Index
Projects
CardIQ takes a month of spending and works out how to split it across your cards for the best return. Underneath it's a strict integer program solved with PuLP and CBC, handling constraints like utilization ceilings and signup bonuses in integer cents so nothing drifts the way floats do. Rather than build a rigid UI full of sliders for goal setting, I fine tuned a small language model on synthetic data, so you say what you want in plain English and it produces the exact solver weights.
Most RAG pipelines are stateless, so every question starts cold and you keep repeating context you already gave. On the QMIND design team I built the parts that fix that. Retrieval runs keyword and semantic search together in Pinecone and merges the two rankings with reciprocal rank fusion, then a cross encoder reranks the top results. An episodic memory module embeds past interactions into their own namespace, scores which ones matter to the current question, and injects them into the prompt without polluting the citations the user sees. It also filters out near identical records so the store doesn't fill up with the same thing.
VisualizeIt generates a texture and blends it onto whatever the camera is looking at, keeping it stuck in place while the subject moves. YOLOv8 finds the target fast and Mask R-CNN cuts out its exact shape. Tracking then splits in two depending on what it found: MediaPipe Holistic computes 3D rigid transforms for people, ORB feature matching computes 2D homographies for solid objects. Stable Diffusion makes the texture, and OpenCV warps it to the right perspective and alpha blends it onto the mask.
An end to end classification pipeline in Python for predicting telecom customer churn. It cleans missing values, applies one-hot and ordinal encoding, and trains a Random Forest ensemble over a dataset of more than 7,000 users. A standalone grid search handles hyperparameter tuning, and seaborn plots feature importance and F1 so you can see what's actually driving the prediction.
A student productivity app in Flutter and Dart that runs on iOS and Android. There's no backend server at all, everything sits in Hive as an embedded local database, so weighted grade calculations, calendar events and swipeable to do lists all keep working with no connection.