"Because apparently running neural networks on hardware that barely has enough RAM is considered fun."
I'm an electronics and robotics engineer who enjoys making hardware do things it was never designed to do.
Most people deploy AI on GPUs.
I deploy it on microcontrollers and then spend three days wondering why I have 12 bytes of SRAM left.
My current work revolves around Embedded AI, Robotics, FPGA acceleration, TinyML, Edge Vision, and Distributed Embedded Systems, where the goal is simple:
Make hardware think before it runs out of memory.
class Sumit:
currently_breaking = [
"STM32",
"ESP32",
"FPGA",
"Raspberry Pi"
]
research = [
"Embedded AI",
"On-device Learning",
"Federated TinyML",
"FPGA Accelerators",
"Computer Vision"
]
hobbies = [
"Reading 1200-page datasheets",
"Optimizing until the compiler gives up",
"Removing printf() to save Flash",
"Finding one missing semicolon after 3 hours"
]
current_status = "Compiling..."
| Project | Description | Tech |
|---|---|---|
| SensiNerveX_STM32 | Federated Learning on STM32 because cloud servers are expensive. | STM32 TinyML Federated Learning |
| SensiNerveX_ESP32 | Teaching an ESP32 to learn new patterns without forgetting the old ones. Humans should learn this too. | ESP32-S3 Embedded AI Continual Learning |
| NanoSplat | Real-time monocular 3D understanding on hardware that definitely shouldn't be doing 3D reconstruction. | Jetson Nano Computer Vision |
| FPGA AI Accelerator | Seeing how much AI fits into programmable logic before timing reports start crying. | Verilog FPGA AI |
| LoRa32T | Secure telemetry because sending plain-text packets in 2026 feels illegal. | ESP32 LoRa |
| uMotion | Motion detection without throwing a neural network at every engineering problem. Mathematics still works. | Embedded C Signal Processing |
Currently exploring:
- 🧠 On-device Learning
- ⚡ FPGA AI Acceleration
- 🤖 TinyML & Edge AI
- 📡 Federated Learning
- 👁️ Embedded Computer Vision
- 🔋 Resource-Constrained Intelligence
I maintain an ORCID researcher profile documenting my published and ongoing research.
- 🧩 Build AI that doesn't need a GPU.
- ⚡ Make microcontrollers learn on their own.
- 🔧 Design hardware that survives outside the lab.
- 🤖 Build robots that don't need cloud permission to think.
- 📖 Reduce the number of tabs containing datasheets. (Currently failing.)
Research Papers ████████░░
Firmware Bugs ██████████
Coffee ██████████
SRAM Available ██░░░░░░░░
Datasheets Open ██████████
Sleep ░░░░░░░░░░
while(true)
{
Learn();
Build();
Break();
Debug();
Repeat();
}"If it compiles on the first try, I'm immediately suspicious."
⚡ Always one compiler warning away from another project.