Selected Research Projects
Research projects across computer vision, medical imaging, cybersecurity, and NLP.
DeepOnP: Outlier-Resilient Neural Solver for the Orthographic-n-Point Problem
Jan 2026 – Present- Evaluating robust neural solvers for camera pose estimation under high outlier ratios and image-noise perturbations.
- Investigating top-K hypothesis aggregation and quaternion rotation averaging to improve pose stability and robustness.
Retinal Vessel Segmentation with Deep Learning
Jan 2026 – May 2026- Studied retinal vessel segmentation on DRIVE and CHASE datasets using U-Net and U-Net++ architectures with pretrained backbones.
- Evaluated models using Dice, IoU, sensitivity, specificity, and accuracy, with emphasis on robust medical image segmentation.
Ensemble Learning for Phishing Website Detection
Jan 2022 – Dec 2024- Designed machine learning pipelines for phishing website detection using ensemble-based classification strategies.
COVID-19 Twitter Sentiment Analysis
Jan 2019 – Jun 2022- Built sentiment analysis models to study public opinion during the COVID-19 pandemic using Twitter data.
Technical Skills
- ProgrammingPython, C/C++, MATLAB, Java
- Deep LearningPyTorch, TensorFlow, Keras, CNNs, RNNs, transfer learning, model training & evaluation
- Computer VisionImage classification, segmentation, 3D reconstruction, camera pose estimation, multi-view geometry, OpenCV, COLMAP-related workflows
- Machine LearningClassification, regression, ensemble learning, PCA, gradient boosting, explainable ML
- Data ScienceNumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, data cleaning, statistical analysis, visualization
- Research ToolsGit, Linux, Google Colab, Kaggle, LaTeX, Overleaf, MS Office, HPC/SLURM exposure