Research Fellow

Jul 2024 - Present

NTU Singapore

As a Research Fellow, I am engaged in an experimental and theoretical study on two-phase flow boiling. My responsibilities include developing theoretical and numerical models to predict flow boiling in flow channels with various orientations and creating new channel designs to mitigate the adverse effects of gravitational direction. I conduct flow boiling experiments to validate predictive models and characterize the thermal-hydraulic performance of these new designs. Additionally, I am involved in developing a generative design (GD) strategy for two-phase cold plates to enhance heat transfer and reduce pressure drop. This includes the design and fabrication of new cold plates developed through GD, followed by their experimental characterization.

Post Doctoral Equivalent Fellowship (P.D.E.F.)

May 2024 - Jun 2024

IIT Madras

I continued developing machine learning models for the prediction of Critical Heat Flux (CHF) in boiling heat transfer systems using acoustics and vibration data. Besides, I approached boiling acoustics as a diagnostic tool, emphasizing the decoding of boiling dynamics through spectral observations. Along with that, I have started to work on implementing machine learning models for acoustic pyrometry problems.

Doctor of Philosophy (Ph.D.)

2020 - 2024

IIT Madras - NTU Singapore Joint Degree

Conducted research in experimental heat transfer and acoustics during my PhD, specializing in pool boiling experiments for electronics cooling. Developed machine learning models for audio signal processing and classification, while innovating in 2D temperature measurements using acoustic pyrometry. Published extensively on boiling acoustics, heat transfer demonstrating a comprehensive exploration of complex interdisciplinary challenges.

Masters of Technology

2017 - 2019

National Institute of Technology Agartala, India

During my M.Tech, I conducted advanced studies in pool boiling heat transfer, pioneering research on surface augmentation for electronic device cooling. Explored numerical simulations and experimental investigations to enhance pool boiling efficiency, showcasing expertise in Ansys Fluent and innovative surface design methodologies.

Flow boiling heat load prediction: Boiling Induced Vibrations

Aug 2023 - May 2024

NTU Singapore

• Predicting the heat load in flow boiling over a pin-fin surface
• Evaluated Random Forest Regression, Support Vector Regression and Multi layer perceptron.
• Tools/Libraries (used): Scikit-Learn, Matplotlib, Numpy and Pandas

Effect of non-uniform discretization of domain in acoustic pyrometry

Feb 2023 - Nov 2023

IIT Madras

• Reconstruction of 2D temperature profile based on the Time Of Flight (TOF) estimations.
• Using bias factor, the temperature domain is discretized non uniformly to reduce the error.
• Tools/Libraries (used): Python, Shapely, Matplotlib, Numpy, Pandas

Data-Driven methods for meta material band gap prediction

Feb 2023 - Dec 2023

IIT Madras

• Predicting the band gap of local resonator array across a range of dimensional parameters.
• Evaluated Random Forest Regression, Support Vector Regression and Multi layer perceptron.
• Tools/Libraries (used): Python, Shapely, Matplotlib, Numpy, Pandas

Evaluation of machine learning models in the classification of pool boiling regimes

Mar 2022 - Feb 2023

IIT Madras

• Acoustics pressure and induced vibration measurements are made at various heat fluxes along the boiling curve.
• Classification of pool boiling regimes is achieved using spectral data through machine learning.
• Software: MATLAB

Experimental investigation and numerical simulation of pool boiling heat transfer

Jun 2018 - May 2019

NIT Agartala

• The pool boiling heat transfer augmentation is necessary for the cooling of electronic devices.
• The pool boiling heat transfer augmentation is achieved with the staggered V patterned micro structured surface copper surface.
• Software: Ansys Fluent, Ansys Design Moduler and Ansys Mesh