Work with thought leaders and academic experts in numerical analysis
Companies can benefit from working with Numerical Analysis experts in several ways. These researchers can help optimize processes, solve complex problems, and improve decision-making through mathematical modeling, algorithm development, and data analysis. They can also assist in developing and implementing numerical methods and algorithms for various applications, such as optimization, simulation, and machine learning. Additionally, their expertise can be valuable in areas like risk assessment, financial modeling, and predictive analytics. Collaborating with these experts can lead to improved efficiency, cost savings, and competitive advantage.
Experts on NotedSource with backgrounds in numerical analysis include Tim Leung, David Blanchett, Dr. Abdussalam Elhanashi, Asst. Prof. Eng. Davide Verzotto, Ph.D., and Enrico Capobianco.
Tim Leung
Professor of Applied Mathematics, Computational Finance & Risk Management (CFRM) Program
Most Relevant Research Interests
Other Research Interests (29)
About
Most Relevant Publications (2+)
138 total publications
ESO Valuation with Job Termination Risk and Jumps in Stock Price
SIAM Journal on Financial Mathematics / Jan 01, 2015
Leung, T., & Wan, H. (2015). ESO Valuation with Job Termination Risk and Jumps in Stock Price. SIAM Journal on Financial Mathematics, 6(1), 487–516. https://doi.org/10.1137/130937949
Optimal Timing to Purchase Options
SIAM Journal on Financial Mathematics / Jan 01, 2011
Leung, T., & Ludkovski, M. (2011). Optimal Timing to Purchase Options. SIAM Journal on Financial Mathematics, 2(1), 768–793. https://doi.org/10.1137/100809386
David Blanchett
Current Director - PGIM (Formerly Prudential Investment Management); Adjunct Professor of Finance
Most Relevant Research Interests
Other Research Interests (17)
About
Most Relevant Publications (1+)
83 total publications
Optimal Initiation of Guaranteed Lifelong Withdrawal Benefit with Dynamic Withdrawals
SIAM Journal on Financial Mathematics / Jan 01, 2017
Huang, Y. T., Zeng, P., & Kwok, Y. K. (2017). Optimal Initiation of Guaranteed Lifelong Withdrawal Benefit with Dynamic Withdrawals. SIAM Journal on Financial Mathematics, 8(1), 804–840. https://doi.org/10.1137/16m1089575
Dr. Abdussalam Elhanashi
Researcher at University of Pisa
Most Relevant Research Interests
Other Research Interests (23)
About
Most Relevant Publications (1+)
28 total publications
An IoT System for Social Distancing and Emergency Management in Smart Cities Using Multi-Sensor Data
Algorithms / Oct 07, 2020
Fedele, R., & Merenda, M. (2020). An IoT System for Social Distancing and Emergency Management in Smart Cities Using Multi-Sensor Data. Algorithms, 13(10), 254. https://doi.org/10.3390/a13100254
Asst. Prof. Eng. Davide Verzotto, Ph.D.
Assistant Professor of Computer Science, Centre for Higher Defence Studies (CASD) - School of Advanced Studies, Italian Defence General Staff, Rome
Most Relevant Research Interests
Other Research Interests (20)
About
Most Relevant Publications (2+)
40 total publications
Editorial: Special Issue on Algorithms for Sequence Analysis and Storage
Algorithms / Mar 25, 2014
Mäkinen, V. (2014). Editorial: Special Issue on Algorithms for Sequence Analysis and Storage. Algorithms, 7(1), 186–187. https://doi.org/10.3390/a7010186
Filtering Degenerate Patterns with Application to Protein Sequence Analysis
Algorithms / May 22, 2013
Comin, M., & Verzotto, D. (2013). Filtering Degenerate Patterns with Application to Protein Sequence Analysis. Algorithms, 6(2), 352–370. https://doi.org/10.3390/a6020352
Enrico Capobianco
The Jackson Laboratory, USA
Most Relevant Research Interests
Other Research Interests (40)
About
Most Relevant Publications (1+)
96 total publications
Entropy embedding and fluctuation analysis in genomic manifolds
Communications in Nonlinear Science and Numerical Simulation / Jun 01, 2009
Capobianco, E. (2009). Entropy embedding and fluctuation analysis in genomic manifolds. Communications in Nonlinear Science and Numerical Simulation, 14(6), 2602–2618. https://doi.org/10.1016/j.cnsns.2008.09.015
Example numerical analysis projects
How can companies collaborate more effectively with researchers, experts, and thought leaders to make progress on numerical analysis?
Optimizing Supply Chain Operations
A Numerical Analysis expert can develop mathematical models and algorithms to optimize supply chain operations, considering factors like demand forecasting, inventory management, and transportation logistics. This can lead to improved efficiency, reduced costs, and better customer satisfaction.
Improving Drug Formulation
Collaborating with a Numerical Analysis researcher can help pharmaceutical companies optimize drug formulation processes. By using mathematical modeling and simulation techniques, they can identify the optimal combination of ingredients, dosage, and delivery methods, leading to improved drug efficacy and reduced development time.
Enhancing Energy Efficiency
Numerical Analysis experts can assist energy companies in optimizing energy production and consumption processes. By developing mathematical models and algorithms, they can identify energy-saving opportunities, optimize resource allocation, and improve overall energy efficiency.
Predictive Maintenance in Manufacturing
Working with a Numerical Analysis researcher, manufacturing companies can develop predictive maintenance models. By analyzing historical data and using machine learning algorithms, they can predict equipment failures, schedule maintenance activities, and minimize downtime, resulting in cost savings and improved productivity.
Risk Assessment in Finance
Collaborating with a Numerical Analysis expert can help financial institutions assess and manage risks. By developing mathematical models and algorithms, they can analyze market trends, evaluate investment portfolios, and quantify risk exposures, enabling informed decision-making and risk mitigation strategies.