Lalith Suresh is a systems-focused CEO and co-founder with 16 years of experience building scalable, low-latency distributed systems and incremental computation engines. At Feldera he leads development of the world’s first Incremental Compute engine that maintains arbitrary SQL in real time, enabling enterprises to migrate complex warehouse workloads and achieve sub-second updates with major cost savings. Before founding Feldera he was a senior researcher at VMware Research, where his projects (Anvil, Sieve, DCM) combined formal verification, automated testing, and incremental view maintenance to find dozens of bugs in popular Kubernetes controllers and influence production systems like ElasticSearch. He holds a PhD from TU Berlin and has deep open-source credentials, contributing to DDlog and ns-3 network simulation work that improved SQL-to-DDlog translation and OLSR routing support. Known for translating rigorous research into production impact, he blends academic depth with founder-level product execution out of Palo Alto.
16 years of coding experience
8 years of employment as a software developer
Master of Science, Distributed Computing, Master of Science, Distributed Computing at KTH Royal Institute of Technology
Doctor of Philosophy (PhD), Electrical Engineering and Computer Science, Doctor of Philosophy (PhD), Electrical Engineering and Computer Science at Technische Universität Berlin
B.Tech, Computer Engineering, B.Tech, Computer Engineering at Malaviya National Institute of Technology Jaipur
European Master in Distributed Computing, Distributed Computing, European Master in Distributed Computing, Distributed Computing at Instituto Superior Técnico
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Role in this project:
Back-end Developer
Contributions:47 commits in 5 years 11 months
Contributions summary:Lalith primarily contributed to the implementation of the OLSR routing protocol within the ns-3 network simulator. Their work involved adding Host Network Association (HNA) support, modifying MID message generation, and fixing bugs related to OLSR message handling on different interfaces. The user also updated the documentation and corrected typos in the test files. The contributions focused on enhancing the functionality and stability of the OLSR implementation.
DDlog is a programming language for incremental computation. It is well suited for writing programs that continuously update their output in response to input changes. A DDlog programmer does not write incremental algorithms; instead they specify the desired input-output mapping in a declarative manner.
Role in this project:
Back-end Developer
Contributions:46 reviews, 46 commits, 18 PRs in 2 years 1 month
Contributions summary:Lalith primarily contributed to the DDlog project by implementing and improving features related to the SQL to DDlog translator. Their work involved refining the translation context, simplifying and optimizing the compilation process, and enhancing the jOOQ provider for improved database interaction. Key changes include adding support for insert and delete queries, handling null values, and migrating to the new parsing API, demonstrating a focus on enhancing SQL query handling within the incremental computation framework.
changescomputationinput-outputincrementalrust
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