2001

Bengaluru

Indian Institute of Technology Kanpur

Integrated M.Sc, Physics / May, 1995

Kanpur
Experience

University of Oxford, UK

Postdoctoral fellow / February, 2001 — February, 2005

EPSRC funded Postdoctoral research fellow at the Physical and theoretial Chemistry Laboratory, University of Oxford, under the supervision of Prof. David E. Logan

Jawaharlal Nehru Centre for Advanced Scientific Research, Bengaluru, India

Fellow, Theoretical Sciences Unit / March, 2005 — March, 2007

Temporary faculty member (similar to Tenure track)

Faculty Fellow, Theoretical Sciences Unit (Similar to Assistant professor) / March, 2007 — March, 2013

Regular faculty member position with responsibilities of guiding Ph.D. students, carrying out research, teaching, and administrative duties

Associate Professor / March, 2013 — March, 2019

Regular faculty member position with responsibilities of guiding Ph.D. students, carrying out research, teaching, and administrative duties

Professor / March, 2019 — Present

Highest academic position within the organization, Regular faculty member position with responsibilities of guiding Ph.D. students, carrying out research, teaching, and administrative duties

University of Cincinnati, USA

Visiting professor / May, 2008 — July, 2008

Visiting professor at the Physics department, carrying out research collaboration with the group of (late) Prof. Mark Jarrell

Most Relevant Research Expertise
Statistical and Nonlinear Physics
Other Research Expertise (8)
Condensed matter physics
quantum transport
quantum many body theory
strongly correlated electronic systems
Kondo physics
And 3 more
About
N. S. Vidhyadhiraja is a physicist with expertise in theoretical and computational condensed matter physics. He completed his Ph.D. in 2001 from Indian Institute of Science Bangalore and has since held various positions in prestigious institutions such as University of Oxford, Jawaharlal Nehru Centre for Advanced Scientific Research, and Purdue University. He has also been a visiting professor at universities in the USA. He has [published numerous papers in international journals ](https://scholar.google.com/citations?hl=en&user=udcA51cAAAAJ)and has made significant contributions to the field of condensed matter physics. His research interests include the study of strongly correlated electronic systems and phenomena using the methods of quantum many body theory. He is currently a [professor at Jawaharlal Nehru Centre for Advanced Scientific Research, Bengaluru, India.](https://www.jncasr.ac.in/faculty/raja)

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Michael Sebek

Boston, Massachusetts, United States of America
14 Years Experience
Northeastern University
Education

Truman State University

Bachelor of Science, Chemistry / May, 2012

Kirksville, Missouri, United States of America

Saint Louis University

Master of Science, Chemistry / May, 2014

St Louis, Missouri, United States of America

Saint Louis University

Ph.D., Chemistry / December, 2017

St Louis, Missouri, United States of America
Experience

Truman State University

Undergraduate Researcher / August, 2010 — May, 2012

Constructed a procedure to apply sol-gel thin films to fiber optic cables, Performed Scanning Electron Microscopy to assess the quality of the coating | Skills: Sol-Gel Preparation, UV-Vis Spectroscopy, Scanning Electron Microscopy

Saint Louis University

Graduate Teaching Assistant / August, 2012 — May, 2017

Prepared and taught labs for Analytical Chemistry I, Physical Chemistry II, General Chemistry I and II

Saint Louis University

Graduate Researcher / July, 2012 — December, 2017

 Created a method to construct and apply networks to units of electrochemical reactions  Explored the impact of network topology and unit heterogeneity on network behavior  Built code in LabVIEW, MATLAB, and R to collect and analyze data as well as to simulate the experiments  Designed community outreach demonstration experiments for the research | Skills: Potentiometry, Anode-Cathode Systems, Electrochemical Cells, LabVIEW, MATLAB, R, TeXworks, 3D printing, Autodesk Eagle, AutoCAD

Most Relevant Research Expertise
Statistical and Nonlinear Physics
Other Research Expertise (7)
network science
food science
electrochemistry
nonlinear dynamics
Mathematical Physics
And 2 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.

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Dario Javier Zamora

11 Years Experience
Ph.D. in physics with expertise in Statistical Physics, Complex Systems, Machine Learning, Data Analysis, and Information Theory
Education

National University of La Plata

Ph.D., Physics / August, 2020

La Plata
Experience

University of Insubria

Researcher / June, 2023 — Present

Brazilian Centre for Physics Research

Researcher / February, 2021 — January, 2022

National University of Tucuman and National Scientific and Technical Research Council

Researcher / March, 2022 — May, 2023

Most Relevant Research Expertise
Statistical and Nonlinear Physics
Other Research Expertise (16)
Statistical Mechanics
Information Theory
Complex Systems
Mathematical Physics
Statistical and Nonlinear Physics
And 11 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.

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Anirudha Menon

3 Years Experience
PhD in theoretical condensed matter physics with a focus on quantum magnetism.
Education

University of California Davis

PhD, Physics / June, 2021

Davis, California, United States of America

University of Illinois at Chicago

M.S., Physics / May, 2015

Chicago
Experience

Indian Association for the Cultivation of Science

National Postdoctoral Fellow / January, 2023 — December, 2024

RA-I / October, 2022 — December, 2022

Indian Statistical Institute

Researcher / January, 2022 — September, 2022

Freie Universität Berlin

Postdoctoral Researcher / September, 2021 — January, 2022

Most Relevant Research Expertise
Statistical and Nonlinear Physics
Other Research Expertise (13)
Quantum Computing
Topological Quantum Matter
Emergent Phenomena
Data Science
Machine Learning
And 8 more
About
I am a lecturer at the University of California, Davis, teaching undergraduate students in physics and engineering basic and advanced physics. I also collaborate with several experimental and theory groups in condensed matter physics all over the globe focussing on critical phenomena, quantum magnetism, topological materials, transport properties, and driven quantum systems. My current interests lie in Hilbert Space fragmentation and associated critical phenomena for systems with subsystem symmetries. Additionally, I use the numerical linked cluster expansion to study heavy fermion compounds of interests to groups in John's Hopkins and Princeton Universities.

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Parvin Bayati

6 Years Experience
Assistant Research Professor, Penn State University
Education

Ph.D, physics / February, 2017

Zanjan
Experience

Pennsylvania State University

Postdoc reseacher / January, 2022 — Present

Université Paris-Sud

Postdoc / November, 2018 — Present

Institute for Advanced Studies in Basic Sciences

Postdoc researcher / August, 2018 — Present

Most Relevant Research Expertise
Statistical and Nonlinear Physics
Other Research Expertise (11)
Active Matter
Soft matter
Microswimmers
Fluid Dynamics
Microfluidic
And 6 more
About
Parvin Bayati is a highly accomplished physicist with a Ph.D in physics from None in 2017. She has extensive experience in conducting research and has worked as a Postdoc researcher at prestigious institutions such as Pennsylvania State University, Université Paris-Sud, and Institute for Advanced Studies in Basic Sciences. Her research focuses on theoretical and computational physics, with a particular interest in quantum mechanics and condensed matter physics. Parvin has published numerous papers in reputable scientific journals and has presented her work at international conferences. She is also a dedicated mentor, having supervised several undergraduate and graduate students in their research projects. With her strong academic background and expertise in physics, Parvin continues to make significant contributions to the field of physics.

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Baidurya Bhattacharya

23 Years Experience
Computational mechanics, probabilistic risk analysis, statistical inference, Monte Carlo simulations
Education

Johns Hopkins University

PhD, Civil Engineering / January, 1997

Baltimore, Maryland, United States of America

Indian Institute of Technology Kharagpur

B.Tech (hons.), Civil Engineering / April, 1991

Kharagpur
Experience

University of Delaware

Visiting Professor / September, 2022 — Present

Assistant Professor / August, 2001 — February, 2006

Indian Institute of Technology Kharagpur

Professor / February, 2006 — Present

Most Relevant Research Expertise
Statistical and Nonlinear Physics
Other Research Expertise (44)
computational materials science
probabilistic mechanics
Mechanical Engineering
Industrial and Manufacturing Engineering
Mechanics of Materials
And 39 more
About
Baidurya Bhattacharya is a highly accomplished and respected civil engineer with over 20 years of experience in the field. He was born in Kolkata, India and completed his B.Tech (hons.) in Civil Engineering from the prestigious Indian Institute of Technology Kharagpur in 1991. He then went on to pursue his PhD in Civil Engineering from Johns Hopkins University, which he completed in 1997. After completing his PhD, Bhattacharya started his academic career as a Visiting Professor at the University of Delaware. He then moved on to become an Assistant Professor at the same university, where he taught for several years and mentored numerous students. In 2005, he returned to his alma mater, Indian Institute of Technology Kharagpur, as a Professor in the Department of Civil Engineering. He has been a valuable member of the faculty and has made significant contributions to the department through his research and teaching. Bhattacharya's research interests lie in the areas of structural engineering, earthquake engineering, and soil dynamics. He has published numerous papers in reputable journals and has also presented his work at various international conferences. His research has been recognized and funded by prestigious organizations such as the National Science Foundation and the American Society of Civil Engineers. Aside from his academic career, Bhattacharya is also actively involved in consulting and has worked on various projects in collaboration with government agencies and private firms. He is known for his expertise and has received several awards and honors for his contributions to the field of civil engineering. Bhattacharya is a dedicated educator and mentor, and he continues to inspire and guide young engineers through his teaching and research. His passion for the field and his dedication to his students make him a highly respected figure in the academic community.

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Ehsan Barati, PhD

10 Years Experience
Theoretical/computational Physicist/chemist/material scientist
Education

Polish Academy of Sciences

Ph.D., Physics (Physical Chemistry) / December, 2014

Warsaw

University of Tabriz

Masters, Physics / September, 2009

Tabriz

Bu-Ali Sina University

Bachelor, Physics / July, 2006

Hamadan
Experience

Polish Academy of Sciences

Computational Physicist / January, 2014 — Present

Condensed Matter Physics

Dutch Research Council

Computational Material Scientist / April, 2016 — April, 2018

Ab-initio (first principles) calculations, spintronics

Brown University

Computational Quantum Chemist / March, 2020 — March, 2022

Implemented, benchmarked and developed Quantum Monte-Carlo simulations for materials, significantly improved the algorithms.

Most Relevant Research Expertise
Statistical and Nonlinear Physics
Other Research Expertise (9)
Condensed Matter Physics
Computational Material Science
Quantum Computing
Computational Chemistry
Electronic, Optical and Magnetic Materials
And 4 more
About
Empowering innovation through 10+ years of dedicated expertise in Computational Research Science, I specialize in leveraging statistical techniques, mathematical modeling, and high-performance computing (HPC) to solve complex challenges across diverse domains. My expertise spans critical areas such as Theoretical/Computational Quantum Condensed Matter Physics, Computational Chemistry, Computational Material Science, Quantum Computing, and Data Analysis. With a proven track record in deploying advanced methodologies, including quantum teleportation (qubit transfer in spin networks), Quantum Monte Carlo Simulations, First-principles (ab-initio) calculations, and cutting-edge algorithms, I bring a robust foundation in both classical and quantum realms. I thrive on translating complex data into actionable insights, utilizing a spectrum of Machine Learning techniques—from supervised to unsupervised and reinforcement learning, encompassing Regression, Classification, Neural Networks, TensorFlow, and Recommender Systems.

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Denys Dutykh

16 Years Experience
Professional Applied Mathematician, Modeller, and Advisor
Education

École Normale Supérieure Paris-Saclay

PhD, Centre de Mathématiques et de Leurs Applications / December, 2007

Cachan
Experience

Centre National de la Recherche Scientifique

Research scientist / October, 2008 — August, 2022

Professional scientific research in the field of Applied Mathematics

Khalifa University of Science and Technology

Associate Professor / August, 2022 — Present

Professional research and educational activities in the field of Applied Mathematics

Most Relevant Research Expertise
Statistical and Nonlinear Physics
Other Research Expertise (51)
Applied mathematics
fluid mechanics
scientific computing
numerical methods
Fluid Flow and Transfer Processes
And 46 more
About
Dr. Denys Dutykh initially comes from the broad field of Applied Mathematics. He did his Master's degree in numerical methods applied to the problems of Continuum Mechanics and a Ph.D. thesis at Ecole Normale Supérieure de Cachan (France) on the mathematical modeling of tsunami waves. After this, he was hired as a permanent research scientist at the Institute of Mathematics (INSMI) at the Centre National de la Recherche Scientifique (CNRS). His research activities have been conducted in the following years at the picturesque University Savoie Mont Blanc (USMB, France) in the field of mathematical methods applied to the modeling and simulation of nonlinear waves (mostly in Fluid Dynamics). The Habilitation thesis of Dr. Dutykh was defended there on the topic of the mathematical methods in the environment. Since then, his research interests have significantly broadened to include the Dimensionality Reduction methods in Machine Learning, modeling of PV panels, and even some more theoretical questions in the Number Theory.

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AHMAD SALMANOGLI

10 Years Experience
Quantum RF Circuit engineer at Ankara Yildirim Beyazit University
Education

University of Tabriz

Msc, Electrical and computer engineering / August, 2007

Tabriz

Hacettepe University

Electrical engineering / June, 2021

Ankara
Experience

Hacettepe Üniversitesi

October, 2014 — July, 2016

Most Relevant Research Expertise
Statistical and Nonlinear Physics
Other Research Expertise (28)
Quantum RF circuit design
Oncology
Physical and Theoretical Chemistry
Pharmaceutical Science
Biomedical Engineering
And 23 more
About
I'm a quantum electronics engineer, and interested in: Quantum circuits and Quantum RF circuits design for quantum computing and quantum sensory applications cQED Quantum Radar Cryogenic RF/MW circuits design for quantum applications: Cryo-CMOS for the design of qubits readout and control circuit Design of transducer for generation of entangled photon ADS (Advanced Design System) and Cadence for RF/MW circuits schematic and layout design and modeling Writing code in Matlab and Python Simulation of physical phenomena in COMSOL Multiphysics

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Enrico Capobianco

25 Years Experience
Expertise in network science and special interest in cancer domain. Scientific Leader, Advisor. Quant, Computational & Digital Biomedical & Health research.
Education

Stanford University

Post-doctoral Fellowship, AI, Machine & Statistical Learning, Neural Networks / 1998

Stanford, California, United States of America

University of Padua

PhD, Statistical Sciences / 1995

Padova
Experience

The Jackson Laboratory

Associate Director, Computational Systems / 2018 — 2024

Most Relevant Research Expertise
Statistical and Nonlinear Physics
Other Research Expertise (35)
Networks
Machine Learning
Big Data
Systems Biology & Medicine
Statistics
And 30 more
About
Enrico Capobianco is a highly experienced and accomplished expert in the fields of artificial intelligence, machine learning, and statistical learning. He holds a Post-doctoral Fellowship in AI, Machine & Statistical Learning, Neural Networks from Stanford University, which he completed in 1998. Prior to that, he received his PhD in Statistical Sciences from the University of Padua in 1995. With over 25 years of experience, Capobianco has held various positions in academia, research, and industry. Most recently, he served as the Associate Director of Computational Systems at The Jackson Laboratory, a leading non-profit research institute focused on genetics and genomics. In this role, he oversaw the development and implementation of computational systems and tools for genetic and genomic research. Throughout his career, Capobianco has published numerous articles and book chapters on topics such as machine learning, artificial intelligence, and computational biology. He has also been a keynote speaker at various international conferences and has received numerous awards and grants for his research. In addition to his professional achievements, Capobianco is known for his collaborative and innovative approach to problem-solving. He is constantly seeking new ways to apply advanced computational techniques to solve complex problems in various industries, from healthcare to finance. Overall, Enrico Capobianco is a highly respected and sought-after expert in the fields of AI, machine learning, and statistical learning. His education and experience have equipped him with the knowledge and skills to make significant contributions to the advancement of these fields.

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Shiang-Yi Han (韓相宜）, Ph.D.

15 Years Experience
Research Fellow at National Cheng Kung University
Education

National Cheng Kung University

Ph.D., Astronautics and Aeronautics / June, 2010

Tainan City
Experience

National Cheng Kung University

Postdoctoral Research Fellow / October, 2010 — February, 2011

Department of Physics

National Kaohsiung Normal University

Postdoctoral Research Fellow / March, 2011 — July, 2012

Department of Physics

Naval Academic

Lecturer / August, 2009 — July, 2010

Department of Applied Science

Most Relevant Research Expertise
Statistical and Nonlinear Physics
Other Research Expertise (23)
foundation of quantum mechanics
relativistic particle
space technology
quantum technology
Mechanics of Materials
And 18 more
About
Shiang-Yi Han received her Ph.D. in Astronautics and Aeronautics from National Cheng Kung University in 2010. During her studies, she specialized in the field of quantum mechanics and conducted research on quantum control for applications. After completing her Ph.D., she worked as a Postdoctoral Research Fellow in the department of physics at both National Cheng Kung University and National Kaohsiung Normal University. In 2011, Dr. Han joined the faculty at Naval Academic as a Lecturer, where she taught courses on space systems and modern physics. She also worked as an IT Engineer at Hundreds Company, where she gained valuable experience in software and hardware development. In 2013, Dr. Han began her career in academia, serving as an Adjunct Assistant Professor at both National University of Kaohsiung and Naval Academic. She taught courses on space exploration, flight dynamics, and control theory. In 2023, Dr. Han transitioned to the industry, taking on the role of Deputy Project Manager at Taiwan Innovative Space, a company focused on developing space launch system. In this position, she was involved in the design, development, and testing of orbit insertion rocket. Dr. Han's research interests include rocket optimal design, space systems, and quantum systems. She has published several papers in prestigious international journals and has presented her research at numerous conferences. She is also a member of Sigma Xi. In addition to her academic and industry work, Dr. Han is also dedicated to promoting space and physics education and outreach. She has organized and participated in various events and workshops aimed at inspiring young students to pursue careers in the space industry. Overall, Dr. Han is a highly accomplished and experienced professional in the field of astronautics and aeronautics and also physics. Her expertise, passion, and dedication make her a valuable asset to any organization or institution.

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Moji Ghadimi

15 Years Experience
Senior Research Fellow, University of Queensland
Education

Griffith University

PhD, Quantum Physics / January, 2017

Brisbane, Queensland, Australia
Experience

The University of Queensland

Research Flllow level B / September, 2021 — Present

I manage a team of research assistants and PhD students who work on machine learning (in collaboration with Queensland Digital Health Centre, AU and Oxford University, UK) and quantum computing projects (in partnership with EQUS Research Centre, AU). I have published the results in world-leading level journals. - Improving quantum sensors using machine learning. - Improving training methods for quantum neural networks. - Improving the accuracy of training methods for neural networks (CNNs, LLMs) in collaboration with Griffith University, AU. - Machine Learning for detection of Kidney injury in hospitals in collaboration with Queensland Digital Health Centre. - Analysis of the ISARIC/Oxford international dataset, the largest COVID dataset in the world.

Griffith University

Research Fellow / December, 2018 — September, 2021

- Supervised stabilising quantum computers using machine learning. - Supervised the project “The Internet of the future: towards an intercontinental quantum network,” funded $870,000 to implement quantum security protocols over 60 km of optical fibre.

Ash food company

IT and Data Analytics Manager / September, 2009 — November, 2012

- Managed the IT unit of the Ash food production company, supervised 5 engineers and 15 technicians in the branches across the country and managed a total annual budget of $500,000. - Performed sales analytics with Excel and SQL Server. - I did web programming with PHP and MySQL. - I received a letter of appreciation for transforming the unit.

Most Relevant Research Expertise
Statistical and Nonlinear Physics
Other Research Expertise (17)
Quantum Foundations
Experimental Quantum Physics
Computational Physics
Machine Learning
Statistical and Nonlinear Physics
And 12 more
About
My passion is to thoroughly understand complex systems to the level that I can explain them to anyone and use that deep understanding to improve them. I have experience in a wide variety of fields in industry and academia (Quantum Computing, AI, IT Management, etc.). With my interdisciplinary knowledge and experience, I have been able to transform the workplaces I worked in so that they continued to perform better even after I left the job. As one example, I can mention my previous job at Griffith University, where I used AI, optimization, and automation to improve the functionality of the quantum computer that my team worked on. Outside work, I spend time with my family, play soccer, or go hiking.

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Example Statistical and Nonlinear Physics projects

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

Financial Market Analysis

A Statistical and Nonlinear Physics expert can analyze financial market data to identify patterns, trends, and correlations. This analysis can help companies make informed investment decisions, predict market movements, and manage risks effectively.

Healthcare Data Analysis

By applying Statistical and Nonlinear Physics techniques to healthcare data, experts can uncover hidden patterns, identify disease risk factors, and develop personalized treatment plans. This can lead to improved patient outcomes, cost savings, and more efficient healthcare delivery.

Energy Optimization

Collaborating with a Statistical and Nonlinear Physics researcher can help companies optimize energy consumption, reduce waste, and improve energy efficiency. By analyzing complex energy systems, experts can identify areas for improvement and develop strategies to minimize environmental impact.

Transportation Modeling

Statistical and Nonlinear Physics experts can develop sophisticated models to optimize transportation networks, improve traffic flow, and reduce congestion. This can lead to cost savings, reduced travel times, and improved overall transportation efficiency.

Manufacturing Process Optimization

By applying Statistical and Nonlinear Physics techniques to manufacturing processes, experts can identify bottlenecks, optimize production schedules, and improve quality control. This can result in increased productivity, reduced costs, and improved product quality.