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Yashil Sukurdeep

Teaching Fellow at The Johns Hopkins University

Baltimore, Maryland

Overview 

Yashil Sukurdeep is an Applied Math Researcher and PhD Candidate at The Johns Hopkins University in Baltimore, Maryland. With a background in machine learning and optimization, Yashil has conducted research in computer vision and image processing, while also gaining experience in venture capital through an internship at Emerald Development Managers LP. Highlights of Yashil's career include conducting research in applied mathematics at a prestigious institution like The Johns Hopkins University and gaining practical experience in venture capital through an internship at Emerald Development Managers LP.

Work Experience 

  • Applied Mathematics Research Assistant

    2018 - Current

    • Conduct research in image and shape analysis, using techniques from differential geometry, optimization and machine learning. • Develop mathematical models, numerical algorithms and software pipelines for image processing tasks, shape registration and shape clustering, leading to applications in computer vision and medical imaging.

  • Teaching Fellow

    2020

    Design and teach the following courses: • The Mathematics of Shapes and Images (EN.500.111) - a seminar style course on image processing and shape analysis for undergraduate students, taught as part of the JHU HEART program. • A Hands-On Introduction to MATLAB (EN.553.282) - an introductory programming course for students in the mathematical sciences.

  • Venture Capital Intern

    2021 - 2021

    • Performed technical diligence to evaluate core technologies and algorithms powering the products developed by startups in the tech, medical imaging, materials engineering and cybersecurity spaces. • Performed market research to assess the quality and viability of investment opportunities.

Emerald Development Managers is a venture capital firm focusing on early-stage growth equity investments.

  • Undergraduate Research Assistant

    2016 - 2018

    • Conducted research in applied probability in the Division of Applied Mathematics at Brown University. • Designed and implemented Markov Chain Monte Carlo methods (parallel tempering and infinite swapping) to estimate solutions for the binary contingency tables problem.

  • Strategy, Research & Development Intern

    2015 - 2015

    • Constructed and solved econometric models used to forecast GDP growth in Mauritius; findings published in MCB Focus, 07/15. • Built a MS Excel database using VBA programming for automatically monitoring the evolution of key macroeconomic variables in the Mauritian economy.

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