Darshit Mehta

I am passionate about advancing knowledge in physical and biomedical sciences through high-quality research and tool development. Self-motivated professional with exceptional quantitative skills and creative problem-solving abilities. My CV can be found here. You can reach me at contact@dmehta.info or at my LinkedIn profile. I am currently an Automation Engineer at Ginkgo Bioworks, Inc. 

PhD dissertation

In my PhD, I was focused on developing novel technologies for chemical sensing, which is an inherently hard problem because of the extremely large number of different chemicals and the presence of noise in the environment in terms of other chemicals, humidity, temperature variation. This situation is magnified when chemical sensing has to be carried out in hazardous environment as in the case of bomb detection. As a potential solution, I (in collaboration with Dr. Raman's Lab) explored the robust olfactory system of an insect like the locust for detecting chemicals at extremely low concentrations. Towards that end, I developed miniature bioelectronics that can read out different signals (eg. neural signals from the brain and the antenna, behavioral signatures) from the locust for detection and identification of chemical compounds in the environment. The size and weight of any recording setup needs to be thoroughly minimized to have minimal impact on locust flight dynamics. The current state-of-the-art neural recording techniques are power-intensive and they either need batteries, which make them too bulky for insects, or they have to maintain a continuous telemetry link to an external power source which restricts the mobility of the organism. In my dissertation, I explored algorithmic and device based approaches for overcoming the limitation of current neural activity recording-technologies in terms of energy efficiency and longevity. 

A full copy of my dissertation can be found here.

List of publications:

Journal

1. D. Mehta, K. Aono, and S. Chakrabartty, “A self-powered analog sensor-data-logging device based on Fowler-Nordheim dynamical systems,” Nature Communications, vol. 11, no. 1, 2020.

2. D. Saha, D. Mehta, E. Altan, R. Chandak, M. Traner, R. Lo, P. Gupta, S. Singamaneni, S. Chakrabartty, and B. Raman, “Explosive sensing with insect-based biorobots,” Biosensors and Bioelectronics: X, vol. 6, p. 100050, 2020.

3. A. Gangopadhyay, D. Mehta, and S. Chakrabartty, “A spiking neuron and population model based on the growth transform dynamical system,” Frontiers in Neuroscience, vol. 14, p. 425, 2020.

4. D. Mehta, M. Rahman, K. Aono, and S. Chakrabartty, “An adaptive synaptic array using Fowler-Nordheim Dynamic Analog Memory,” Nature Communications, vol. 13, no. 1, 2022.

Conference

1. K. Barri, Q. Zhang, D. Mehta, S. Chakrabartty, R. E. Debski, and A. H. Alavi, “An implantable, battery-free sensing system for monitoring of spinal fusion,” in Health Monitoring of Structural and Biological Systems XV, vol. 11593, p. 115930Z, International Society for Optics and Photonics, 2021.

2. D. Mehta, B. Raman, and S. Chakrabartty, “Differential Fowler-Nordheim tunneling dynamical system for attojoule sensing and recording,” in 2019 IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1–5, IEEE, 2019.

3. D. Mehta, L. Zhou, K. Aono, and S. Chakrabartty, “Self-powered sensing and time-stamping of tampering events,” in 2018 IEEE 61st International Midwest Symposium on Circuits and Systems (MWSCAS), pp. 968–971, IEEE, 2018.

4. D. Mehta, E. Altan, R. Chandak, B. Raman, and S. Chakrabartty, “Behaving cyborg locusts for standoff chemical sensing,” in 2017 IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1–4, IEEE, 2017.