ASHER JARVIS PINTO

Robotics and AI Engineering Undergraduate

⚲ Karnataka, India

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About Me

I have expertise in developing AI systems, neural networks, and data-driven solutions.
My work focuses on data analysis, ML model tuning and deployment.
I'm currently exploring backend programming using nodeJS, Postman and SQL.

I enjoy research in Deep Learning, Image Processing and LLMs.
On the casual side of things I like Illustrating on both traditional and digital mediums
and also have an interest in learning new languages.

Programming and Development

Python MySQL JavaScript React C

AIML and Data Science

Scikit-Learn TensorFlow Pandas NumPy Keras Matplotlib

Robotics

Arduino Sensor Fusion Control Systems MATLAB Simulink WPLSoft

Other Tools

Git GitHub Jupyter Notebook Linux Google Colab

Experience

June 2025 - July 2025

Project Intern

Regional Remote Sensing Centre, RRSC-South, ISRO Bangalore

Annotated 2000+ images for object detection in Plastic Waste Classification.
Compared and contrasted several ML models, heavily focusing on Faster R-CNN and YOLOv8 models. Achieved 83% accuracy with YOLOv8n, proving optimal for deployment.
Enabled fast, lightweight, and accurate detection for real-time environmental monitoring.

June 2024 - July 2024

Research Intern

Indian Institute of Science (IISc), Bangalore

Gained hands-on experience in chemical process analysis through practical work with Batch Reactors and GC-MS instrumentation.
Conducted over 3 literature reviews to identify key chemical indicators, and collected, cleaned, and fine-tuned more than 5 experimental datasets
Applied both traditional ML algorithms (Linear Regression, SVM, Random Forest) and deep learning models (MLP, CNN) for prediction and classification tasks, achieving up to 85% accuracy and reducing preprocessing time by 30%
Focused on identifying compound concentrations, reaction yields, and anomaly detection in chemical outputs.

2022 - 2023

Project Intern

NMAM Institute of Technology, Nitte

During my internship on the project 3DSCAPE, I led the development of a user-friendly GUI that improved task completion time by 30% and enhanced user experience.
I followed intuitive design principles and contributed to over 250 lines of backend code, assisting with testing and integration

Projects

SIR Model Prediction

This Project Visualizes the performance of a trained MLP model on SIR simulation data, highlighting prediction accuracy for susceptible (S), infected (I), and recovered (R) compartments.

Python Deep Learning Data Science SIR Model Simulation

GitHub Jupyter Notebook

AQI Prediction Using MLP

This project applies a Multilayer Perceptron (MLP) Regressor to predict Air Quality Index (AQI) based on pollutant data collected from Indian cities.
The model is trained using the city_day.csv dataset, which contains daily air pollution readings along with AQI values

Python Deep Learning Regression MLP

GitHub

AQI Prediction using RBFNN

This project applies a Radial Basis Function Neural Network (RBFNN) to predict the Air Quality Index (AQI) based on pollutant data collected from Indian cities.
The model is trained using the city_day.csv dataset, which contains daily air pollution readings along with AQI values.

Python Deep Learning Custom Neural Network RBFNN

GitHub

CI-FAKE CNN Image Classifier

This project applies a Convolutional Neural Network to predict Real vs. AI-synthesized Images using the CIFAKE dataset.
The model is trained with a MobileNetV2 base model.

Deep Learning MobileNetV2 Classifier

GitHub

2-DOF Forward Kinematics

As part of my Kinematics and Dynamics of Robots course, I worked with MATLAB and Simulink to simulate the forward kinematics of a 2-DOF robotic arm.
Using built-in blocks and the Transform Tree, I visualized joint motion and extracted the end-effector’s position in 3D space.

MATLAB Simulink Kinematics

GitHub

Graphical User Interface (GUI)

I designed the GUI in Figma, applying core UI/UX principles to ensure an intuitive and visually appealing user experience.
The initial background artwork was created in Procreate, adding a custom, hand-crafted aesthetic to the interface.

Figma Tkinter UI/UX

GitHub Figma

Voice Analysis with MATLAB

As part of my Consumer Electronics course, I worked with MATLAB to analyze a voice file and extract features such as Pitch, Amplitude, Timbre and SNR ratio.
It further classifies the voice signal into one of four moods: Happy, Sad, Stressed and Calm.

MATLAB Signal Processing

Portfolio Website

This is my personalized portfolio website.
It reflects my work in AI, Robotics and Programming.
Projects, Roles and Skills are displayed in a clean and interactive website.

HTML CSS JavaScript

GitHub