i'm a computer science undergraduate specializing in artificial intelligence, with a strong interest in backend engineering, distributed systems, and end-to-end machine learning pipelines. i enjoy exploring ai engineering workflows, experimenting with langchain, agents, and model integration, and designing scalable system architectures.
i have worked with c++, python, scala and tools like docker, kafka, and various cloud platforms with industrial exposure during my internship at microsoft. my current intellectual pursuits are centered around machine learning research!
some of my recent research interests include:
worked on the azure data spark dev native execution engine (nee) using c++, scala, velox, gluten, docker, azure devops. integrated fuzz-testing pipelines, improved operator reliability, and enhanced ci/cd diagnostics for large-scale distributed sql execution.
researched recommender systems and computer vision using pytorch, tensorflow. improved ndcg/mrr on mf models and benchmarked cnn/transformer architectures for emotion recognition on fer2013.
fine-tuned pegasus on the aeslc dataset for abstractive summarization in low-resource email domains, benchmarking domain transferability.
designed optimal path algorithms using dijkstra's and custom c++ regression models for yield prediction and demand forecasting.
end-to-end workflow system integrating azure openai and ai search for enterprise-grade automation.
high-throughput log ingestion and search system handling 50k+ logs/sec using go concurrency and kafka.
sequence-to-sequence summarization model using encoder-decoder transformers.
generative models to produce smooth volatility surfaces for option pricing.
privacy-first clipboard history manager with fuzzy search and aes-256 encryption.