Skip to content
View Mummanajagadeesh's full-sized avatar
🤖
Focusing
🤖
Focusing

Highlights

  • Pro

Organizations

@cARMa360

Block or report Mummanajagadeesh

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
Mummanajagadeesh/README.md

Ciao mondo! This is Jagadeesh.

Portfolio Portfolio LinkedIn Instagram Discord GitHub Email

YouTube CLID Duolingo Google Play

  • VLSI, Robotics & AI Enthusiast
  • rocket icon Always learning — check out my blog
  • I'm currently working on few hardware-focused projects
  • Pursuing Electronics and Communication Engineering
  • From National Institute of Technology Calicut
  • How to reach me: Carrier Pigeons 😉
  • Pronouns: he/him
  • Hobbies: Speedcubing, Movies, Blogging
  • Fun fact: I'm Batman



About ME

Hey , I'm Jagadeesh—a Robotics, AI & VLSI hardware enthusiast passionate about building at the intersection of digital logic and intelligent systems.
I enjoy bringing algorithms to silicon, exploring digital design and hardware acceleration for machine learning and image processing, and collaborating with like-minded innovators.

MY Key Interests:

  • VLSI Design: Analog Circuits & Digital Design
  • Neural Networks & Image Processing in HW/SW
  • Embedded Programming (C, C++, Python)
  • Microcontrollers & Electronics
  • Computer Vision, Sensor Fusion
  • Robotics, AMR Path Planning & Navigation

Feel free to check out my projects here, and if you’re interested in collaborating or discussing hardware, AI, or robotics, let’s connect!

Featured Projects | All Projects

(Click sections below to expand)

Verilog HDL Toolkit for Image Processing and Pattern Recognition | Link

" I tried to ImProVe, but NeVer really did — so I MOVe-d on ¯\_(ツ)_/¯ "



ImProVe GitHub repository card in light mode: Image processing algorithms ImProVe GitHub repository card in dark mode: Image processing algorithms NeVer GitHub repository card in light mode: Verilog-based neural network NeVer GitHub repository card in dark mode: Verilog-based neural network

ImProVe – IMage PROcessing using VErilog: A collection of image processing algorithms implemented in Verilog, including geometric transformations, color space conversions, and other foundational operations.

NeVer – NEural NEtwork on VERilog: A hardware-implemented multi-layer perceptron (MLP) neural network in Verilog for character recognition using EMNIST and MNIST datasets.


MOVe – Math Ops in VErilog

CORDIC Algorithm GitHub repository card in light mode: Trigonometric and root functions CORDIC Algorithm GitHub repository card in dark mode: Trigonometric and root functions Systolic Array Matrix Multiplication GitHub repository card in light mode: Hardware-optimized matrix multiplication Systolic Array Matrix Multiplication GitHub repository card in dark mode: Hardware-optimized matrix multiplication
ImProVe Repo Card (light) ImProVe Repo Card (dark)

  • CORDIC Algorithm – Implements Coordinate Rotation Digital Computer (CORDIC) algorithms in Verilog for efficient hardware-based calculation of sine, cosine, tangent, square root, magnitude, and more.

  • Systolic Array Matrix Multiplication – Verilog implementation of matrix multiplication using systolic arrays to enable parallel computation and hardware-level performance optimization. Each processing element leverages a Multiply-Accumulate (MAC) unit for core operations.

  • Multiply-Accumulate Unit – The MAC unit uses Booth’s algorithm for efficient signed multiplication and a Kogge-Stone adder for fast, parallel addition. Booth reduces operation count by encoding the multiplier, while Kogge-Stone ensures low-latency summation through parallel carry computation. Together, they enable compute-heavy multiply-accumulate operations in a compact and optimized form.

  • Posit Arithmetic (Python) – Currently using fixed-point arithmetic; considering Posit as an alternative to IEEE 754 for better precision and dynamic range. Still working through the trade-off.


Storage and Buffer Modules

  • RAM1KB – A 1KB (1024 x 8-bit) memory module in Verilog with write-once locking for even addresses. Includes a randomized testbench.

  • FIFO Buffer – Not started. Planned as a synchronous FIFO with fixed depth, single clock domain, and standard full/empty flag logic.


Duration: Individual, Ongoing
Tools: Verilog (Icarus Verilog, Xilinx Vivado) | Python (OpenCV, NumPy, Tkinter) | Scripting (TCL, Perl)

  • Designed image processing algorithms (e.g., edge detection, geometric & color transforms, noise reduction) in Verilog, utilizing hardware optimized math techniques to maximize computational efficiency. These algorithms were fine-tuned for low-latency preprocessing in embedded vision SoCs.

  • Implemented a 64-bit 3-layer perceptron (MLP 784-256-128-62, ~242k params) for Extended-MNIST Character Recognition (62 classes, ∼124k samples) using an FSM-controlled neural network in Verilog. This implementation achieved >90% training accuracy (>75% simulation accuracy) with ~1.5s inference latency (in simulation). A full end-to-end preprocessing and inference workflow was developed.

  • Automated model inference and performance metric evaluation via Tcl/Perl scripts (executing Python and Icarus Verilog commands). Additionally, a real-time Tkinter GUI was created for test user input.

  • Now working on a lightweight CNN accelerator for image classification on CIFAR-10, with a focus on making it hardware-friendly

ANAV for Martian Surface Exploration (ISRO IRoC‑U 2025) | Link



ImProVe Repo Card (light) ImProVe Repo Card (dark)

Duration: Team-based (ISRO RIG), Ongoing Tools: Jetson Nano | Pixhawk | RealSense D435i | ESP32 (ESP‑Now) | VINS‑Fusion | ROS2

  • Built a <2kg autonomous quadrotor> for GNSS-denied environments, capable of real-time mapping, navigation, and safe-zone detection with zero manual intervention; Jetson Nano was used for onboard compute and Pixhawk handled flight control.

  • Calibrated ESCs and implemented embedded power distribution via BEC module to ensure stable regulation for compute/sensing; integrated barometer and external optical flow sensor with Pixhawk for redundancy in low-texture or drifting conditions.

  • Fused stereo-IMU data from Intel RealSense D435i using VINS-Fusion on ROS2, achieving <5cm drift over ~5m; transmitted real-time telemetry using ESP32 modules (ESP‑Now); autonomously landed on obstacle-free 1.5×1.5m zones with <15° slopes.

RV32I RTL CPU DESIGN | Link



ImProVe Repo Card (light) ImProVe Repo Card (dark)

Duration: Individual, Ongoing
Tools: Verilog (Icarus Verilog) | TL-Verilog (Makerchip)

  • Implemented a fully synthesizable RV32I RISC-V core in TL-Verilog with a single-stage pipeline, supporting all base integer instructions and immediate formats (I, S, B, U, J).

  • Developed a test program summing integers 1 to 9, verified correct ALU operations, branching, and control flow within 50 simulation cycles, with pass/fail status stored in registers x30 and x31.

  • Designed a 32-register file with dual-read and single-write ports, enforcing write-disable on register x0, and integrated instruction decode logic handling opcode, funct3, and funct7 fields.

  • Implemented comprehensive ALU supporting arithmetic, logic, shifts, and comparisons, with immediate extraction and flexible program counter update logic including branch and jump target calculation.

  • Enabled simulation and debugging via Makerchip integration using m4+cpu_viz(), with waveform visualization and automated test validation through register monitoring.

I2C & SPI Protocol FSMs in Verilog | Link



SPI Protocol in Verilog (light mode) SPI Protocol in Verilog (dark mode) I2C Protocol in Verilog (light mode) I2C Protocol in Verilog (dark mode)


Designed I2C with a single-master, multi-slave configuration supporting clock stretching and configurable delays; SPI supports modes 0–3 via CPOL/CPHA, performs single 8-bit full-duplex transfers, and allows clock frequency scaling through a divider

Device Modeling using Sentaurus TCAD | Link



ImProVe Repo Card (light) ImProVe Repo Card (dark)

Designed and simulated semiconductor structures (N-resistor, PN diode, NMOS) using Sentaurus TCAD; explored effects of doping, geometry, and physical models through process setup, simulation scripting, and visual analysis of internal device behavior

RU83C – Rubik’S Cube Solving Robot | Link



RUBEC Repo Card (light) RUBEC Repo Card (dark) V-RU81K5CU83 Repo Card (light) V-RU81K5CU83 Repo Card (dark)

A vision-guided, algorithm-driven robot that solves the Rubik’s Cube with precision using Kociemba’s two-phase algorithm for optimal move sequences, developed in Unity3D with C# scripting



Tools and Technologies

Python C Programming C++ Java Git Linux Ubuntu MATLAB Simulink ThingSpeak Wokwi Arduino Raspberry Pi ESP32 ROS2 Webots Gazebo CoppeliaSim OpenCV NumPy Matplotlib Pandas Fusion 360 SolidWorks Blender Unity Vivado Icarus Verilog

GitHub Stats

GitHub Views Total repos

mummanajagadeesh trophies (light) mummanajagadeesh trophies (dark)

Stats (light) Streak (light) Top Languages (light)

Stats (dark) Streak (dark) Top Languages (dark)

RndmQuoteGen()

Motivational Quote (light)

Motivational Quote (dark)

Pinned Loading

  1. digital-inverter digital-inverter Public

    RTL-to-GDSII using OpenLANE and SKY130A PDK on Google Colab

  2. gpbot-w gpbot-w Public

    This 4-wheeled robot is equipped with GPS, IMU, LiDAR, Distance Sensors, and a 2-DOF camera (using linear and rotary actuators). It detects objects using computer vision, avoids obstacles, and navi…

    C++ 2 1

  3. Mummanajagadeesh.github.io Mummanajagadeesh.github.io Public

    Personal portfolio and blog site built with Hugo, hosted on GitHub Pages

    HTML 1

  4. aws-deepracer-rl-models aws-deepracer-rl-models Public

    Collection of trained reinforcement learning models for autonomous car racing on AWS DeepRacer

    Python

  5. robotrix-2k25 robotrix-2k25 Public

    Basket the Ball – A robotics project built during the 24-hour IEEE Robotrix 2K25 Hackathon by NITK

    Python 1

  6. ORIGO2K25 ORIGO2K25 Public

    Virtual handout and website for ORIGO 2025 — the annual robotics workshop hosted at NIT Calicut

    HTML 2