Bio


I am a PhD student in the Institute for Computational and Mathematical Engineering. My research interests lie in Numerical Linear Algebra and Parallel Computing. I'm working with Prof. Eric Darve on developing fast algorithms for general linear systems. I obtained my B.Tech (Honors) in Chemical Engineering from Indian Institute of Technology Madras, India.

I was born and brought up in Neyveli, an industrial town in south India. I enjoy listening to Indian music and reading novels.

Education & Certifications


  • B.Tech (Honours), Indian Institute of Technology Madras, Chemical Engineering (2016)

All Publications


  • Variation in COVID-19 Data Reporting Across India: 6Months into the Pandemic. Journal of the Indian Institute of Science Vasudevan, V., Gnanasekaran, A., Sankar, V., Vasudevan, S. A., Zou, J. 2020: 1–8

    Abstract

    India reported its first case of COVID-19 on January 30, 2020. Six months since then, COVID-19 continues to be a growing crisis in India with over 1.6 million reported cases. In this communication, we assess the quality of COVID-19 data reporting done by the state and union territory governments in India between July 12 and July 25, 2020. We compare our findings with those from an earlier assessment conducted in May 2020. We conclude that 6months into the pandemic, the quality of COVID-19 data reporting across India continues to be highly disparate, which could hinder public health efforts.

    View details for DOI 10.1007/s41745-020-00188-z

    View details for PubMedID 33078049

  • On the role of hydrodynamic interactions in the engineered-assembly of droplet ensembles SOFT MATTER Raj, M., Gnanasekaran, A., Rengaswamy, R. 2019; 15 (39): 7863–75

    Abstract

    Droplets, as they flow inside a microchannel, interact hydrodynamically to result in spatio-temporal patterns. The nature of the interaction decides the type of collective behaviour observed. In this context, we study the application of droplet microfluidics in the area of complex-shape particle synthesis. We show how the dynamics of droplet motion, the steady-state characteristics, the short and long-range hydrodynamics, the dependence on inlet conditions etc. are all related to the features that characterize a device like the functionality (producing many shapes) and robustness (insensitivity to fluctuations). Two primary operating regimes are identified, one where long-range interactions are dominant and the other where they are short-range. In the former, the shapes formed by droplets are steady-state solutions to the governing equations, while in the latter they are a function of how the droplets enter the channel (frequency of entry). We show that identifying the inlet conditions for producing a particle of the desired shape requires the use of a systematic approach to design which involves solving an optimization problem (using genetic algorithms) to identify the optimal operating strategy. With the knowledge of the hydrodynamics between the droplets, we demonstrate how one can reduce the complexity of the design process. We also discuss the control strategies required if one were to realize the identified operating strategy experimentally.

    View details for DOI 10.1039/c9sm01528k

    View details for Web of Science ID 000496486700013

    View details for PubMedID 31531495