I am an Electrical Engineer, graduated from the Indian Institute of Technology Palakkad in 2020. I am currently working as a Researcher at Tata Research Development and Design Centre. My research interest lies in Bio-Signal Processing, Brain-Computer Interface, and Deep Learning.
I enjoy learning new skills, reading, listening to music, and connecting with people.
A glimpse of my work can be found here. I hope you enjoy your visit.
Currently part of Behavioral, Business and Social Sciences research group studying human behavior.
Developed a Multimodal Deception Detection system that can detect if a person is innocent or guilty based on eye-tracking data. The project was in collaboration with Temasek Labs, under the guidance of Prof. Eng Siong. Various attributes were extracted from the raw data and a classifier was designed to make the prediction.
Worked on various modes of wired communication, Ethernet, and UART. Incorporated GMII Communication for packet decoding project, improvising the communication system for more speed and throughput. Also, implemented C-based hardware programming using a tool flow kit called Chips 2.0.
Designed a Machine Learning based Defect Detection application using convolutional neural networks. Also, ported the application to an FPGA for better speed and accuracy.
I pursued my Bachelor's from IIT Palakkad majoring in Electrical Engineering. In my academic life, I did many project and courses which have built up my interest in Brain-Computer Interface and Deep Learning.
12th Grade, PCM in ISC Board (2015 - 2016) 10th Grade, PCM in ICSE Board (2013 - 2014)
The project started at Nanyang Technological University as a part of Temasek Labs, wherein a person needs to be classified as guilty or innocent based on several psychological signals. In the initial phase, eye features were used and an accuracy of 99.2% was achieved.
EOG(Electrooculogram) based virtual keyboard can assist people with motor neuron disease to communicate effectively. EOG signals were extracted using ECG electrodes attached around the eyes. The signals were filtered using an array of filters and digitized using Arduino.
A Heart Rate Monitoring System is developed using the Infrared PPG (Plethysmograph) sensor. The signals were filtered and processed using Arduino and Matlab.
Developed an assistive communication device for paralyzed and speech-impaired patients. Assisted a sixty-three-year-old fully paralyzed and speech-impaired patient in communicating her thoughts and needs to her family. The accomplishment was featured in The Times of India, December 16, 2019.
Made it to the Quarterfinals of the challenge in designing a Smart Wheelchair which can be used by paralyzed people in moving around comfortably. The wheelchair can be operated using eye signals. The contest was anchored by NSRCEL, Indian Institute of Management, Bangalore (IIMB) and supported by MyGov.