challa Harshini profile photo 1 on Tal

challa Harshini

Student at Amrita Vishwa Vidyapeetham

Kollam

1+ year of work experience

Smartworks
Jul 20263 mosPresent

Bengaluru

NIT Trichy
May 20251 yr 5 mosPresent

India

I successfully completed my Research Internship at the National Institute of Technology Tiruchirappalli, where I worked on the project titled “Remaining Useful Life (RUL) Prediction of Lead-Acid Batteries Using Hybrid Algorithms.” As part of this research, I developed a hybrid predictive model that integrates Convolutional Neural Networks (CNN) and XGBoost to predict the Remaining Useful Life of lead-acid batteries using battery parameter data. The model combines the feature extraction capabilities of CNN with the predictive strength of XGBoost to improve estimation accuracy and support predictive maintenance in battery management systems. This internship provided me with valuable hands-on experience in machine learning, deep learning, data preprocessing, feature engineering, and battery health analytics while strengthening my research and problem-solving skills in intelligent energy storage systems.

challa’s AI Stack

claude code
claude code
claude
claude
cursor
cursor
gemini
gemini
ChatGPT
ChatGPT
ChatGPT Images
ChatGPT Images

Education

Amrita Vishwa Vidyapeetham

Amrita Vishwa Vidyapeetham

20234 yrs2027

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challa Harshini on Tal

Headline

Student at Amrita Vishwa Vidyapeetham

Location

Kollam

AI stack

claude code

claude

cursor

gemini

ChatGPT

ChatGPT Images

Work experience

Operations Executive at Smartworks, Jul 2026 - Present · 3 mos, Bengaluru

Research Intern at NIT Trichy, May 2025 - Present · 1 yr 5 mos, India, I successfully completed my Research Internship at the National Institute of Technology Tiruchirappalli, where I worked on the project titled “Remaining Useful Life (RUL) Prediction of Lead-Acid Batteries Using Hybrid Algorithms.” As part of this research, I developed a hybrid predictive model that integrates Convolutional Neural Networks (CNN) and XGBoost to predict the Remaining Useful Life of lead-acid batteries using battery parameter data. The model combines the feature extraction capabilities of CNN with the predictive strength of XGBoost to improve estimation accuracy and support predictive maintenance in battery management systems. This internship provided me with valuable hands-on experience in machine learning, deep learning, data preprocessing, feature engineering, and battery health analytics while strengthening my research and problem-solving skills in intelligent energy storage systems.

Education

Amrita Vishwa Vidyapeetham

challa Harshini - Operations Executive in Kollam | Tal