Bio


I am a Ph.D. student in the Institute for Computational and Mathematical Engineering (ICME) at Stanford Univesity. I am advised by Biondo Biondi & András Vasy. I expect to graduate in 2022. I obtained a Masters from ICME in Computational Mathematics in 2017. Before coming to Stanford, I had the privilege to work for Schlumberger in USA and Mexico. I finished my undergraduate study in IIT Kharagpur, India.

Honors & Awards


  • Shell Fellowship, Stanford University (2015-2016)
  • DAAD WISE Scholarship, DAAD (Deutscher Akademischer Austauschdienst) (2010)
  • Institute Silver Medal, Indian Institute of Technology, Kharagpur (2011)

Education & Certifications


  • Ph.D., Stanford University, Computational and Mathematical Engineering
  • MS, Stanford University, Computational and Mathematical Engineering (2017)
  • Integrated BS and MS, Indian Institute of Technology, Kharagpur, Geophysics (Major), Physics (Minor) (2011)

Stanford Advisors


Patents


  • Rahul Sarkar, Marco Pistoia. "United StatesEfficient quadratic Ising Hamiltonian generation with qubit reduction", IBM Corporation., Nov 1, 2019

Personal Interests


Traveling, Physics, Finance.

Current Research and Scholarly Interests


Inverse problems, machine learning for seismic imaging, quantum computing

Projects


  • Finding a cover for an ellipse with N rectangles, Stanford University (1/1/2016 - 3/31/2016)

    This is an interesting class project that I did as part of my "Numerical Optimization" class at Stanford. The problem statement is to find a cover for an ellipse with N rectangles, such that the area outside the ellipse is minimized. In this project, I first formulate an equivalent problem that reduces to finding a cover for a circle with the same number of rectangles. The problem is then solved using a Modified-Newton Hessian based approach, and the performance is compared against Steepest Descent. It is found that Modified Newton based approach is much more efficient, although each iteration is significantly more expensive compared to Steepest Descent. I also compare the performance of using different line search algorithms like Goldstein vs Strong-Wolfe conditions, and conclude that the Strong-Wolfe conditions provide much better results.

    Location

    ICME, Stanford University

    For More Information:

  • Dynamic Asset Allocation using Reinforcement Learning, Stanford University (9/20/2016 - 12/16/2016)

    This was a project done as part of the CS221 (Artificial Intelligence) class at Stanford University. In this project, we used reinforcement learning to perform asset allocation between two asset classes - a bond and a stock. Model based and model free techniques were used to perform this task, and the results were compared against one another and also against historical returns of the stock.

    Location

    ICME, Stanford University

    Collaborators

    • Enguerrand Horel, Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2016, School of Engineering
    • Victor Storchan, Software Engineer, Adobe

    For More Information:

  • Automated Aircraft Touchdown, Stanford University (10/1/2016 - 12/31/2016)

    This was a class project done as part of the "Decision Making Under Uncertainty" class at Stanford University. In this project we experiment with a few Reinforcement Learning algorithms with the goal to safely land an aircraft, in the presence of stochastic winds. The project was implemented in python 2.7. Code on github: https://github.com/rsarkar-github/CS238-Automated-Aircraft-Landing-Reinforcement-Learning

    Location

    ICME, Stanford University

    Collaborators

    • Amy Shoemaker, School of Engineering
    • Sagar Vare, School of Engineering

    For More Information:

  • Information Directed Reinforcement Learning, Stanford University (1/1/2017 - 3/30/2017)

    This is a project done as part of CS334 (Advanced Reinforcement Learning) class at Stanford University. In this project, we explored an efficient exploration strategy based on information directed reinforcement learning. Details are provided in the attached paper.

    Location

    ICME, Stanford University

    For More Information:

Lab Affiliations


Work Experience


  • Quantum Computing Graduate Intern, IBM Thomas J. Watson Research Center (6/17/2019 - 9/13/2019)

    Location

    Yorktown Heights, NY

  • Quantum Algorithms Researcher, QC Ware Corp. (7/1/2018 - 9/23/2018)

    Research into quantum algorithms on finance, and topological data analysis.

    Location

    Palo Alto, USA

  • Application Developer, QC Ware (7/1/2017 - 9/25/2017)

    Worked on binary optimization problems that can be solved using a quantum computer. Current projects include : Financial Applications, Topological Data Analysis.

    Location

    Palo Alto

  • Geophysicist, Schlumberger (10/1/2013 - 8/31/2015)

    My role in this position is to foster growth of the new and advanced technology businesses in Mexico, which include Full Waveform Inversion, Seismic Guided Drilling, Advanced Depth Imaging among others. Other responsibilities include training the staff in using these technologies, assist the center in winning new businesses and help in the execution of these projects.

    Location

    Mexico

  • Incubator Program, Schlumberger (7/24/2011 - 9/30/2013)

    I was part of a cohort of ~10 people recruited globally for a special incubator training program. Worked with advanced seismic imaging algorithms and model parameter estimation using full waveform inversion and ray based tomography.

    Location

    Houston, USA

All Publications


  • Texture Based Classification Of Seismic Image Patches Using Topological Data Analysis 81st EAGE Conference and Exhibition 2019 Sarkar, R., Nelson, B. J. 2019
  • Illumination compensation of shadow zones in extended least squares migrated images by solving the linear inverse problem in tomographic full waveform inversion 89th SEG Annual International Meeting Sarkar, R., Biondi, B. 2019: 4297–4301
  • Seismic velocity estimation: a deep recurrent neural-network approach Geophysics Fabien-Ouellet, G., Sarkar, R. 2019; 85 (6): 1--35

    View details for DOI 10.1190/geo2018-0786.1

  • On sets of commuting and anticommuting Paulis arXiv Sarkar, R., Berg, E. v. 2019
  • Snell tomography for net-to-gross estimation using quantum annealing SEG 88th Annual Meeting Sarkar, R., Levin, S. 2018: 5078–82