I'm a Masters Student (MASc) in Electrical and Computer Engineering (ECE) at The University of British Columbia. I studied Biomedical Engineering as an Undergrad. I like to work on interesting projects in the areas of ASIC Design, Silicon Photonics and PIC Design, Electronics, Robotics, Integrated Sensing, Wearable Devices, and Machine Learning Tools for Hardware Design Automation (EDA/EPDA) and Simulation.

• 🔭 I’m currently working on designing sensors on Silicon Photonics Chips and Microfluidic Control Systems.
• 📫 How to reach me: [email protected]
• 👯 I’m looking to collaborate on projects at the intersection of Machine Learning, Biomedical Engineering, and PIC/ASIC Hardware Design Automation. I have collaborated on gdsfactory during an internship and collaborated on projects for SiEPIC during my Master's.
• ⚡ Fun fact: I find myself being more drawn to software+AI than to hardware as I grow older. But I want to continue doing open-source hardware and DIY projects :)

• An upcoming analog design project on ASIC Chip Design through IEEE SSCS OSE.
  • Universalization of IC Design from CASS (UNIC-CASS)
  • Notes on Tiny Tapeout from an Analog CMOS Design Perspective.
  • A jupyter-book collection of notes on SystemVerilog and OpenLane + Analog design,
    • Collection of training notes

• GitHub hosted jupyter-book with source repo
  • A collection of deep-dive notes to navigate the learning curve on the topics with advice from experienced people.
  • Ideas to work on Generative techniques for Biosignal Synthesis+Reconstruction.
  • Cool library for Neurophysiological Data Analysis with NeuroKit2
• Additionally,
  • An upcoming project on AI-powered EPDA Tools for SDL (Ideas from ControlNet).
  • Nice concept - RALF: Reinforcement Learning Assisted Automated Analog Layout Design Flow
  • Numerical simulation methods with Finite Difference Time Domain (FDTD) method
    • Opportunities to apply ML/AI in the design and simulation workflow (Should do an internship on this :) )
    • Finite Difference Time Domain solver
    • FDTD 101 Youtube
    • FDTD 101 Flexcompute

• A Low-cost EEG Amplifier for Long Term Neonatal Neurological Disorder Management - Towards AI Powered Infancy Epilepsy Screening.
• The goal is to develop an affordable system that is capable of acquiring and monitoring real-time EEG signal data of neonates, and is aimed towards increasing the efficiency of long term neonatal epilepsy screening.
• The project is currently on-going;
  • The project was taken forward by a group of undergraduates in 2023 as an FYP | Repo | IEEE SMC Paper

• A Low-cost AI Powered Stethoscope for Cardiovascular Disease Management in Resource-Constrained Environments.
• The device is aimed to affordably help increase the screening of congenital heart diseases in the community. It can also be wirelessly utilized in COVID-19 related situations.
• The project won the First Runner-up Award at the 2020 CASS COVID-19 Special Student Design Competition and was presented on the opening day of ISCAS 2020 for the Student Design Competition Session - Presentation | Paper | Paper
• The project is currently on-going;
  • The project was taken forward by a group of undergraduates in 2024 as an FYP | Repo | IEEE ISCAS Paper

• SINDiB Micromouse Project
  • The project was taken forward by a group of undergraduates in 2023, creating the above knowledge base. I hope this project serves as a resource for more micromouse projects to come.
• A talk on Micromouse Robots given by me in 2022 is available here.
• Contact me if you are interested in designing a micromouse; I am hoping to put up a proper repository on the micromouse project in the future after I design a new version of this project.

• I have designed courses, mainly related to Embedded System Design, Embedded Machine Learning and Embedded Product Design for IoT. I will post more information about them here.
• I contributed to the SystemVerilog Short Course on ASIC flow with Synopsys DesignCompiler & IC Compiler.

• I have been interested in developing and improving a course on embedded machine learning. I am working with a team on developing the following demos;
  • Embedded machine learning for speech recognition using Arduino Nano 33 BLE Sense | Repo
  • Embedded machine learning for person detection using Arduino Nano 33 BLE Sense | Repo
  • Embedded machine learning for gesture recognition using Arduino Nano 33 BLE Sense | Repo

• Embedded workshop | Youtube
• ROS workshop | Youtube | Repo 1 2 3
• Quantum Computing workshop | Youtube | Repo
• Generative AI workshop | Youtube | Repo

• Development of a Cost-effective sEMG Sensor System for Controlling Bionic Arms
  • Undergraduate thesis project
  • The goal is to develop a cost-effective solution for individual finger based wireless interaction using sEMG technology, for amputees and all other users. This device is aimed to be a revolutionary new wearable technology with many applications, mainly being for Bionic Hand Control.
  • Published: ICASSP paper | SMC paper
• Bionic Humanoid Arm and EMG recording device using R-Pi 3
  • Created a low-cost device and circuit using AD623 for obtaining Bio-potentials using a R-Pi protoboard for recording EMG Signals. Bionic Hand was completely 3-D printed and developed using nylon strings and servo motors mounted on the arm. This project was awarded a Distinction pass after it was presented as a Self Initiated Innovation project, which was expanded into the FYP under the supervision Dr. Simon Lind Kappel.
• Automated Plant Leaf Disease Detection
  • First project that ever amounted to anything.
  • Used multi-spectral image feeds (NIR/RGB spectra) and implemented transfer learning-based training of CNNs on small datasets of domain-specific images. The product was deployed using a mobile app with edge inference and recognized as a Top Initiative at the National Tech Awards.