This website is a living archive of my work and ideas—constantly evolving as I learn and explore new frontiers. What do I do? I design and build ETL systems and query engines, architecting scalable data pipelines that power analytics and AI-driven insights. My work spans big data, machine learning, and scientific computing, with a strong focus on automation, real-time processing, and intelligent decision-making. Lately, I’ve been fascinated by the AI revolution—how LLMs are transforming the way we interact with data, automate workflows, and make sense of unstructured information. From natural language understanding to predictive analytics, AI is reshaping industries, and I’m always experimenting with ways to integrate it into scalable systems. Whether it’s optimizing AI workloads, building adaptive data pipelines, or exploring how intelligent agents can enhance decision-making, I’m constantly pushing the boundaries of what’s possible.
I design and build scalable big data and ETL systems from the ground up for early-stage startups, optimizing data pipelines for high-volume processing and real-time analytics. Focused on reliability, efficiency, and cloud-native architectures, ensuring seamless scaling and cost-effective performance. Lately, I’ve been integrating AI-driven analytics and leveraging LLMs for automated data processing, anomaly detection, and intelligent insights. With a deep understanding of AI capabilities, I build systems that enhance decision-making, automate workflows, and scale machine learning models for real-world applications.
Lately, I've been pleasantly surprised with Rust and have been working with it for its memory safety and performance benefits, alongside Python and Java for scalable backend systems. My background also includes MATLAB, R, and JMP for numerical computing, as well as Scala and Haskell for functional programming. I enjoy working with distributed systems, leveraging technologies like Kafka and Spark for big data processing, and have experience optimizing algorithms for high-performance computing. Whether it's low-level systems programming or large-scale data pipelines, I thrive in solving complex technical challenges with efficiency and scalability in mind.
Progress is sharing intelligence. Like Yuval Noah Harari thinks, human civilization wouldn't have been as successful as it is if not for congnitive revolution. I think open sourcing plays a big role in that. I love making sense of messy data—whether it’s spotting fraud with anomaly detection, enhancing images with deep learning, or crunching sensor data for real-time insights. From training neural networks to fine-tuning models for predictive analytics, I work with TensorFlow and PyTorch to build scalable ML systems. Whether it’s NLP, time-series forecasting, or AI-powered image processing, I enjoy turning raw data into smart decisions.
Find my public projects on to public repositories here on my GitHub page. You can contact me via email here.
Find my docker hub images Docker hub.