I am a dedicated Ph.D. Scholar at IIITD in New Delhi, India, with a profound passion for research. My focus lies at the intersection of artificial intelligence and mental health, where I am committed to making a difference. In my interdisciplinary journey, I harness physiological data from wearable devices to develop robust predictive models for mental health assessment. I work with deep learning models and I'm continually exploring weakly supervised algorithms to glean insights into mental well-being in diverse, real-world scenarios with limited labeled data. My overarching goal is to contribute to the holistic well-being of individuals through cutting-edge technology and pioneering research.
Research Interest: Human Centered AI, TinyML, Wearables, Mental Health
- Email: firstname.lastname@example.org
- City: New Delhi, India
Deep Learning, Machine Learning, HCAI
Tiny ML India Organizing Team, Student Volunteer: HCI and Friends, AISS (Sumer school of Explainable AI), Program Chair: AutoMLPerSys 2024 (Co-located with PERCOM).
I'm currently pursuing Ph.D.at IIITD, India, under the guidance of Prof. Pushpendra Singh, IIITD, India, and Prof. Mohan Kumar, RIT, USA. I work on "Wearable AI for Mental Health". Before joining IIITD, I worked as an Embedded Software Engineer towards developing solutions for Industrial Automation and Automobiles Industry.
Started in August 2021
Doctor of Philosophy
Indraprastha Institute of Information Technology, New Delhi, India
I am pursuing PhD in Department of Computer Science and Engineering. My thesis is directed towards interdisciplinary research at the intersection of Wearables , Efficient AI and mental health monitoring, management and diagnosis. I am looking into developing robust AI algorithms for better mental health support. I am working with Biosignals and Behavorial data. My present works revolves around the biasness in self-reports and I am exploring Weakly supervised learning methods.
Post Graduate Diploma in Embedded Systems Design
2018 - 2019
Centre for Development of Advanced Computing (C-DAC), ACTS, Pune, India
This course has helped me learn more about Embedded Systems, a unique field where engineers need to have sound knowledge in hardware and software design. And this is what I have gained out of this Course, An understanding of writing software for hardware.
Bachelor of Technology
2014 - 2018
Institute of Engineering and Technology, Dr. Ram Mnohar Lohia, Awadh University, U.P, India
Electronics and Communication Engineering.
Embedded Devices and Intelligent Systems Lab, TCS Research
- This internship was on Platform Aware neural architecture search for embedded devices.
- I have contributed in benchmarking for Tiny DNNs generation using Hardware aware NAS for the task of single lead ECG classification in wearables.
- I have conducted a State-of-the-Art survey on NAS techniques for various task like image classification and object detection.
Embedded Systems Engineer (R & D)
2020 - 2021
Lohia Mechatronik, Pune, India
- Developing Bare-Metal Embedded Software for Thickness Gauging Systems.
- Involved in integrating various new sensor technologies to final product.
- Involved in Research and Development for overall product design.
- Involved in Motion Control Applications for precision measurement.
Embedded Software Engineer
2019 - 2020
KPIT Technologies, Pune, India
- Worked in Requirement Analysis for Communication and Diagnostic Stack of Classic AUTOSAR.
- Deriving Verification Criteria and Software level Requirements.
- Model based Design for development of SWC's for Electric Power Assisted Steering.
- MIL Testing for new Software components.
- IEEE PERCOM, 2023
- This study demonstrates the applicability of Neural Architecture Search (NAS) in producing compact yet highly precise multi-objective models for the classification of ECG signals.