I hold a PhD in Computer Science and bring over 10 years of experience in software engineering, specializing in performance optimization and GPU-accelerated computing. I have a proven track record of driving significant improvements in query engine optimization, numerical computing, and deep learning, contributing to leading open-source projects such as PyTorch, Apache Arrow, NVIDIA RapidsAI, and more.
- ⚡ Advanced query optimization and indexing strategies, consistently delivering large improvements in query engine throughput and responsiveness.
- 🎯 GPU acceleration, leveraging CUDA and libraries like PyTorch and CuDF to achieve 10x-50x speedups in data-intensive workloads.
- 🔧 Pioneer in PyTorch sparse tensor support, enabling efficient processing of large-scale, sparse datasets.
- 🧠 Algorithm design, creating innovative solutions for complex data processing challenges in big data environments.
- PyTorch - Tensors and dynamic neural networks in Python with strong GPU acceleration.
- Apache Arrow - A development platform for in-memory analytics.
- CuDF - GPU DataFrame library.
- BlazingSQL - A lightweight, GPU-accelerated SQL engine for Python, built on RAPIDS cuDF.
I have a deep passion for data structures and algorithms. What fascinates me most is how they evolve and adapt as they scale—like building a complex bridge with Lego blocks, where each optimization introduces new strengths and challenges. If you’re passionate about these topics too, feel free to connect with me on X (formerly Twitter)!