About Me

Hey, I'm Shanmugha Balan, an undergrad at BITS Pilani, Pilani Campus. I'm pursuing a Masters in Physics and Bachelors in Electrical and Electronics Engineering. My primary research interests are solar physics and observational astrophysics, but I'd love to listen to you about most of the things under the sun! I'm currently working on research projects with Dr Kaushar Vaidya from the Astrophysics Group at the Physics Department of BITS Pilani and with Dr Nandita Srivastava from the Udaipur Solar Observatory under the Physical Research Laboratory. I'd love to take up some work on simulation-based projects, so if you have something for me, feel free to get in touch!

Research Projects

Performance Analysis of OTFS in Railway Applications

under Dr Sandeep Joshi, BITS Pilani Current

A new method to modulate signals is the OTFS (Orthogonal Time Frequency Space) modulation, working on the delay-Doppler domain. In this study, a comparative performance analysis of OTFS-based systems against OFDM systems and GFDM systems was done in a high-speed railway scenario with high channel Doppler.

Denoising Astrophysical X Ray Images

under Dr Sainath Bitragunta, BITS Pilani September 2022 - December 2022

Astrophysical images are composed of multiple point sources of light scattered across them. Noise affects these images in a way that is slightly different from usual images. This study aims to apply, test and compare a variety of image denoising algorithms and potentially develop novel algorithms to denoise astrophysical images.

Indian Sky Watch Array Network (SWAN) Project

under Dr Avinash Deshpande, Raman Research Institute, with TRACAugust 2022

The Indian SWAN Project aims to set up a Very Large Baseline Interferometry Telescope across multiple campuses in India for the reliable detection of energetic radio transients. The SWAN system can also help in the study of inter-planetary weather, intergalactic gas and in high angular resolution imaging of low frequency radio sources. A team from BITS Pilani undertook in a one week trip to the Gauribidanur Radio Observatory to get hands-on training with the SWAN instrumentation.

Reconstruction of Light Curves with Pan-STARRS Data

under Dr Roger CC Lin, University of Hawaii, Institute for Astronomy January 2022 - July 2022

Variable stars are stars which vary in their brightness in the sky. The variation in their brightness can be studied with respect to time by plotting their light curves. For periodic variable stars with a known period, we can build phased light curves; where plot brightness as a fraction of the completed period. Variable stars often show long term trends in their brighness which is often not so apparent in phased light curves. We build a deep learning based time series model to explore how well light curves can be reconstructed.

Optimal Trajectory Determination for Lunar Landing Missions

under Dr Dipti Patil, Space Technology Cell, Pune October 2021 - January 2022

With humanity looking to expand beyond our planet, we're looking to explore the Moon as a first base. Automating the landing for lunar missions would help make many more missions succesful by reducing human error significantly. Reinforcement learning based systems have recently shown promise solving similar tasks and when combined with standard control theory approaches, might just be the solution. In this work, we theorized the viability and analyzed the capability of such systems to produce optimal and controlled landing trajectories. This work belongs to the Indian Space Research Organization.

DCNs to mimic Matched Filtering for Gravitational Waves

with The Radio Astronomy Club, BITS Pilani May 2021 - July 2021

Matched filtering is a standard method to detect well modeled gravitational wave signals. However, the method is computationally expensive, especially at low latencies. Deep convolutional neural networks offer a more efficient solution at comparable accuracies. We reimplement this paper by Gabbard et al and achieve a comparable accuracy with fewer parameters.

Properties of Open Clusters using Gaia Data

under Dr Kaushar Vaidya, BITS Pilani January 2021 - April 2021

Gaia is an astrometry mission by the ESA, which has helped in cataloguing numerous objects in our galaxy in unprecedented detail. The cluster membership information based on Gaia DR2 data of open clusters will be used to understand the effect of dynamical evolution on the observed properties of star clusters. In particular, star clusters with a clear binary track are examined to study the radial distributions of these binary stars with respect to the radial distribution of single stars. Alongside, the morphology of star clusters is examined to look for the presence of any tidal tails in the star clusters. Report.

Graph Theoretical Analysis of Protein Networks

under Dr Karthik Raman, IIT Madras May 2018 - June 2018

Protein networks for any organism form an intricate structure which can be mapped onto a mathematical graph. This graph can then be studied to find how the various proteins interact with each other. Finding the most well connected proteins gives us an idea about which proteins are essential to an organism. If it is a pathogen for which we are performing this analysis, we might be able to determine some possible proteins to target. This can result in new, more potent drugs. The data for the analysis of E. coli was taken from the STRING database and was analysed with NetworkX, a python package for analysing graph data. Report.


A Gaia EDR3 search for tidal tails in disintegrating open clusters

Bhattacharya, S., Rao, K. K., Agarwal, M., Balan, S., and Vaidya, K. Monthly Notices of the Royal Astronomical Society, Volume 517, Issue 3, December 2022, Pages 3525–3549.

Dynamical Evolution of Open Clusters using Gaia EDR3

Balan, S., Rao, K. K., Vaidya, K., Agarwal, M., and Bhattacharya, S. Poster at the Gaia DR3 Symposium, IIA Bangalore, July 2022; Paper in preparation.

Determination of dynamical ages of open clusters through the A+ parameter – II

Rao, K. K., Vaidya, K., Agarwal, M., Balan, S., and Bhattacharya, S. Paper in preparation.

Technical Skills

  • Proficient

  • Python

  • Pandas | Numpy | Scipy
  • Image Manipulation and Plotting

  • OpenCV | Matplotlib | Seaborn | Plotly
  • Machine Learning

  • Tensorflow | Pytorch | Scikit-Learn
  • Astrophysics

  • Astropy | SunPy | PFSSPY | CASA
  • Others

  • C | C++ | MATLAB | Julia
  • Familiar

  • Front End Web Development

  • HTML | CSS | JS
  • Technologies

  • LaTeX | Bash | Git | Linux

Contact Me


+91 77340 18009

University Email


Personal email