Title: Founding Partner
Company: Calico Science Consulting LLC
Location: Austin, Texas, United States
Sergei Levendorskii, PhD, Founding Partner at Calico Science Consulting LLC, has been recognized by Marquis Who’s Who Top Scientists for dedication, achievements, and leadership in developing new efficient methods for pricing derivative securities.
After more than 30 years in academia and doing research in various fields of mathematics, mathematical physics, economics and quantitative finance, Dr. Levendorskii began consulting for clients, providing fast and accurate numerical methods for evaluating integrals representing probability distribution functions, derivative prices and special functions. Before pivoting into consulting, he enjoyed a rewarding career in higher education, beginning as a faculty member at Rostov State University of Economics in his home country of Russia as a professor teaching mathematical courses related to economics and finance for over a decade until 2002 and as the university’s mathematics department chair from 1991 to 1996. Subsequently earning a position in the U.S. with the University of Texas at Austin, Dr. Levendorskii taught statistics as a visiting professor in the department of economics between 2003 and 2006, followed by a visiting professor role at the University of Kansas in 2006 teaching financial economics and methods of optimization before returning to the University of Texas at Austin as a senior lecturer of statistics from 2007 to 2008.
Before pivoting into consulting, Dr. Levendorskii enjoyed a rewarding career in higher education, beginning as a faculty member at Rostov State University of Economics in his home country of Russia as a professor teaching mathematical courses applied in economics and finance for over a decade until 2002 and as the university’s mathematics department chair from 1991 to 1996. Subsequently earning a position in the U.S. with the University of Texas at Austin, Dr. Levendorskii taught statistics as a visiting professor in the department of economics between 2003 and 2006, followed by a visiting professor role at the University of Kansas in 2006 teaching financial economics and methods of optimization before returning to the University of Texas at Austin as a senior lecturer of statistics from 2007 to 2008.
Following his time in the U.S., Dr. Levendorskii accepted a position of chair in mathematical finance and insurance at Department of Mathematics, the University of Leicester in the U.K. Between 2008 and 2014, Dr. Levendorskii developed new courses in Advanced Derivative pricing and a distance learning program Financial Engineering and Risk Management. In 2015, he was a honorary professor.
Possessing a rich educational background, Dr. Levendorskii received a Master of Science from Rostov State University, now known as Southern Federal University, in Southern Russia, followed by a Doctor of Philosophy on campus. He also received a Doctor of Science in mathematics from the Institute of Mathematics, National Academy of Sciences of the Ukraine.
As a seasoned researcher, Dr. Levendorskii’s early work focused on partial differential equations and spectral theory. Subsequently, he obtained several important results in quantum groups. Switching back to Spectral Theory, Dr. Levendorskii’s work on perturbations of Schrӧdinger operators with periodic electric and magnetic fields earned him a Soros Grant from Open Society Foundations. For his work on Economics of Transition, he received a Fulbright Award from the Institute of International Education Inc. and the U.S. Department of State, and three grants from the Economics Education and Research Consortium.
A prolific writer, Dr. Levendorskii has disseminated about 200 academic and scientific articles to various peer-reviewed and other professional journals as the result of his research, and published four monographs. Among recent results, Dr. Levendorskii (with co-authors) developed a new general Conformal Bootstrap principle, applied the principle to develop fast and reliable calibration methods for complicated models, and demonstrated that standard methods are either non-reliable or slow or both, especially if Deep Neural Networks are used. The principle can be used in many fields, where complicated integrals needs to be evaluated accurately and fast
Reflecting on his tenured career in academia, Dr. Levendorskii credits his achievements to his dedication to self-education. From an early age, he learned the value of independent learning. This mindset has influenced his career path and his longevity in the industry.
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