Founding Engineer & Systems Builder. Expert in JVM internals, low-latency engines, and scaling fintech platforms.

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Shamsuddeen K S  • Peerlist

Designed and developed “Nomos,” a lightweight, high-performance, developer-first rule engine for Java & Spring Boot: built as a simple, fast, and transparent alternative to heavyweight rule engines like Drools. Key Work & Responsibilities: • Core Engine: Architected the nomos-core module with a forward-chaining RuleEngine and immutable Facts system supporting POJO property access via dot-notation. • Custom Expression Language: Implemented a full expression system (Lexer, Parser, AST Evaluator) for dynamic evaluation of rule conditions. • YAML DSL: Built YAMLRuleLoader to parse human-readable rule definitions from external configuration files, decoupling logic from code. • Hot Reloading: Created ReloadableRuleEngine using a FileWatcher to detect rule-file changes and atomically reload rule-sets at runtime. • Spring Boot Integration: Developed the nomos-spring-boot-starter with NomosAutoConfiguration for zero-configuration setup and extensibility. • High-Performance Extensibility: Added annotation-based registries (@NomosFunction, @NomosAction) powered by MethodHandles for reflection-free invocation. • Testing & Benchmarking: Implemented comprehensive JUnit tests and JMH benchmarks to ensure correctness and high throughput. Tech: Java 17 · Spring Boot · Gradle (Kotlin DSL) · SnakeYAML · JUnit 5 · JMH

Nomos: An Open Source Lightweight Java & Spri

• Designed and implemented a quantum algorithm tailored for precise edge detection in medical images, enhancing accuracy and processing speed. • Leveraged the IBM Quantum Experience platform for executing the algorithm, ensuring compatibility and scalability for medical imaging applications. • Evaluated and scrutinized the algorithm’s performance, demonstrating its efficacy in rapidly and accurately identifying critical features in medical imagery. • Cultivated expertise in quantum computing methodologies, image processing techniques, programming languages, and data analysis methodologies throughout project engagement. • Investigated the algorithm’s potential applications in various medical imaging contexts, showcasing its potential impact on diagnostics, treatment planning, and healthcare advancements.