Founders of some of the startups incubated by IIT Madras attend the World IP Day programme on campus Sourced by the Telegraph
The last financial year has been a landmark one for the startup ecosystem at the Indian Institute of Technology Madras. In its 13th year, the IIT-M Incubation Cell crossed the 500-startup mark, reaching a total portfolio of 567 startups. The portfolio is collectively valued at over ₹74,100 crore based on latest funding rounds, and includes two unicorns. A unicorn startup is privately owned and worth $1 billion. This year also marked the first IPO offering from IIT-MIC’s portfolio; Ather Energy, founded by IIT-M alumni and incubated by IIT-MIC in 2013, has now become a publicly-listed company.
The cell incubated 112 startups this year, the second year it supported more than a 100 new companies. The newly incubated startups span a wide range of sectors, including manufacturing, robotics, automotive, batteries, defence, aerospace, AI, machine learning, quantum technologies, analytics, fintech, healthtech, agritech, biotech, climate technologies, IoT and cyber-physical systems. Over 60 per cent of the startups do not have IIT-M alumni as founders, demonstrating IIT-MIC’s pan-India reach.
Meanwhile, IIT Madras continued its strong innovation momentum, filing 431 patents during the year, translating research into real-world impact. Of the patents filed, 79 were international ones. The patents were in areas such as AI/ML, quantum technologies, semiconductors, 5G/6G, robotics, advanced manufacturing, sustainable energy systems, photonics, blockchain, AR/VR and biomedical imaging.
Prof. V. Kamakoti, director of IIT-Madras who had set the goal of 100 startups a year in 2024 and one patent a day in 2023, shared the inspiring news with students, faculty, researchers and startup founders during the World IP Day celebrations (in pic) held on campus on April 24.
Adulteration check
Researchers at the National Institute of Technology, or NIT, Rourkela have patented a system that can quickly detect and measure adulteration in spices and other food items. It combines Fourier Transform Infrared spectroscopy with advanced machine learning to deliver accurate results.
In India, food and spice adulteration poses serious health and economic risks. Traditional methods to detect food adulteration — such as chromatography or molecular techniques — are resource-intensive and results take a long time. They are therefore not suitable for rapid, routine testing. The NIT researchers — assistant professor Sushil Kumar Singh, the late Poonam Singha and graduate student Rishabh Goyal (left in pic) from food process engineering — set out to address these limitations.
The new system is quick, cost-effective and suitable for real-time deployment in quality control labs and processing units. FTIR spectroscopy is used to identify organic materials by measuring how they absorb infrared light. During food checks, the new system collects these patterns and processes them using machine learning models. These models look at patterns in the sample to detect abnormalities. Unlike conventional methods, the new technology also measures the level of adulteration in seconds. This is essential for food processing industries and regulatory bodies that need require precise measurements to ensure compliance and maintain quality.