1. Volunteer at Teach India
Outreach, Worked with a local NGO, Sewa Bharti, to teach underprivileged kids Science and Math, Aug 2007 - Mar 2008
Outreach, Worked with a local NGO, Sewa Bharti, to teach underprivileged kids Science and Math, Aug 2007 - Mar 2008
Outreach, Taught game-programming in Python in an underserved school under STEM Mentoring Initiative at SBU, Spring 2015
Outreach, Organizer of quarterly STEM webinars geared towards students and early career professionals, Spring 2017 - current
Outreach, Conduct workshops related to Unix, Git and Python in education institutions, March 2019 - current
Outreach, This workshop introduced debugging tools such as GNU's GDB, Valgrind and DDT to tackle the bugs encountered in high performance computing, April 13, 2019
K-12 Education, Created and curated content for V2Learn, a K-12 self-paced e-learning tool for Mathematics, Fall 2009
Undergraduate Course, Business Mathematics (calculus, linear programming, statistics) at IIPM, Gurgaon (India), Spring 2009
Undergraduate Course, BUS 220 (Introduction to Decision Sciences) at Stony Brook University, Fall 2015
Graduate Seminar Course: MAT696, Computational tools and techniques for STEM, Spring 2019
Course Description: Computation is now an integral part of the advancement of science, alongside theory and experiment. Computational modeling, analysis and visualization capabilities offer widespread applications across many disciplines. In this course, a quick and practical introduction to writing reliable and sustainable software in Python utilizing good practices and standard development tools will be presented. This includes main principles of object oriented programming, unit testing, version control, debugging, and performance optimization tools. The course will provide a basic understanding of computer architecture and memory hierarchy, data structures, including external libraries in the code, and handling large datasets. Some standard software in computational science, such as VisIt for data visualization and Numpy and Scipy for post-processing will be used. Additionally, an introduction to parallel programming through the use of Message Passing Interface (MPI) will be covered using mpi4py.
Workshop, Stony Brook University, Aug 23-24, 2012
Workshop, Institute for Advanced Computational Science, Stony Brook University, Aug 23, 2013
Workshop, Institute for Advanced Computational Science, Stony Brook University, Jan 23-24, 2014
Summer School, Institute for Advanced Computational Science, Stony Brook University, July 8-18, 2014
Workshop, Institute for Advanced Computational Science, Stony Brook University, Aug 21, 2014
Workshop, National Energy Research Scientific Computing Center (NERSC), LBNL, Oct 28, 2014
Workshop Series, University of Oklahoma, Jan 20 - Apr 28, 2015
Summer School, Argonne National Lab, Aug 2-14, 2015