Anand Lo

Anand Lo

"Exploring today, creating tomorrow."

About Me

I'm currently pursuing a Bachelor of Applied Computer Science at Dalhousie University, with a minor in Statistics. I enjoy exploring new technologies and finding creative ways to solve problems. In my free time, I love swimming, playing badminton, and listening to music. These activities help me stay balanced and fuel my curiosity for learning and discovery.

Anand Lo

Experience

TDP Intern

Seaspan | January 2025 – Present | Vancouver, BC, CA

  • Developed a Retrieval-Augmented Generation (RAG) model using Python and LangChain to index 500+ project documents, reducing manual retrieval time by 60%.
  • Engineered an automated data validation pipeline with OpenPyXL and Pandas, validating over 1M records and streamlining Power BI reporting.

Junior Machine Learning Engineer

Omdena (Hosted by HOT) | January 2025 – Present | New York, NY, USA (Remote)

  • Reduced segmentation inference time by 40% by freezing the SAM2 image encoder and fine-tuning on 50,000+ satellite images with AdamW optimization and a linear warmup-decay schedule.
  • Improved segmentation accuracy by 12% through dynamic prompt selection and optimizing mask predictions with sigmoid activation and post-processing.

Geospatial Developer

Dalhousie Space Systems Lab (DSS) | February 2025 – Present | Halifax, NS, CA

  • Implemented a Python-based orthorectification pipeline using GDAL and Rasterio to correct satellite image distortions.
  • Leveraged satellite ephemeris data (position and attitude) to apply polynomial transformation models for precise georeferencing and coordinate assignment.

Junior Computer Vision Developer

Neuroimaging Probe Placement (NPP) | January 2024 – April 2024 | Halifax, NS, CA

  • Collaborated with a team of 7 to develop a non-invasive brain mapping method by integrating MR image segmentation with curvature analysis to compute optimal probe insertion points.
  • Developed an iOS tool using RealityKit to capture real-time LiDAR data, and used OpenCV and MediaPipe to detect over 450 facial landmarks while synchronizing accelerometer I/O for spatial calibration.

Projects

Falcon 9 Landing Prediction

Developed SVM, Decision Tree, and Logistic Regression models to predict SpaceX Falcon 9 landings. Processed SpaceX API data using SQLite3 and SQLAlchemy, and visualized geospatial trends with Folium and Dash-Plotly. Achieved up to 88.92% accuracy after hyperparameter tuning with GridSearchCV.

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Breast Cancer Diagnosis

Built a predictive model to classify breast tumors using 48,842 patient records. Applied PCA for dimensionality reduction and trained an SVM classifier with an RBF kernel, fine-tuned with Randomized Search CV and 5-fold cross-validation to achieve 94.7% accuracy and 89% recall.

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Intrusion Detection System

Developed an IDS to classify network traffic using the KDD Cup 1999 dataset (over 4.9M records). Employed Gaussian Naive Bayes, Decision Trees, Random Forest, SVM, and Logistic Regression to achieve 99.97% test accuracy with Random Forest, while optimizing training and inference times.

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CoaSight

Extracted Sentinel-2 imagery using Google Earth Engine with polygon-based selection, cloud filtering (<20%), and temporal filtering. Converted GeoTIFFs to JPG with Rasterio, standardized images with NumPy, and detected shorelines via OpenCV’s Canny Edge Detection to calculate retreat rates and shifts.

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Ocean Wave Height Prediction

Developed an LSTM model in TensorFlow to predict wave heights at the Herring Cove buoy using over 31,000 time-series data points. Applied feature engineering with a 60-timestep sliding window and trained for 20 epochs to achieve an RMSE of 0.346.

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Climate Change Sentiment Analysis

Developed a BERT-based sentiment analysis model to classify 7,000 climate change tweets. Preprocessed data with DistilBERT, applied padding and attention masks, and used features from BERT’s last hidden state to implement a Logistic Regression classifier, achieving 81.8% test accuracy.

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Farmalytics

Developed a prototype for the NASA Space Apps 2024 Hackathon, creating a satellite-driven platform that provides farmers with real-time insights to mitigate contamination risks and optimize irrigation. Extracted and preprocessed EO data, and trained an XGBoost model to predict correlations between satellite data and water quality, leveraging NLP to generate actionable risk scores.

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Event Management Platform

Built a PHP-based platform featuring secure login, dynamic forms, and full CRUD operations. Implemented data storage with MySQL and used JavaScript, XML, and JSON for client-server communication, alongside a responsive interface using HTML5, CSS3, and AJAX.

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Diamond Price Analysis

Built an XGBoost regression model in Snowflake to analyze diamond pricing, achieving an R² score of 98.36. Utilized Snowpark for feature engineering and GridSearchCV for hyperparameter tuning, and deployed the model as a Vectorized UDF for efficient large-scale processing.

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Skills

Programming Languages

Python, SQL, C++, JavaScript, Java

Libraries & Frameworks

PyTorch, TensorFlow, Keras, Scikit-Learn, OpenCV, MediaPipe, Hydra, LangChain, GDAL, Rasterio, Folium, Seaborn, statsmodels, Flask

Tools & Platforms

AWS, Snowflake, Docker, Kubernetes, Git, Jira, Confluence, Power BI, Tableau, Databricks, GEE

Certificates & Hackathons

Certifications

Hackathon Participation

  • NASA Space Apps 2023 (Winner) | Developed a full-stack exoplanet visualization platform using Python & Flask
  • NASA Space Apps 2024 | Advanced data analysis solutions for space exploration
  • DeepSense Hackathon | Leveraged ocean data for environmental insights
  • Ocean of Data Hackathon | Designed data-driven solutions to optimize marine sustainability
  • Deloitte Ideathon | Innovated ideas for industry-specific challenges
  • RBC Innovative Challenge | Explored tech solutions for financial sector problems
  • ShiftKey Labs Gen AI Hackathon | Built AI models to enhance productivity and automation

Education

Dalhousie University

Bachelor of Applied Computer Science, Minor in Statistics (GPA: 3.86)
September 2022 – Present (Expected 2026)

  • Certificate in Data Analytics, Certificate in Managing Data
  • Sexton Scholar – Awarded for academic excellence
  • Dean’s List – Consistently achieved top 10% of class
  • Recipient of the General Entrance Scholarship and the Computer Science Faculty Scholarship for outstanding performance

Leadership

Founder & President

Dalhousie Machine Learning Society (DMLS) | January 2025 – Present | Halifax, NS

  • Founded DMLS and grew the community from 0 to 100+ members.
  • Organized events, workshops, and networking sessions for ML education.

Peer Mentor

Together@Dal Mentorship Program | August 2024 – Present | Halifax, NS

  • Mentored 30+ first-year students with personalized academic support.
  • Led bi-weekly sessions on SMART goals and study strategies.

Student Representative

Computer Science Society | April 2023 – Present | Halifax, NS

  • Advocated for student needs through regular meetings with faculty and administration.
  • Coordinated over 40 course representatives to ensure effective communication.

Team Leader

McDonald's | October 2022 – Present | Halifax, NS

  • Led teams during peak hours to ensure smooth operations.
  • Trained new employees, improving operational efficiency by 15%.

International Students Rep

Dalhousie Student Union (DSU) | November 2023 – April 2024 | Halifax, NS

  • Advocated for over 1,000 international students by managing inclusivity programs.
  • Distributed 300+ emergency bursaries and enhanced financial aid support.