an AI Engineer building intelligent, secure deep learning architectures

🎓 ACADEMICS: Institution : Amrita Vishwa Vidyapeetham Degree : B.Tech in Artificial Intelligence & Data Science (Sem 7) CGPA : 8.72 / 10.0 Focus : Graph Neural Networks (GNNs), Threat Detection, Agentic AI

📑 Analysis of Deep and Graph Neural Networks for Enhanced DDoS Attack Detection: A Pathway to Hybrid Models

Mahendran, S., Vignesh, V. S., et al. (IEEE, 2026)

Evaluated Deep Neural Networks (DNNs) and Graph Neural Networks (GNNs) inside a Software-Defined Networking (SDN) framework to capture spatial/topological traffic anomalies, achieving superior accuracy against standard and novel DDoS attack vectors.

📑 An Intelligent Plug-In Playable Orchestration Model that Combines Gen-AI Prompting, RAG and Agentic AI for Efficient Cybersecurity Operations

Mahendran, S., Vignesh, V. S., et al. (Springer Nature, 2026)

Developed a plug-and-play orchestration framework integrating Generative AI prompts, RAG, and Agentic AI workflows to optimize security event management, leveraging Model Context Protocol (MCP) and agent-to-agent interactions.

⚡ Telesto Energy (Singapore - Remote) — Artificial Intelligence Intern

Dec 2025 – March 2026

• Architected a scalable multi-modal RAG system using vector search engines and Neo4j for graph-based multi-hop retrieval.
• Leveraged open-source frameworks to index heterogeneous archival document corpora, enabling rapid semantic search across massive text records.
• Engineered an OpenCV-based document restoration pipeline to remove digital artifacts and improve downstream text extraction accuracy.

AWS Bedrock Neo4j FAISS Redis OpenCV

⚡ InceptAI (Coimbatore - Remote) — Artificial Intelligence Intern

March 2025 – April 2025

• Designed Microsoft Security Copilot plugins with RAG pipelines (DeepSeek R1) for context-aware KQL generation; implemented agentic workflows that measurably reduced SOC incident response time.
• Shipped plugins to production via CI/CD pipelines in collaboration with senior engineers.
• Contributed to AI-powered solution development, collaborating on healthcare chatbots and data analysis tools.

DeepSeek R1 KQL Microsoft Security Copilot Agentic Workflows CI/CD

🛠️ NetSuite -- Network Diagnostic & Utility Suite

Built an end-to-end web suite for automated network tools, socket utilities, and client-side network diagnostics. Engineered modular architecture to handle real-time API queries, response benchmarking, and payload formatting.

TypeScript React REST APIs Diagnostics

🛠️ Real-Time Multimodal Emotion Detection

Designed a real-time big data system to detect facial expressions from video, audio, and text streams using YOLO and ViT. Integrated models using Spark Streaming to pipeline Bronze, Silver, and Gold medallion HDFS data pools.

YOLO ViT NLP Spark Streaming HDFS Scala

🛠️ Music Emotion Recognition using CNN and HuBERT

Developed a deep learning architecture incorporating fine-tuned HuBERT speech embeddings and 2D Convolutional Neural Networks for acoustic feature extraction. Engineered an analytical framework to map raw signals into distinct emotion categories.

Deep Learning Speech Processing HuBERT CNN Acoustics

🛠️ Monte Carlo Simulation in Supply Chain Management

Implemented stochastic modeling using Monte Carlo methods to evaluate disruptions, lead times, and financial risk profiles within a logistics pipeline. Modeled statistical distributions to forecast stockouts and optimize inventory rules.

Stochastic Modeling Python Simulation Risk Analytics

Languages	Deep Learning	Databases & Cloud	Tools & Ops
Python C++ Java TypeScript	PyTorch TensorFlow OpenCV	Neo4j Redis PostgreSQL	AWS Bedrock Docker Git

⚡ Building secure, high-speed neural architectures & agentic platforms.

Code of Conduct · Collaboration · Security