Ananya
Barthakur

Python implementation for electronic energy approximation and molecular orbital visualization in quantum chemistry applications.

• —Implemented the Self-Consistent Field (SCF) algorithm for solving the many-electron Schrödinger equation
• —Built efficient integral evaluation and matrix manipulation routines for molecular systems
• —Achieved numerical stability through symmetric orthogonalization and convergence acceleration
• —Designed modular architecture for different basis sets and molecular configurations

Python · NumPy · Quantum Chemistry · Scientific Computing

CNN and RNN models for breast cancer tissue analysis, enabling automated identification of tumor characteristics in TNBC research.

• —Implemented U-Net and FCN architectures for nuclei segmentation in histopathological images
• —Achieved over 90% accuracy identifying cancer nuclei morphology and characteristics
• —Built a comprehensive data augmentation pipeline for medical imaging robustness
• —Designed custom loss functions combining Dice loss and boundary loss for precise segmentation

PyTorch · Computer Vision · Medical Imaging · Deep Learning

Kernel Ridge Regression model with Gaussian Processes to predict molecular potential energy surfaces, using PyTorch for automatic differentiation.

• —Implemented Kernel Ridge Regression with custom kernel functions for molecular property prediction
• —Used Gaussian Processes for uncertainty quantification in energy surface mapping
• —Leveraged PyTorch's automatic differentiation for gradient-based optimization
• —Achieved high accuracy predicting molecular configurations and energy landscapes

Python · PyTorch · Machine Learning · Gaussian Processes · Quantum Chemistry