Prof. Mayank Shrivastava, Department of Electronic Systems Engineering and Prof. Sridharan Devarajan receive Swarnajayanti Fellowship Award 2020-2021. Click here for the details of award announcement.
Prof. Mayank Shrivastava, received the fellowship for his “outstanding contributions in the broad field of engineering sciences”. Prof Shrivastava broadly works on applications of emerging materials like Gallium Nitride (GaN), atomically thin two-dimensional materials like Graphene and TMDCs, in electronic and electro-optic devices working closer to its fundamental limits (like the ability to handle extreme powers, ability to work at THz like ultra-high frequencies, or ability to compute information in unconventional ways). Currently, his group is developing few-atom thick neuromorphic circuits (ICs), GaN-based ultra-high-power devices with high reliability, and devices/circuits for operation at THz frequencies. Prof Shrivastava is also one of the co-founders of a GaN manufacturing start-up named AGNIT Semiconductors Pvt. Ltd. Prof Shrivastava’s work has resulted in over 150 peer-reviewed publications and 50 patents. Most of these patents are either licensed by semiconductor companies or are in use in their products. As part of this fellowship, his group will be working on novel devices emulating brain like (computational) behaviour.
Sridharan Devarajan, Associate Professor in the Centre for Neuroscience and Associate faculty at Computer Science and Automation, has received the Swarnajayanti Fellowship in the Life Science category. Sridharan’s research focuses on understanding the neural basis of selective attention and decision making. His lab studies these, and other, high-level cognitive phenomena in human participants using non-invasive approaches. They employ a range of experimental techniques, including behavioral psychophysics, computational modeling, neuroimaging (fMRI/EEG), and magnetic/electrical brain stimulation (TMS/tACS). A second, emerging area of research in his lab involves applying artificial intelligence (AI) algorithms, including deep learning, for understanding brain mechanisms of attention, in healthy individuals, and its decline, in neurodegenerative disorders. For the Swarnajayanti fellowship, Sridharan and his team will work on deciphering causal mechanisms of visual attention in the human brain. As part of this proposal, they plan to develop novel brain-machine interface technologies for training human attention, with potential applications in managing and treating attention disorders.
