Research Statement
“My research focuses on autonomous service orchestration across the Edge–Fog–Cloud computing continuum, Edge & Generative AI, and secure 5G/6G network slicing. I design resource-aware optimization frameworks, lightweight industrial acoustic intelligence, and resilient edge systems for safety-critical cyber-physical applications.”
Broad Research Areas
- Edge, Fog & Cloud Computing (The Computing Continuum)
- Edge AI & TinyML
- Generative AI & Foundation Models
- 5G/6G Network Slicing & Infrastructure Security
- Industrial IoT (IIoT) & Cyber-Physical Systems
Research Work and Experience
Recognised Researcher @ Barcelona Supercomputing Center, Spain
Worked as a Recognised Researcher in the Predictable Parallel Computing Group, Computer Science Dept., Barcelona Supercomputing Center. My research work mainly focussed on orchestrating (deployment and monitoring) the workflow on the computing continuum consisting of Edge/Fog and Cloud resources for the realtime/time-senstive applications.
Group: Predictable Parallel Computing - Computer Sciences
Visiting Researcher/Postdoctoral Researcher @ Institute of Computing, University of Campinas, Brazil
As a Visiting Researcher/Postdoctoral Researcher at LRC, UNICAMP, worked on developing the orchestration controller for dynamic deployment of the user requests on multi-level computing architecture. The Video Streaming/VoD requests are handled using the multi-level Edge/Fog-Cloud Computing Architecture to stream videos and thus ensure the viewers’ QoE and QoS.
Supervisor: Prof. Luiz Fernando Bittencourt
Doctoral Researcher @NITK, Surathkal, Karnataka
Doctoral research focused on developing the fog framework on the resources constrained devices using docker containers to host and process the IoT/IIoT service requests. Developed a container-based two-level fog framework and then proposed various multi-objective optimization-based service placement strategies using evolutionary algorithms to place the IoT/IIoT service requests in the fog framework. The fog server-based prototype is developed to analyze and classify the machine’s operating sounds as normal and abnormal and thus monitor the malfunctioning machines based on their operating sounds in the Smart Industry/Industry 4.0 environment. Further, the fog framework is used to analyze the videos at the device level to identify and classify the vehicles, normal and abnormal activities in Smart Surveillance Environments.
Supervisor: Prof. Ram Mohana Reddy Guddeti
Current Rsearch Interests
Computing Continuum & Autonomous Orchestration
- Dynamic Resource & Service Orchestration: Mathematical modeling, multi-objective optimization (GA, RL, heuristic scheduling), and intelligent workload placement across heterogeneous Edge–Fog–Cloud architectures.
- Cloud-Native Edge Deployments: Containerized orchestration frameworks (e.g., KubeEdge, OpenYurt, Docker) for automated management of 5G/6G access and core network functions with deterministic QoS/QoE guarantees.
Edge AI, TinyML & Industrial Intelligence
- Acoustic Anomaly Detection & Condition Monitoring: Lightweight deep learning models leveraging advanced acoustic feature representations (MFCC, GFCC, LPC) for real-time fault diagnostics in Industrial IoT (IIoT).
- On-Device Inference & Data Reduction: Compact neural network architectures optimized for ultra-low latency, energy efficiency, and high-ratio telemetry compression at the network edge.
Generative AI & Distributed Foundation Models
- Edge-Native GenAI & Physical Reasoning: Small Language Models (SLMs) and Vision-Language models tailored for physics-informed reasoning, simulator-state supervision, and synthetic sensor data generation.
- Efficient Distributed Inference: Parameter-efficient fine-tuning (PEFT), model quantization, and collaborative edge-fog inference pipelines for resource-constrained environments.
Network Slicing
- SLA-Driven 5G/6G Network Slicing: Dynamic slice provisioning, isolation, and lifecycle management for mission-critical verticals including Connected/Autonomous Vehicles (V2X), Smart Healthcare, and Industry 4.0.