I build autonomous data engines and high-performance analytics platforms. Specializing in Web3 On-chain Data, Deep Learning (NLP/LSTM), and Python Automation.
From predicting crypto market volatility to architecting Big Data pipelines with Spark & Hadoop—I transform complex, unstructured data into strategic assets.
A selection of my recent work in Machine Learning, Deep Learning, and Data Science.
Professional analytics platform for Xandeum pNodes featuring real-time gossip visualization, storage efficiency metrics, and historic data persistence.
Multivariate LSTM model integrating Crypto Fear & Greed Index. Achieved significantly lower error (MAPE 2.33%).
Exploring CLIP's performance in zero-shot image-text classification for livestock.
Comparing FastText, Transformer, and LSTM using GloVe embeddings on AGNews.
Predicts weekly sales using XGBoost. Deployed as an interactive Streamlit dashboard.
Analyzed market trends using Python, Spark, and Hadoop to identify patterns.
Applying K-Means clustering to identify distinct customer groups for marketing.
Predicting herbal compound activity for breast cancer therapy using ML.
Simulating Meta Inc. stock price trajectory using stochastic modeling.
Time-series volatility modeling for climate data analysis (Temperature & CO2).
Data analytics for predicting and analyzing global EV sales trends (2010-2024).
Analyzing global renewable energy adoption trends using Looker Studio.
System to automate file backup and monitor security across servers.