Home
How It Works
Solutions
Resources
Events
Blog
Case Studies
For Academic Experts
Sign Up
Login

Work with thought leaders and academic experts in analysis

Companies can benefit from working with an academic researcher in Analysis in several ways. These experts can provide valuable insights and recommendations based on data analysis, helping companies make informed decisions. They can also assist in developing and implementing analytical models and algorithms to optimize business processes. Additionally, academic researchers can conduct in-depth research and analysis to identify trends, patterns, and opportunities in the market. Their expertise can be leveraged to improve forecasting accuracy, identify risks, and develop strategies for growth. Collaborating with an Analysis researcher can enhance a company's analytical capabilities, drive innovation, and stay ahead of the competition.

Researchers on NotedSource with backgrounds in analysis include Tim Osswald, john kerry, Dario Javier Zamora, Edoardo Airoldi, Dmitry Batenkov, Ph.D., and Wesley R. Hartmann.

Tim Osswald

Polymers Professor - University of Wisconsin
Most Relevant Research Interests
Analysis
Other Research Interests (44)
Polymer Engineering
Advanced Manufacturing
Composites
Additive Manufacturing
Materials Chemistry
And 39 more
About
T. Osswald is Hoeganaes Professor of Materials at the University of Wisconsin-Madison, where he has been a faculty member since 1989. Osswald received the PhD in Mechanical Engineering from the University of Illinois at Urbana-Champaign in 1987, the MS in Mechanical Engineering from the South Dakota School of Mines and Technology in 1982, and the BS in Mechanical Engineering from the South Dakota School of Mines and Technology in 1981. Before joining the UW-Madison faculty, Osswald was a Humboldt Fellow at the Rheinisch Westfalische Technische Hochschule Aachen. Osswald’s research interests are in the areas of processing-structure-property relationships for metals and composites, with a focus on powder metallurgy and metal injection molding. His research has been supported by the National Science Foundation, the Department of Energy, the US Army Research Office, and industry. Osswald is a Fellow of ASM International and the American Academy of Mechanics, and he has received the Extrusion Division Award, the Powder Metallurgy Division Award, and the Distinguished Teaching Award from TMS.
Most Relevant Publications (1+)

117 total publications

Analysis of fiber damage mechanisms during processing of reinforced polymer melts

Engineering Analysis with Boundary Elements / Jul 01, 2002

Hernandez, J. P., Raush, T., Rios, A., Strauss, S., & Osswald, T. A. (2002). Analysis of fiber damage mechanisms during processing of reinforced polymer melts. Engineering Analysis with Boundary Elements, 26(7), 621–628. https://doi.org/10.1016/s0955-7997(02)00018-8

See Full Profile

john kerry

Food Consultant PhD in Food Science & Technology
Most Relevant Research Interests
Analysis
Other Research Interests (10)
Food Process Technology
Value Added RTE meat and Convenience Foods
Food Safety
Product R&D
Food Science
And 5 more
About
A Food professional with > 20 years of experience within the meat and value added food sectors, Internationally. Considerable know how in food process (turn key lines: equipment development/selection, installation and commissioning/optimization) and product development (use of novel ingredients, least cost formulation, product quality enhancement initiatives as related to formulation and equipment/process selection). An excellent communicator and project manger with an ability to disseminate information in a clear and concise manner.
Most Relevant Publications (1+)

43 total publications

Optical fibre sensors for assessing food quality in full scale production ovens — a principal component analysis and artificial neural network based approach

Nonlinear Analysis: Hybrid Systems / Mar 01, 2008

Lewis, E., Sheridan, C., O’Farrell, M., Flanagan, C., Kerry, J. F., & Jackman, N. (2008). Optical fibre sensors for assessing food quality in full scale production ovens — a principal component analysis and artificial neural network based approach. Nonlinear Analysis: Hybrid Systems, 2(1), 51–57. https://doi.org/10.1016/j.nahs.2006.05.008

See Full Profile

Dario Javier Zamora

Ph.D. in physics with expertise in Statistical Physics, Complex Systems, Machine Learning, Data Analysis, and Information Theory
Most Relevant Research Interests
Analysis
Other Research Interests (15)
Statistical Mechanics
Information Theory
Complex Systems
Mathematical Physics
Statistical and Nonlinear Physics
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

See Full Profile

Edoardo Airoldi

Professor of Statistics & Data Science Temple University & PI, Harvard University
Most Relevant Research Interests
Analysis
Other Research Interests (43)
Statistics
Causal Inference
Network Science
Cell Biology
Molecular Biology
And 38 more
About
Edoardo Airoldi is a Professor in the Department of Machine Learning at Temple University. He is also the Director of the Center for Machine Learning and Health. He is a world-renowned expert in the fields of machine learning and artificial intelligence, with a focus on applications to health. Airoldi is a member of the prestigious Association for the Advancement of Artificial Intelligence (AAAI) and the International Machine Learning Society (IMLS). He has published over 200 papers in leading journals and conferences, and his work has been covered by various media outlets including The New York Times, The Wall Street Journal, The Economist, and Wired.
Most Relevant Publications (1+)

106 total publications

Confidence sets for network structure

Statistical Analysis and Data Mining / Sep 09, 2011

Airoldi, E. M., Choi, D. S., & Wolfe, P. J. (2011). Confidence sets for network structure. Statistical Analysis and Data Mining, 4(5), 461–469. https://doi.org/10.1002/sam.10136

See Full Profile

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 Interests
Analysis
Other Research Interests (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 (6+)

51 total publications

Super-resolution of near-colliding point sources

Information and Inference: A Journal of the IMA / May 11, 2020

Batenkov, D., Goldman, G., & Yomdin, Y. (2020). Super-resolution of near-colliding point sources. Information and Inference: A Journal of the IMA, 10(2), 515–572. https://doi.org/10.1093/imaiai/iaaa005

Conditioning of Partial Nonuniform Fourier Matrices with Clustered Nodes

SIAM Journal on Matrix Analysis and Applications / Jan 01, 2020

Batenkov, D., Demanet, L., Goldman, G., & Yomdin, Y. (2020). Conditioning of Partial Nonuniform Fourier Matrices with Clustered Nodes. SIAM Journal on Matrix Analysis and Applications, 41(1), 199–220. https://doi.org/10.1137/18m1212197

Accuracy of Algebraic Fourier Reconstruction for Shifts of Several Signals

Sampling Theory in Signal and Image Processing / May 01, 2014

Batenkov, D., Sarig, N., & Yomdin, Y. (2014). Accuracy of Algebraic Fourier Reconstruction for Shifts of Several Signals. Sampling Theory in Signal and Image Processing, 13(2), 151–173. https://doi.org/10.1007/bf03549577

Accuracy of Algebraic Fourier Reconstruction for Shifts of Several Signals

Sampling Theory in Signal and Image Processing / May 01, 2014

Batenkov, D., Sarig, N., & Yomdin, Y. (2014). Accuracy of Algebraic Fourier Reconstruction for Shifts of Several Signals. Sampling Theory in Signal and Image Processing, 13(2), 151–173. https://doi.org/10.1007/bf03549577

Uniform upper bounds for the cyclicity of the zero solution of the Abel differential equation

Journal of Differential Equations / Dec 01, 2015

Batenkov, D., & Binyamini, G. (2015). Uniform upper bounds for the cyclicity of the zero solution of the Abel differential equation. Journal of Differential Equations, 259(11), 5769–5781. https://doi.org/10.1016/j.jde.2015.07.009

Sampling, Metric Entropy, and Dimensionality Reduction

SIAM Journal on Mathematical Analysis / Jan 01, 2015

Batenkov, D., Friedland, O., & Yomdin, Y. (2015). Sampling, Metric Entropy, and Dimensionality Reduction. SIAM Journal on Mathematical Analysis, 47(1), 786–796. https://doi.org/10.1137/130944436

See Full Profile

Wesley R. Hartmann

The John G. McCoy-Banc One Corporation Professor of Marketing
Most Relevant Research Interests
Analysis
Other Research Interests (11)
Marketing
Economics and Econometrics
Business and International Management
Management Science and Operations Research
Strategy and Management
And 6 more
About
Wesley R. Hartmann is a Professor at the Graduate School of Business at Stanford University. He received his PhD in Economics from the University of California, Los Angeles in 2003, and his MA in Economics from the University of California, Los Angeles in 2001. He also holds a BA in Economics and Political Science from the University of California, Irvine.
Most Relevant Publications (1+)

26 total publications

Dynamics of polynomials with disconnected Julia sets

Discrete & Continuous Dynamical Systems - A / Jan 01, 2003

D. Emerson, N. (2003). Dynamics of polynomials with disconnected Julia sets. Discrete & Continuous Dynamical Systems - A, 9(4), 801–834. https://doi.org/10.3934/dcds.2003.9.801

See Full Profile

Example analysis projects

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

Market Analysis for a Retail Company

An Analysis researcher can conduct a comprehensive market analysis for a retail company, including customer segmentation, competitor analysis, and trend identification. This analysis can help the company understand its target market, identify new opportunities, and develop effective marketing strategies.

Financial Data Analysis for a Banking Institution

An Analysis researcher can analyze financial data for a banking institution, identifying patterns and trends in customer behavior, loan repayment, and risk assessment. This analysis can help the institution make data-driven decisions, improve risk management, and optimize financial processes.

Supply Chain Optimization for a Manufacturing Company

An Analysis researcher can optimize the supply chain of a manufacturing company by analyzing data related to inventory management, production processes, and logistics. This analysis can help the company reduce costs, improve efficiency, and enhance customer satisfaction.

Data-driven Decision Making for a Healthcare Organization

An Analysis researcher can assist a healthcare organization in making data-driven decisions by analyzing patient data, treatment outcomes, and resource allocation. This analysis can help the organization improve patient care, optimize resource utilization, and enhance operational efficiency.

Predictive Analytics for an E-commerce Company

An Analysis researcher can develop predictive analytics models for an e-commerce company, analyzing customer behavior, purchase patterns, and market trends. This analysis can help the company personalize marketing campaigns, optimize pricing strategies, and improve customer retention.