Siddhant Ray is a research-focused systems engineer and PhD candidate at the University of Chicago with eight years of experience spanning networking, cloud systems, and NLP. He designs joint quality-latency optimizations for RAG LLM systems and builds Transformer-based per-packet latency predictors to cut tail latency in latency-sensitive networks. His work bridges theoretical resource-scheduling and practical KV-cache reuse patterns, evidenced by METIS (SOSP'25) and SwiftQueue (NINeS'26) contributions. Previously he advanced programmable networks and SDN routing algorithms and applied NLP to political corpora at ETH Zurich, combining domain knowledge across networking and language. He has industry experience at Microsoft and research stints across UPC Barcelona and ETH, and brings a knack for turning model-level insights into packet- and system-level performance gains. Based in Chicago, he pairs rigorous academic training (PhD UChicago, MSc ETH Zurich, BTech VIT) with applied systems engineering for production-scale problems.
8 years of coding experience
2 years of employment as a software developer
Bachelor of Technology - BTech, Electronics and Communication Engineering, Bachelor of Technology - BTech, Electronics and Communication Engineering at Vellore Institute of Technology
Master of Science - MSc, Electrical Engineering and Information Technology, Master of Science - MSc, Electrical Engineering and Information Technology at ETH Zürich
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Chicago
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