Bachelor of Science, Computer Science & Engineering  ·  May 2022 – June 2026
Ahsanullah University of Science and Technology, Dhaka, Bangladesh

RAG   Vector Embeddings   Semantic Search   Compression   Multi-Agent Systems   LLM

Conference Paper  ·  Under review at ICCIT 2026
Embedding-Driven Wind Forecasting with Semantic Tokenization, Phase Prediction, and Human-in-the-Loop Review
Ananto Nayan Bala, et al.
GitHub

A wind forecasting system built on NOAA/METAR data that combines LSTM-based speed prediction with compressed semantic representations of wind states. Wind conditions are tokenized into discrete phases, and a GRU model learns to predict upcoming regimes from those tokens. A Human-in-the-Loop interface lets domain experts review, correct, and confirm forecasts — keeping a human in the decision loop for high-stakes outputs. The system also retrieves historically similar wind states and supports live data feeds.

Adversarial Forecasting with LSTM vs GAN-LSTM  ·  GitHub

Standard LSTMs tend to produce over-smoothed long-horizon forecasts. This work adds a lightweight discriminator that scores how realistic each prediction looks compared to actual sequences, pushing the LSTM toward outputs that better preserve the structural patterns in the data.

Customer Segmentation using PySpark  ·  GitHub

Applies unsupervised clustering to the Online Retail dataset at scale using PySpark. KMeans and Gaussian Mixture Model (GMM) are run and compared to surface distinct customer groups — distinguishing high-value repeat buyers from low-frequency occasional ones.

Diabetes Prediction — Decision Tree vs KNN  ·  GitHub

Side-by-side comparison of a Decision Tree and a K-Nearest Neighbours classifier on a diabetes dataset, evaluating where each model's decision boundaries hold up and where they break down.

Phishing Website Detection  ·  GitHub

A WEKA-based ML pipeline that takes raw URLs and decides whether they are phishing attempts or legitimate sites. Beyond classification, the pipeline uncovers hidden clusters in URL structure and generates human-readable rules that explain which patterns signal risk.