AI Labs

Pioneering next-generation AI innovations:

The FRIPL AI Lab is a hub of innovation, dedicated to advancing cutting-edge AI algorithms and intelligent solutions. Our research spans multiple AI disciplines, integrating cognitive AI, generative AI, and deep learning to build next-generation, context-aware, and interactive AI systems.

Driving AI excellence across domains:

Our AI Lab focuses on developing human-like reasoning capabilities by harnessing:

Cognitive AI & Generative AI for intelligent decision-making across industries
Large Language Models (LLMs) for advanced natural language understanding
Knowledge Graphs & Graph AI to enhance data-driven insights at scale
3D Dense Point Cloud Processing for precision in spatial computing
Generative Models for Images & Videos to transform visual content generation
Autonomous Intelligent Agents that enable real-time, adaptive automation

Transforming industries with AI:

Finance – AI-driven fraud detection, risk assessment, and market predictions
Telecommunications & Networking – Intelligent automation for seamless connectivity
Urban Planning – AI-powered data analytics for smart city development
Enterprise Applications – AI-driven insights for operational efficiency and automation

Building a smarter, sustainable future with AI:

At FRIPL AI Lab, our team of dedicated researchers and AI experts are pushing the boundaries of innovation. As a key contributor to Fujitsu’s vision, we are committed to leveraging AI for a smarter, sustainable, and connected world.

Why FRIPL AI Lab?

Cutting-edge research in AI, Generative AI, Graph AI, and Computer Vision
Industry-leading expertise in network security, automation, and 3D data analytics
Driving AI transformation across finance, telecom, urban development, and cybersecurity
Commitment to building trustworthy, transparent, and ethical AI solutions

At FRIPL AI Lab, we are pushing the boundaries of Artificial Intelligence (AI), Graph AI, Generative AI, Network AI, 3D Vision, and Conversational AI to develop next-generation solutions. Our research spans large-scale data processing, intelligent automation, and human-AI interaction, enabling breakthroughs across industries such as finance, telecommunications, cybersecurity, urban planning, autonomous systems, and enterprise AI.

A. Graph AI: Unlocking the power of interconnected data

The Graph AI Team at FRIPL is revolutionizing how complex relationships are understood and utilized across social networks, transportation, finance, recommendation systems, and molecular structures.

Key research areas:

Large-Scale Graph Learning – Developing scalable graph representations for billions of nodes and edges, extracting valuable insights efficiently.
Dynamic & Streaming Graphs – Modeling time-evolving graphs for real-time analytics in finance, logistics, and social networks.
Continual Learning – Building adaptive AI models that evolve without forgetting past knowledge.
Explainable AI in Graphs – Enhancing transparency in AI-driven decisions, fostering trustworthy and interpretable AI systems.

B. Network AI: Powering Secure & Intelligent Networks:

Our Network AI Team leverages Generative AI (LLMs), Explainable AI, Trustable AI, and Self-Supervised Learning to redefine network security, automation, and dynamic scheduling.

Key research areas:

Complex Time Series Forecasting – Deciphering spatiotemporal patterns for network congestion detection & mitigation.
AI-Driven Network Security – Using anomaly detection & Generative AI to prevent cyber threats, including DDoS attacks.
Automated Network Management – Optimizing bandwidth allocation, spectrum management, and traffic forecasting.
Network Automation – Deploying AI-powered disaster recovery, self-healing networks, and dynamic reconfiguration.
Root Cause Analysis (RCA) – Interpreting sparse, unstructured log data for proactive issue resolution.

C. Point Cloud 3D Research: Transforming Spatial Intelligence:

The Point Cloud 3D Research Team at FRIPL is leading innovations in urban planning, autonomous navigation, and surveillance through advanced 3D data analysis.

Key Research Areas:

Few-Shot Learning for 3D Object Detection – Enhancing autonomous driving & urban planning with minimal labeled data.
Privacy-Preserving Surveillance – Developing AI-driven, large-scale security solutions that balance public safety and privacy.
AI-Powered Urban Planning Frameworks – Revolutionizing city development through AI-driven spatial analytics & simulations.

D. Graph for Vision: AI-Powered Image & Graph Integration

Our Graph for Vision Team bridges computer vision, generative AI, and multimodal learning, transforming image recognition and AI-assisted decision-making.

Key Research Areas:

Image-to-Graph AI – Advancing human-object interaction detection for smart factories, warehouses, and retail automation.
Graph-to-Image Generation – Using Generative AI to create synthetic visual scenes from structured data.
Vision-Language Understanding – Retrieving scenes from videos & extracting contextual information from documents.
AI Harmonization – Integrating Specialized AI & General AI to optimize real-time decision-making.

E. Applied NEL: Redefining Conversational AI & LLMs

The Applied NEL Team at FRIPL specializes in Conversational AI, Knowledge Graphs, and Large Language Models (LLMs) to develop robust, enterprise-grade AI solutions.

Key Research Areas:

Conversational AI – Developing advanced chatbots & virtual assistants with contextual understanding.
Enterprise AI Applications – Building scalable, AI-powered APIs for seamless enterprise integration.
LLMs with 3D Understanding – Combining language models with 3D data interpretation for augmented reality & robotics applications.

Meet our leadership

Mahesh Chandran

Mahesh Chandran is a multidisciplinary R&D leader with over two decades of experience across industry and academia, specializing in AI, computational science, and applied innovation. As Director of Research at Fujitsu Research India, he leads cutting-edge work in Generative and Cognitive AI, driving breakthroughs across scientific modeling, industrial IoT, and sustainable technologies. A published researcher with 30+ journal papers and four patents, Mahesh combines deep expertise in physics, machine learning, and high-performance computing to build impactful, future-ready solutions.