AI & Intelligent Systems
LLMs, RAG, agentic workflows, on-device ML, inference optimization, and AI-assisted engineering.
Applied R&D across artificial intelligence, embedded systems, automotive platforms, cloud infrastructure, systems performance, and emerging computing.
Zenova focuses on technically demanding problems that span device software, intelligent applications, connected platforms, and system-level reliability.
LLMs, RAG, agentic workflows, on-device ML, inference optimization, and AI-assisted engineering.
C/C++, Rust, Linux, firmware, IPC, device services, diagnostics, and constrained-system design.
Android Automotive, AOSP, HAL integration, CAN, BLE, telematics, infotainment, and platform services.
Google Cloud, Firebase, APIs, OTA workflows, observability, backend integration, and connected-device architecture.
Concurrency, race conditions, deadlocks, memory behavior, latency analysis, profiling, and reliability engineering.
Quantum ML, QCNN experimentation, edge intelligence, hybrid architectures, and AI-assisted software development.
Research themes connect practical engineering with new methods in AI, embedded computing, automotive software, and quantum machine learning.
Architecture research around local inference, machine interfaces, hardware integration, diagnostics, OTA, secure backend communication, and cloud-assisted reasoning.
HAL integration, connectivity, system services, performance, audio, and platform reliability.
Exploring quantum-assisted classification and hybrid classical/quantum workflows.
From low-level execution and device integration to cloud services and AI workflows.
Technical writing focused on practical system design and emerging computing approaches.
Explore Zenova's engineering and research work across embedded platforms, intelligent systems, automotive software, and connected cloud architectures.