Global Innovators Showcase Breakthrough Technologies at Bengaluru Exhibition

The exhibition highlighted how locally developed ideas are increasingly finding global relevance. From renewable energy systems and circular manufacturing models to artificial intelligence-driven diagnostics, the event underscored the growing role of interdisciplinary innovation in shaping future industries and public services.

Among the key highlights was the work of Venkata Sai Teja Yarlagadda, a U.S.-based research scientist, whose AI-powered tuberculosis diagnostic device drew considerable attention from healthcare professionals and policy observers.
Standing out among the Top 15 innovators, Venkata Sai Teja Yarlagadda presented a novel AI-driven diagnostic device designed to improve tuberculosis (TB) detection, addressing one of the world’s most persistent public health challenges. Tuberculosis remains a leading cause of death globally, particularly in low-resource and high-burden regions where access to rapid and accurate diagnostics is limited.

Yarlagadda’s innovation leverages deep learning and convolutional neural networks (CNNs) to analyze chest X-ray images and automatically identify TB-related abnormalities. By employing transfer learning on large, annotated medical imaging datasets, the system significantly improves diagnostic accuracy while reducing dependence on specialist interpretation.

Yarlagadda’s innovation focuses on improving the accuracy and speed of tuberculosis screening using artificial intelligence. The system analyses chest X-ray images through deep learning models based on convolutional neural networks, enabling automated detection of TB-related abnormalities. By applying transfer learning techniques to large, annotated medical imaging datasets, the device significantly enhances diagnostic precision while reducing dependence on specialist interpretation.

Traditional TB diagnostic methods, such as sputum smear microscopy and conventional radiography, often suffer from delayed results and limited sensitivity. According to evaluation data presented at the exhibition, Yarlagadda’s system demonstrated improved accuracy and a marked reduction in false-negative cases, enabling earlier diagnosis and timely clinical intervention. The technology is designed for rapid screening, making it suitable for deployment in high-volume hospitals as well as resource-constrained settings.

Organisers noted that innovations showcased at the exhibition reflected a broader shift toward impact-driven and ethically responsible technology development. Projects addressed challenges such as industrial decarbonisation, water scarcity, sustainable food processing, and accessible automation for small and medium enterprises.
The exhibition also emphasised collaboration, highlighting how cross-border partnerships and knowledge-sharing are accelerating innovation. Curators stated that the goal was not merely to display finished products, but to present innovation as an evolving process shaped by research, experimentation, and social responsibility.

As the Innovator Meet Tech Exhibition 2025 concluded, participants and visitors alike noted the growing convergence of technology and human need. With healthcare innovations such as Yarlagadda’s AI-driven diagnostic system, the exhibition reaffirmed that purposeful innovation can play a critical role in addressing global public health and development challenges.