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!
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.
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.
under Dr Avinash Deshpande, Raman Research Institute, with TRAC•August 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.
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.
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.
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.
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.
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.
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.
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.
Rao, K. K., Vaidya, K., Agarwal, M., Balan, S., and Bhattacharya, S.• Paper in preparation.
