Researcher · Builder. I develop AI systems and publish research at the intersection of machine learning and real-world applications.
I am Priyam Bhattacharya, an AI/ML researcher and developer based in Kolkata, India. My work spans academic research and building real-world machine learning applications.
I have one published paper on a Dual-Axis Solar Tracker system in IJTSRD, and two manuscripts currently under review — covering evolutionary algorithms and a novel sorting algorithm (HRP Sort).
I enjoy the intersection of theory and application — turning research ideas into working prototypes that people can interact with.
One paper published in IJTSRD and two manuscripts currently under review at international journals.
Built end-to-end ML applications using Python and Streamlit, covering healthcare and sports analytics.
Passionate about applying ML to real-world problems — from cardiovascular risk detection to sports analytics.
Pursuing M.Sc. Computer Science at University of Calcutta. B.Sc. Honours with 7.933 CGPA from Sarsuna College.
One peer-reviewed publication and two manuscripts currently under review at international journals.
Presents the design and implementation of a dual-axis solar tracking system that maximises solar energy absorption by continuously orienting solar panels towards the sun. Demonstrates significant efficiency gains over fixed-panel installations through real-time positional adjustment driven by light sensor feedback and microcontroller logic.
↗ View PaperA comprehensive review of evolutionary computation paradigms — including Genetic Algorithms, Particle Swarm Optimisation, Differential Evolution, and Ant Colony Optimisation — examining theoretical foundations, real-world applications, and comparative performance on benchmark optimisation problems.
Proposes HRP Sort, a new sorting algorithm designed for high reliability and parallel execution efficiency. Benchmarks the algorithm against classical approaches (Merge Sort, Quick Sort, Heap Sort) across varying dataset sizes, demonstrating superior performance in parallelisable environments.
End-to-end machine learning applications built with Python and Streamlit, with live interactive demos.
An ML model that classifies cricket batting shots from input data using ensemble classification methods. Users input shot parameters and receive real-time predictions with probability scores.
A clinical ML application for cardiovascular risk assessment using the UCI Heart Disease dataset. Compares Logistic Regression, Random Forest, SVM, and XGBoost with feature importance analysis.
Pursuing postgraduate research in Computer Science with a focus on Machine Learning, AI, and algorithms. Expected completion 2026.
🔵 Currently EnrolledGraduated with Honours. Coursework included data structures, algorithms, machine learning, operating systems, and software engineering.
✅ CGPA: 7.933Completed Indian School Certificate (ISC) examination with Science stream.
✅ 82% (Best of 4)Completed Indian Certificate of Secondary Education (ICSE) examination.
✅ 88% (Best of 5)Published research on a Dual-Axis Solar Tracker in IJTSRD. Currently conducting research on evolutionary algorithms and the HRP Sort algorithm — both manuscripts under review. Each paper is backed by working ML prototypes.
Designed and built end-to-end machine learning web applications — from data preprocessing and model training to interactive UI deployment on Streamlit. Projects span healthcare diagnostics and sports analytics.
View my full academic and professional background in one document.
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Open to collaborations, research discussions, and AI/ML project opportunities.
I'm open to research collaborations, ML project opportunities, and academic discussions. Students and fellow researchers are especially welcome!
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