Wolfram Computation Meets Knowledge

Wolfram Innovator Award

Wolfram technologies have long been a major force in many areas of industry and research. Leaders in many top organizations and institutions have played a major role in using computational intelligence and pushing the boundaries of how the Wolfram technology stack is leveraged for innovation across fields and disciplines.

We recognize these deserving recipients with the Wolfram Innovator Award, which is awarded at the Wolfram Technology Conferences around the world.

2018

Nicholas Mecholsky

Research Scientist, Vitreous State Laboratory
Adjunct Assistant Professor, Catholic University of America

Areas: Authoring and Publishing, Image Processing, Machine Learning, Nuclear Engineering, Optimization, Physics, System Modeling

Nicholas Mecholsky is a research scientist and professor focusing on optimization and physical modeling. In addition to demonstrating high-level math and physics concepts to his students with the Wolfram Language, he has utilized it in research publications on subjects ranging from animal flocks to autonomous cars to thermoelectric transfer. He is currently involved in a joint project with the US Department of Energy and Vitreous State Laboratory using Wolfram Language image processing and machine learning to model, analyze and predict crystallization phenomena in nuclear tank waste. The project has significantly improved the efficiency of vitrification (transformation into glass), helping to make safer nuclear waste storage a reality.

2017

Dr. Tarkeshwar Singh

Quantitative Analyst and Software Engineer, Quiet Light Securities

Areas: Authoring and Publishing, Finance, Machine Learning, Risk Management

Dr. Singh is a quantitative analyst and software engineer at Quiet Light Securities and an early adopter of Wolfram Finance Platform. In conjunction with the CTO, Robert Maxwell, Dr. Singh brought Finance Platform on board to support daily derivative trading operations by developing extensive strategies and volatility surface models, as well as performing backtesting with intraday market tick data. He also provided daily snapshots of company-wide risk through CDF documents that provided insights and satisfied compliance requirements. He also developed an internal training program to bring quants up to speed with Wolfram technologies. In the future, he hopes to utilize the machine learning capabilities of the Wolfram Language to develop advanced trading algorithms through neural networks.

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