◦ Designed and developed a novel, cache-friendly in-memory storage engine in C++ for dynamic graphdatabases that handle Hybrid Transactional/Analytical Processing (HTAP) workloads, achieving up to73× transactional update throughput and 357× analytical scans on snapshot queries compared to existingstate-of-the-art systems.◦ Designed a graph storage layout to efficiently support both snapshot and historical queries.◦ Designed the first graph database storage system to integrate native support for out-of-order updates,addressing a common challenge that occurs when receiving updates from streams.◦ Paper Accepted in VLDB 2024

AI4DI: Prediction of touch event on the tactile sensor using deep learning

Graduate Assistant