Krishnanunni C G

POB 3SEo2B
201 E 24th St
Austin, Texas 78712
I am a PhD scholar in the Department of Aerospace Engineering & Engineering Mechanics, UT Austin working at the interface of machine learning and mechanics. I am a member of the PHO-ICES group, Oden Institute for Computational Engineering and Sciences and work with my advisor Prof. Tan Bui-Thanh. I received a bachelors degree in Civil Engineering from National Institute of Technology, Calicut in 2017 and a masters degree in Structural Engineering from Indian Institute of Technology, Madras in 2020.
I come from a mechanics background where I undertook projects on signal processing, optimization, and mathematical modelling in solid mechanics with Prof. B. N. Rao at IIT Madras and Prof. Mohammed Ameen at NIT Calicut. I was fortunate to be awarded a research fellowship to work with Prof. Phoolan Prasad at the Indian Institute of Science, Bangalore who exposed me to rigorous mathematics behind nonlinear hyperbolic waves and in particular allowed me to appreciate the beauty of mathematics in mechanics. Currently, my broad interest lies in anything creative and mathematically beautiful. In particular, I work on projects in the field of inverse problems, machine learning, nonlinear estimation theory, and mathematical modelling.
news
Jun 25, 2025 | Our new paper “Lilan: A linear latent network approach for real-time solutions of stiff, nonlinear, ordinary differential equations” is available in arXiv. |
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Jun 1, 2025 | I will be coorganizing the SIAM TXLA 2025 Sectional meeting hosted by the Oden Institute of Computational Engineering and Sciences, UT Austin. Minisymposium proposals can be submitted HERE. |
May 25, 2025 | Our new paper on a “topological derivative approach for deep neural network architecture adaptation” is available in arXiv. |
Mar 15, 2025 | Our new paper on “An adaptive and stability-promoting layerwise training approach for sparse deep neural network architecture” has been accepted for publication in Computer Methods in Applied Mechanics and Engineering. |
Oct 24, 2024 | Won the best poster award at the Workshop on Scientific Machine Learning, October 2024. The poster talks about “approaches for deep neural network architecture adaptation”. Poster is provided HERE. |
selected publications
2025
2023
- IP
2022
- arXivLayerwise Sparsifying Training and Sequential Learning Strategy for Neural Architecture AdaptationarXiv preprint arXiv:2211.06860, 2022