01
FinRAG: Retrieval-Augmented Generation for Financial QA
Built a financial-domain RAG system that answers investment, risk-analysis, and forecasting queries with improved factuality and reduced hallucinations.
Aug–Dec 2025
🎓 MS Data Science — Class of 2026
Hi, I'm Suraj Thapa
Recent MS Data Science graduate passionate about building intelligent systems with machine learning and computer vision.
About
About Me
I recently graduated with a Master's degree in Data Science from the University of New Haven (May 2026). I am deeply passionate about building intelligent, robust systems that solve complex real-world problems, and I am driven by a fascination with transforming raw data into actionable, high-impact intelligence.
Rather than just training models, I enjoy the entire end-to-end process — from architecting efficient data pipelines and engineering software, to deploying scalable machine learning solutions. I thrive in dynamic environments where rigorous theoretical mathematics meets practical, hands-on software engineering.
I am a strong advocate for the open-source community and value continuous learning, cross-disciplinary collaboration, and breaking down complex topics through detailed technical writing and tutorials.
Actively seeking full-time opportunities in Data Analytics, Machine Learning, and Computer Vision.
Let's connect →
Core Skills
Research
Research Interests
Exploring robust estimation and computer vision with a focus on accuracy, determinism, and reproducibility.
Robust Estimation
RANSAC and deterministic variants to effectively filter extreme outliers.
Computer Vision
Homography, object tracking, and instance segmentation techniques.
Information Fusion
Fusing multi-modal sensory inputs like LiDAR and RGB arrays for SLAM.
Machine & Deep Learning
Training specialized neural networks, optimization algorithms, and NLP applications.
Environmental Science
Applying data-driven and geospatial techniques directly to ecological conservation and analysis.
Projects
Featured Projects
Selected academic and applied work across vision, ML, and systems.
02
Instance Segmentation Using Mask R-CNN
Implemented a three-class instance segmentation pipeline on a custom dataset using Detectron2/Mask R-CNN. Trained & fine-tuned models analyzing mAP, IoU.
Aug–Dec 2025
03
Tango Puzzle Solver with AC-3 and A* Search
End-to-end solver for the Tango logic puzzle with interactive visualization via Pygame. Extended with Q-learning experiments.
Feb–May 2025
04
EDA and DE Pipeline
Exploratory Data Analysis and Data Engineering pipeline ensuring robust transformation, cleaning, and preparation of raw datasets for scalable machine learning.
2024
05
ORB-SLAM3 Experiments
Explorations and integrations using the ORB-SLAM3 framework for visual, visual-inertial, and multi-map SLAM operations across diverse environments.
2024
Blog
Latest Articles
Insights and tutorials on deep learning, machine learning algorithms, and optimization.
Forward & Backward Propagation Explained
A detailed walkthrough of how neural networks make predictions and learn from mistakes, with step-by-step math and Python code.
Visual Guide: 7 Activation Functions Explained
A comprehensive breakdown of ReLU, Sigmoid, Tanh, and other critical neural network activation functions with generated mathematical plots.
Gradient Descent & Its Variants (BGD vs SGD)
Understanding the calculus behind model optimization and why mini-batches strike the perfect balance between speed and stability.
Stop Relying on Accuracy: Real Evaluation Metrics
Why the Confusion Matrix, Precision, Recall, and F1-Scores are far more important than raw Accuracy — especially with imbalanced datasets.
Principal Component Analysis (PCA) Intuition
Defeating the Curse of Dimensionality by using variance-maximizing orthogonal transformations to compress massive datasets.
Law of Large Numbers vs Central Limit Theorem
Unpacking two of the most commonly confused fundamental theorems in classical probability and how they power data science inference.
Contact
Get in Touch
I am a recent MS Data Science graduate actively looking for full-time roles in Data Analytics, Machine Learning, and Computer Vision. Whether you have an opportunity, a collaboration idea, or just want to connect — I'd love to hear from you!