Ciao mondo! This is Jagadeesh.
VLSI, Robotics & AI Enthusiast
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
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)_/¯ "
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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
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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.
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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.
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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.
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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
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RAM1KB – A 1KB (1024 x 8-bit) memory module in Verilog with write-once locking for even addresses. Includes a randomized testbench.
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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)
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Designed
image processing algorithms
(e.g., edge detection, geometric & color transforms, noise reduction) in Verilog, utilizinghardware optimized math
techniques to maximize computational efficiency. These algorithms were fine-tuned forlow-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
andperformance 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
onCIFAR-10
, with a focus on making it hardware-friendly
ANAV for Martian Surface Exploration (ISRO IRoC‑U 2025) | Link
Duration: Team-based (ISRO RIG), Ongoing Tools: Jetson Nano | Pixhawk | RealSense D435i | ESP32 (ESP‑Now) | VINS‑Fusion | ROS2
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Built a
<2kg autonomous quadrotor>
forGNSS-denied environments
, capable ofreal-time mapping
,navigation
, andsafe-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
usingVINS-Fusion
onROS2
, achieving<5cm drift
over ~5m; transmitted real-time telemetry using ESP32 modules (ESP‑Now
); autonomously landed onobstacle-free 1.5×1.5m
zones with<15° slopes
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RV32I RTL CPU DESIGN | Link
Duration: Individual, Ongoing
Tools: Verilog (Icarus Verilog) | TL-Verilog (Makerchip)
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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).
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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
andx31
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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.
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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
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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
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
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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