LOHUM Puts Industry in Charge of India’s Science Push

LOHUM Cleantech Pvt. Ltd has appointed Nobel laureate Konstantin Novoselov to lead a research initiative in advanced materials and cleaner technology, putting a company-backed incubator at the centre of a push to turn scientific work into industrial production. Founder and chief executive Rajat Verma said Wednesday that the initiative will draw on the expertise of India's veteran engineers to lower barriers to setting up manufacturing projects.

Who Sets the Research Agenda

The incubator will develop “products and processes” to bridge the gap between positive laboratory results and scalable manufacturing, Verma said at a New Delhi news conference with Novoselov. It will have 50-80 people and aims to produce five commercially viable technologies each year. The full list of focus areas has yet to be announced; LOHUM said its team is still assessing them, with strategic and critical minerals, nanomaterials and 2D structures, advanced magnetic materials and other emerging technologies among the likely sectors.

LOHUM is expanding beyond material recycling into manufacturing sintered rare-earth magnets and battery components such as cathode active material, according to Verma. The company’s research priorities sit within a larger contest over strategic technologies: the article cites geopolitical uncertainty and the potential weaponization of crucial technologies, as well as China’s 2025 export control order on rare-earth magnets, which disrupted manufacturing around the world in renewable energy, defence, electronics and automobiles.

The spending figures show the scale of the resources behind that contest. India's research and development spending rose to 0.84% of gross domestic product in FY24, from 0.64% in FY21, according to the Department of Science and Technology's Research and Development Statistics 2025-26. China's spending was 2.80% in 2025 and the United States' was 3.44% in 2024.

Novoselov, born in the Soviet Union in 1974, later conducted graphene-related research at the University of Manchester. He argued that research without immediate commercial goals still needs funding. “The US used venture capital for research towards technological advancement, while China used government funding. Every single technology that we see around us was a scientific project some time ago. Developing technology can be more expensive than making it commercial. And that requires some support, whether governmental or venture capital,” he said. The choices on the table, in his account, are funding from governments or capital seeking a return.

Machines, Models and Measurement

Caltech professor and Accelerated Understanding co-founder Anima Anandkumar is developing physical artificial intelligence models to simulate complex phenomena and accelerate scientific discovery. Her San Francisco-based start-up built a model for physics rather than language tasks that handled 5 trillion pieces of data in a single prompt in tests. Anandkumar said she and her husband developed a model that can replace expensive experiments used to test scientific ideas.

“It provides directional feedback to see how to improve upon ideas to make our inventions and discoveries even better,” Anandkumar said. She said language-based models lack “that physical grounding and understanding” and the ability to simulate experiments in a physically valid way.

Her team used simulations to assess a medical catheter designed to reduce fluid backflow and prevent bacterial infection. Fluid flow and wave propagation make it difficult to determine how different triangular shapes inside the catheter affect performance, so the team tested designs through the model before producing them. “But we didn't have to 3D print those because we could simulate what different designs provide and come up with the best design that we believe will work really well in the physical world,” she said. The team then printed and tested a design, which led to a hundredfold reduction in bacterial contamination, according to Anandkumar.

The model uses neural operators, a technology Anandkumar pioneered. Weather agencies have adopted her AI model to predict natural disasters faster through improved modelling; other applications include chip design and cleaner energy sources. Accelerated Understanding is working with chip makers on new designs and physics problems, but Anandkumar declined to name the companies. “Because we try to pack more and more transistors in smaller and smaller spaces, the question is how to lay that out to make sure the physics does not come in the way,” she said.

Recognition and Institutional Gatekeepers

Anandkumar was included among TIME Magazine's 100 most influential AI personalities in 2026. After graduating from IIT Madras, she earned a PhD in electrical engineering at Cornell University and worked with Amazon Web Services (AWS) and Nvidia. She started Accelerated Understanding with her husband, Benedikt Jenik, in early 2024. Anandkumar declined to discuss the company's backers or how much it has raised. She said it has partnerships with computing providers, especially hyperscalers, which supplied hardware clusters to develop and run its model, but declined to identify them.

Separately, 48 researchers from Amrita Vishwa Vidyapeetham appeared in the 2026 update of a global database of top-cited scientists published in the Elsevier Data Repository, according to figures compiled by the university. Seventeen appeared in the career-long category and 44 in the single-year category; 13 appeared in both. The list uses Scopus citation data and a composite score accounting for factors including co-authorship and author positions. Elsevier's database measures citation impact across disciplines, with selection based on researchers ranking among the top 100,000 by the composite score or within the top 2% of their subfields. The rankings recognize researchers through a system built around citations and institutional data; they don't change who controls the labs, companies or funding described here.