New Delhi: To encourage its young, ignited students to transform knowledge into tangible products at an early stage of their career, IIT Delhi is running two internal research schemes for them since 2016. The schemes run by the Institute’s Industrial Research and Development (IRD) wing are known as Students Startup Action Programme and Discover &Learn (1-2-3-4).
Under both the schemes, a seed grant is given to the selected students through their faculty mentors, providing the students an opportunity to use scientific and technical methodologies to solve practical problems faced by society.
The Students Startup Action Programme seeks to engage IIT Delhi’s undergraduate student groups in startup actions by providing a supportive environment in recognition, initial seed grant, and expert advice.
“Learning to Transform Knowledge to Products” is the key objective of the scheme where in the selected student teams are given a seed grant of Rs. 2 Lakh per year.
‘Learning by Research’ is the goal of the other scheme known as Discover & Learn (1-2-3- 4), run by IIT Delhi for its students. Under this scheme, a group of 4 students each from 1st, 2nd, 3rd, 4th year of ongoing B.Tech/ 5th year (for Dual degree/Integrated degree) or M.Tech. programme may propose a project under the guidance of a faculty mentor. When the final year student graduates, a new first year student joins the team and the projects continue in a relay mode.
Since the time the schemes were launched, 18 projects under IRD Students Startup Action Programme involving about 40 students and 32 projects under Discover & Learn (1-2-3-4) involving about 130 students are in progress in various research areas of national interest at IIT Delhi.
Under the two schemes, some very innovative and promising technologies have been developed, viz.,
(i) SUXMA Pvt. Ltd. – Developed a point of care device (Fig.1) for early-stage diagnosis of sub-clinical mastitis in dairy animals.
(ii) Flexmotiv – A former incubated startup at IIT Delhi developed Flexmo, an all-terrain, slipresistant crutch (Fig.2) for the disabled and elderly.
(iii) CYRAN AI Solutions – Prototyped edge-AI semiconductor hardware primitives for security applications.
(iv) Vecros Technologies Pvt. Ltd. – Devised a computer vision-powered drone (Fig. 3) with a server-based cloud app to monitor and scale the drone operations for industrial inspections.
(v) Silov Solutions Pvt. Ltd. – Invented a DC home solution and Modular Smart Electric Vehicle Charger (Fig.4)
Speaking about the two schemes, Prof. V. Ramgopal Rao, Director, IIT Delhi said, “To enhance research aptitude among its undergraduate & graduate student community and increase learning by research, we had introduced these two schemes at IIT Delhi in 2016. These schemes are designed to expose students to research at a very early stage in their careers, to provide them opportunities to work in interdisciplinary teams and to help them identify societal problems and develop solutions to them in a time bound manner. In a team effort, what matters is not how good you are, rather, how good you are to the team. Such learnings can happen only outside the classroom environment and while working on real life problems that cut across disciplinary boundaries. I am happy to see that, what we started as experimental schemes five years ago, are bearing fruit and helping the society and the careers of these students. We plan to scale up these initiatives further.”
Under the Students Startup Action Programme, the following projects have been sponsored by the Institute in 2021: (a) Blockchain Implementation of Health Electronic Records (HER),
(b) Spirited AI, (c) Develop energy-efficient permanent magnets and switched reluctance motors for two-wheeler electronic vehicles (EVs).
Under the Discover and Learn (1-2-3-4) scheme, this year IIT Delhi will support the following projects: (a) On-line, Wide-range, Low-cost Sensor for Biomass Concentration, (b) Control and Data Acquisition for Cold Atom Quantum Technology, (c) Managing safety at construction sites using digital technology, (d) Develop an application for semantic tagging of video sequences for stochastic modeling of reactive systems, (e) Digitization in Healthcare.