Dec 2022 – Dec 2022 · 0 mo · Trieste, Friuli-Venezia Giulia, Italy · On-site

• Attended the winter school on 'Machine Learning in Biology'.

May 2022 – Jul 2022 · 2 mos · Dresden, Saxony, Germany

• Project on analysing fluorescent microscopy images of intracellular mesoscale structures with deep learning models under the guidance of Dr. Ivo Sbalzarini, MOSAIC Group.

Jun 2021 – Aug 2021 · 2 mos

• Project on Differential Convex Optimization Implicit Layers in Deep Learning under the guidance of Dr. Ivo Sbalzarini, MOSAIC group for Scientific Computing for image-based Systems Biology. Studied differentiable convex optimisation implicit layers and implemented them using Cvxpy package in Python on a toy denoising problem. Currently investigating the utility of differentiable layers in neural networks for learning consistent PDE differential operators by embedding hard moment constraints in the implicit layers.

Apr 2021 – Jul 2021 · 3 mos

• Project on Product Demand Forecasting using Extreme Learning Machines and Harris hawks optimization under the guidance of Dr. Bugra Alkan, School of Engineering, Computer Science and Informatics Department. Built a novel forecasting model - an extreme learning machine model hypertuned with Harris Hawks optimisation algorithm to improve accuracy of predicting future product demand from historical sales data. Used the model to predict future product sales of a gaming consoles company and showed that our ELM-HHO approach had superior performance to other models like ARIMA, LSTM, GRU, ELM and ELM-BO. Work published in Applied Intelligence, Springer.

Apr 2021 – Jul 2021 · 3 mos

• Project on refining, simulating and validating discrete-continuous models of metabolic-regulatory networks under the guidance of Dr. Alexander Bockmayr, Mathematics in Life Sciences group. Studied flux balance analysis, dynamic flux balance analysis, regulatory flux balance analysis, regulatory dynamic enzyme flux balance analysis in constraint-based modelling of metabolic regulatory networks of biological organisms. Performed FBA, dFBA, rFBA on core carbon metabolic model of E. Coli using COBRA toolbox in Matlab, COBRApy in Python and Flexflux. Performed deFBA and r-deFBA analysis using pyrrrate-FBA software on core carbon metabolic model of E. Coli.

Jan 2021 – Jan 2021 · 0 mo · Bengaluru, Karnataka, India

• Attended the Thirsting for Theoretical Biology Programme.

Dec 2020 – Dec 2020 · 0 mo · Moscow City, Russia

• Attended the Winter School on Machine Learning in Robotics

May 2020 – Jul 2020 · 2 mos

• Worked on a team project to enable offline voice commanding in Mobile Word:
• 1) Built a Convolutional Neural Network model to perform text classification of commands into 26 different intents.
• 2) Built a CNN based named entity recognition model to perform parameter extraction of commands.
• 3) Deployed models on Android app for testing.
• 4) Implemented dynamic download of models on device from Azure Blob Storage and direct download from a Onedrive link.
• 5) Built a data collection Android app for collecting transcripts of voice commands from different users.
• 6) Built an automated transcription pipeline to convert voice commands to text and included all inaccurate speech-to-text conversions in dataset to improve offline speech-to-text accuracy.

Apr 2020 – Apr 2021 · 1 yr

• Used dynamic network biomarkers, surprisal analysis and other computational methods to investigate the presence of tipping points in the context of epithelial-mesenchymal transitions under the guidance of Dr. Mohit Kumar Jolly at the Cancer and Systems biology laboratory in the centre of Biosystems Science and Engineering.

Dec 2019 – Dec 2019 · 0 mo · Bengaluru, Karnataka, India

• Attended the ICTP-ICTS Winter School on Quantitative Systems Biology

May 2019 – Jun 2019 · 1 mo · Punjab,India

• Project titled 'Forecasting tipping points through a model-less approach',non-linear dynamics,theoretical ecology,mathematical modelling,advanced calculus

Dec 2018 – Dec 2018 · 0 mo · Bhopal

• Attended the National Science(Vijyoshi) camp for KVPY fellows