Welcome to my GitHub! I'm a 3rd-year Applied Computer Science student w/ Statistics at Dalhousie University, blending my passion for data science, machine learning, and software development with real-world applications. Whether it's predicting coastal erosion, optimizing water management for farmers, or segmenting fish underwater, my projects strive to make an impact through innovation and creativity.

🏅 Sexton Scholar | Dean’s List | Entrance Scholarship Recipient
📍 Based in Halifax, Nova Scotia | Website | LinkedIn

Dalhousie University, Halifax, NS (2022 – 2026)

• Bachelor of Applied Computer Science (3.86 GPA) with a Minor in Statistics
• Certificates: Data Analytics, Managing Data
• Relevant Coursework: Machine Learning, Statistical Analysis, Data Analytics, Cloud Computing, Data Structures

Python, R, SQL, C, Java, JavaScript, PHP, HTML/CSS

TensorFlow, PyTorch, OpenCV, Scikit-Learn, MediaPipe, U-Net, ConvLSTM, React, Flask, Tailwind CSS

AWS, OpenShift, Docker, Kubernetes, Git, Tableau, Power BI, Snowflake, Folium, Jira, Confluence

• IBM Data Science Certified (2024)
• AWS Certified Cloud Practitioner (CLF-C02) (2024)
• IBM Containers with Docker, Kubernetes & OpenShift (2024)

A NASA Space Apps 2024 project helping farmers optimize irrigation and mitigate contamination risks:

• Built a data pipeline processing over 1GB of NASA Earth Observation data with Pandas, Scikit-learn, and XGBoost.
• Achieved R² of 0.83 for contamination risk prediction.
• Designed an intuitive user interface using JavaScript and Tailwind CSS.
  View Project

• Developed a U-Net with ConvLSTM model to segment fish in underwater videos, achieving 99.99% Mean IoU.
• Integrated real-time video processing with OpenCV for efficient mask overlays.
• Dataset: DeepFish | Code Repository

• Built an LSTM model forecasting wave heights at Herring Cove, leveraging time series data of 31,000+ points.
• Achieved RMSE of 0.346, offering practical insights for marine safety.
  Code Repository

• A startup simplifying scheduling by consolidating Gmail and Outlook emails using NLP to identify key events.
• Integrated SMS notifications and iOS Reminders app for seamless task management.
• Part of the Collide Discover 2024 Program.

• Analyzed erosion patterns in Nova Scotia using satellite imagery across timeframes.
• Trained machine learning models to track depletion rates, creating GIS visualizations.
• Tech Stack: Python, Google Colab, ArcGIS

• NASA Space Apps Challenge Winner (2023)
• Participant in multiple hackathons: DeepSense Hackathon, ShiftKey Labs Gen AI Hackathon, and more.
• Peer Mentor for the Together@Dal Program
• BACS Student Representative (2024-25) for the Dalhousie Computer Science Society

NeuroCognitive Imaging Lab, Dalhousie University

• Developed a LiDAR-based brain mapping tool using RealityKit, OpenCV, and MediaPipe.
• Enhanced probe positioning accuracy through accelerometer data analysis.

McDonald’s, Halifax, NS

• Managed a team of 12+ crew members, fostering a high-performance environment.

• DeepSense Hackathon: Predicting coastal changes with ML and satellite imagery.
• Exploring process automation and real-time quality checks using computer vision for supply chain optimization.

If you’re interested in collaborations, mentorship, or just a good tech conversation:
📧 Email: AnandLo@dal.ca
🌐 Portfolio | GitHub

Together, let’s build something impactful!