Shivani Shah: Innovator in Industrial Digital Transformation

Shivani Shah is a prominent figure in the field of industrial digital transformation and artificial intelligence. As the Co-founder and CTO of Samp.ai, she is at the forefront of revolutionizing how large industrial facilities are maintained and modernized1. Shah's journey in technology and innovation began with her academic pursuits, culminating in a Ph.D. focused on Machine Learning using Graphs for large Metagenomic datasets1.

Professional Journey and Achievements

Shah's career trajectory showcases her expertise in various technological domains:

• Co-founded Samp.ai in February 2020, developing a SaaS platform for 3D Shared Reality in industrial plants1
• Completed her Ph.D. at CEA, focusing on machine learning and big data applications in metagenomics (2015-2019)1
• Conducted research at LIG - Grenoble Informatics Laboratory, developing interactive visualizations for protein and peptide structural similarities1
• Interned at W3C, working on mobile web browser standards for Indian languages1

Samp.ai: Pioneering Industrial Digital Twins

Under Shah's technical leadership, Samp.ai has made significant strides:

• Developed AI-powered technology to create and update intelligent 3D models of industrial facilities12
• Reduced modification planning time from months to days for industrial sites2
• Secured over 150 client sites in France, including major companies like Suez, Engie, and Veolia2
• Successfully raised €6 million in Series A funding, led by Promus Ventures2

Vision and Future Plans

Shah and her team at Samp.ai are focused on:

• Transforming industrial sites worldwide through real-time updatable digital twins2
• Contributing to safer, more efficient, and sustainable industry practices2
• Expanding their presence in Europe and preparing for entry into the U.S. market2

Expertise and Skills

Shah's diverse skill set includes:

• Machine Learning and AI
• Big Data Analytics
• Computer Vision
• Human-Computer Interaction
• Programming languages: Java, Python, R, and more1

Conclusion: A Visionary in Industrial AI

Shivani Shah's work at Samp.ai is not just about technological innovation; it's about creating practical solutions that address critical challenges in industrial operations. Her vision of using AI and 3D modeling to enhance safety, efficiency, and sustainability in heavy industries positions her as a key player in the ongoing digital transformation of the industrial sector.

Shivani Shah's AI Research in Metagenomics Applications

• Research Focus: Shivani Shah's PhD work centered on applying machine learning, particularly graph-based approaches, to large metagenomic datasets 1. Her research aimed to develop novel computational methods for analyzing complex microbial communities.

• Methodological Approach: Shah utilized graph sparsification techniques and unsupervised machine learning algorithms to process and extract insights from metagenomic sequencing data 9. This approach allowed for more efficient analysis of the vast amounts of genetic information produced by modern sequencing technologies.

• Applications: The methods developed by Shah have potential applications in various areas of metagenomics, including:

  • Microbial diversity assessment in environmental samples
  • Functional annotation of metagenomic sequences
  • Detection of novel genes and enzymes from unculturable microorganisms
  • Analysis of human microbiome data for health and disease studies

• Technological Contributions: Shah's work contributes to advancing the field of computational metagenomics by developing more scalable and interpretable machine learning models for analyzing complex microbial ecosystems 9.

• Broader Impact: By improving the analysis of metagenomic data, Shah's research supports efforts to better understand microbial communities and their roles in environmental and human health, potentially leading to new insights in areas like bioremediation, drug discovery, and microbiome-based diagnostics 7.

Samp's AI-Powered Digital Twin Technology Advances Industrial Site Management

Samp, a French deeptech startup, has secured €6 million in funding to scale up its innovative "Shared Reality" digital twin solution for industrial sites 12. Key advancements include:

• Rapid 3D Modeling: Samp's patented AI and 3D streaming technology generates digital twins of industrial facilities within days, offering a comprehensive and precise 3D vision of infrastructure states 1.

• Data Integration: The platform seamlessly integrates image captures from industrial sites with existing technical data, allowing for fast 3D modeling and contextualizing of equipment information 1.

• Real-Time Updates: Samp's solution enables constant asset monitoring, improving safety and operational efficiency in inspection, maintenance, and construction activities 1.

• Wide Adoption: Already implemented in over 150 industrial sites across France, Samp's technology has been embraced by industry leaders like Engie, SUEZ, and VEOLIA 12.

• Sustainability Focus: The platform accelerates and improves the reliability of industrial sites' transition towards sustainable production, addressing critical challenges in security, resilience, and environmental impact 1.

This funding will support Samp's international expansion, continued R&D efforts, and sales team development to meet growing demand for their transformative digital twin technology 12.