Meghna Roy Chowdhury

PhD Student, Electrical & Computer Engineering @ Purdue University

Hello there! I'm Meghna, a PhD student in ECE at Purdue University, focusing on the exciting domain of low-power wearable tech & AI in Healthcare.

My research involves system-level applications combining low-power sensing, communication, and analysis of various biopotential signals. I utilize techniques from Signal Processing, Machine Learning, Deep Learning, and Computer Vision, and also work on data collection and building predictive models.

Currently researching at SPARC Lab, I enjoy blending hardware and software skills to create impactful solutions.

To sum it up: I am a passionate, hands-on, and always-ready-to-learn-and-apply-new-tech kind of individual, seeking opportunities to contribute my best in the domain of low-power wearables tech & AI in Healthcare.

📍 Based in West Lafayette, IN (Boiler Up!) 🚂

🤯 Fascinated by low-power computing & clever algorithms

🧠Health AI Enthusiast | 📷 Amateur Photographer | 🍫 Chocolate Lover

🛠️ Technical Toolkit

A collection of languages, tools, and concepts I work with.

Software and Coding

Python C / C++ Micropython Embedded C MATLAB Ansys HFSS Verilog HTML/CSS/JS

Hardware & Embedded

Microcontrollers (Arduino/NodeMCU/PSoC) FPGA (Artix-7) Raspberry Pi SDR (HackRF, USRP)

Subject Knowledge

Machine Learing Signal Processing Embedded Systems IoT & IoB Biopotential Signals (ECG/EMG/EEG/PPG)

Soft Skills (i know it's not a technical thing, but still)

Great Collaborater Problem Solver Adaptable Accountable Good Time Manager Analytical Thinker

👩‍💻Projects and Publications

Featured Projects

Bringing ideas to life with code and circuits. More on GitHub.

I-HOPE Project Visual

I-HOPE

Predicting college student mental health with high accuracy (91%) using interpretable AI to understand complex behavioral data.

I-HOPE Project Visual

DistNN

Enabling powerful, real-time AI on wearables with extreme energy efficiency (~1000x > GPU) via distributed neural networks.

I-HOPE Project Visual

SSL-SE-EEG

Achieving state-of-the-art EEG analysis accuracy (91% on MindBigData) with less labeled data using a novel Self-Supervised Learning framework.

I-HOPE Project Visual

FlexECG

An ultra-low power (20µW) flexible ECG patch utilizing body heat and Human Body Communication for seamless monitoring.

IDD Simulation Results

Precise Drug Delivery

A novel electronic system using electric fields for accurate, potentially lower-cost Intrathecal Drug Delivery (IDD).

I-HOPE Project Visual

Depth of Anesthesia

Predicting surgical anesthesia depth using Deep Learning on ECG/PPG signals for enhanced real-time patient safety (82% Acc).

Publications

Here are some of my published research findings. More on Google Scholar.

Chowdhury, M. R., Ding, Y. & Sen, S.(2025). 'SSL-SE-EEG: A Framework for Robust Learning from Unlabeled EEG Data with Self-Supervised Learning and Squeeze-Excitation Networks'. In IEEE Engineering in Medicine and Biology Society (EMBC). (Accepted)
Chowdhury, M. R., Xuan, W., Sen, S., Zhao, Y. & Ding, Y. (2025). 'Predicting and Understanding College Student Mental Health with Interpretable Machine Learning'. In IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE). [Link]
Chowdhury, M. R., & Sen, S. (2025). 'Measurement and Analysis of System Parameter Effects on Noise in EEG Systems'. In IEEE International Symposium on Circuits and Systems (ISCAS). (Accepted)
Chowdhury, M. R., Ghosh, A., Bari, M. F., & Sen, S. (2024). 'Leveraging Ultra-Low-Power Wearables Using Distributed Neural Networks'. In IEEE Body Sensor Networks Conference (BSN). [Link]
Bari, M. F., Chowdhury, M. R., & Sen, S. (2023). Long Range Detection of Emanation from HDMI Cables Using CNN and Transfer Learning. In Design, Automation & Test in Europe Conference & Exhibition (DATE) 2023. [Link]
Bari, M. F., Chowdhury, M. R., Chatterjee, B., & Sen, S. (2022). Detection of Rogue Devices using Unintended Near and Far-field Emanations with Spectral and Temporal Signatures. In IEEE MTT-S International Microwave Symposium (IMS) 2022. [Link]
Chowdhury, M. R., Madanu, R., Abbod, M. F., Fan, S. Z., & Shieh, J. S. (2021). Deep learning via ECG and PPG signals for prediction of depth of anesthesia. Biomedical Signal Processing and Control, 68, 102663. [Link]

⏳ Experience Timeline

My journey through research labs and industry roles.

Aug 2021 – Present

Graduate Research Assistant

SPARCLAB, Purdue University

Researching low-power embedded systems, HBC, and hardware security.

Aug 2020 – Aug 2021

Developer - R&I (Analytics & Insights)

TATA CONSULTANCY SERVICES (TCS)

Developed ML solutions for structured & unstructured data.

May 2020 - Jul 2020

Research Intern

YUAN ZE UNIVERSITY, TAIWAN

Focus: Signal processing & time-series analysis using CNNs/LSTMs for ECG and PPG.

Jan 2020 – Apr 2020

Machine Learning Intern

TATA CONSULTANCY SERVICES (TCS)

Focus: Predictive modeling for IoT applications in EV battery life prediction and range estimation.

May 2019 – Jun 2019

Research Intern (SEAL Lab, CSE)

IIT KHARAGPUR

Focus: Hardware security primitives, FPGA implementation and testing.

May 2018 – Jul 2018

Summer Intern (EE Department)

IIT BOMBAY

Focus: Embedded programming, sensor interfacing, cloud communication.

🎓 Education

My academic journey so far.

2014

Grade X (ICSE)

Ebenezer Intl. School
Bangalore, India
Score: 96%
2016

Grade XII (CBSE)

Jaipuriar School
Mumbai, India
Score: 92%
2016 - 2020

B.Tech, ECE

VIT Vellore
Electronics & Comm. Eng.
Vellore, India
CGPA: 9.24 / 10.0
2021 - Present

PhD, ECE

Purdue University
Electrical & Computer Eng.
West Lafayette, IN

💪 Beyond the Lab

When I step away from the screen and soldering iron...

📷Photography

🏊Swimming

🚶Hiking

🧗Bouldering

🏸Badminton

✈️Travel Bug

A Glimpse Through My Lens

More on Instagram. Click photos to enlarge.

Heart shape in sky

Seagull eating

Sunset silhouette

Street motion blur

Navi Mumbai skyline

Crescent moon

Flamingos

Street scene reflection

Howrah Bridge

Landscape view

Myna bird

Painted Stork bird

🤝 Get In Touch

Whether you have questions, ideas for collaboration in low-power tech or AI in healthcare, or just want to chat about research (or photography!), please feel free to reach out!

Email: royc.meghna@gmail.com

Or schedule a quick virtual coffee chat:

Schedule a 30-min Call