system_boot.exe
> Initializing portfolio...
> Loading core modules...
> Starting developer environment...
> Compiling portfolio components...
0%

About Me

Hey there! I’m Aditya, a curious coder, AI enthusiast, and full-time tech explorer, currently studying Computer Science (AI & ML) at VIT.

I’m passionate about turning ideas into reality through code — whether that’s building innovative machine learning models, developing full-stack web apps, or experimenting with cybersecurity and custom language models just for the thrill of it. From deepfake detectors to GPT-powered job agents, I’ve dabbled in a variety of exciting projects (and yes, I actually enjoy debugging!).

When I’m not deep into code, you’ll likely find me chasing new project ideas, diving into the latest deep learning research, or competing in hackathons (I’ve earned a few accolades in national competitions, too!).

I’m always looking to learn, build, and collaborate. If you’re into AI, clean code, or ambitious tech projects, I’m sure we’ll get along great.

Let’s create something awesome together!

Skills

Educational Experience

Real Life Experience

  • Programming Languages: Python, C, C++, Java, HTML, CSS, MATLAB
  • Machine Learning & Data Science: Scikit-learn, Logistic Regression, SVM, Random Forest, Gradient Boosting, XGBoost, LightGBM, K-Means, DBSCAN, PCA, t-SNE, Decision Trees, Naïve Bayes, KNN, Lasso, Ridge, SVR, Isolation Forest, One-Class SVM, Hyperparameter Tuning, Cross-Validation, Model Evaluation, Feature Engineering, Dimensionality Reduction
  • Deep Learning & Generative AI: TensorFlow, Keras, PyTorch, Transformers, Hugging Face, LSTMs, GRUs, CNNs, Diffusion Models, BERT, GPT, Stable Diffusion, LoRA, Attention Mechanisms, Transfer Learning, Model Fine-Tuning, Tokenization, Prompt Engineering
  • Data Analysis & Visualization: NumPy, Pandas, Matplotlib, Seaborn, SciPy, Plotly
  • Cybersecurity: hashlib, pefile, Wireshark, Basic Pen-testing, Computer Networks
  • Soft Skills: Time Management, Technical Communication, Analytical Thinking, Team Leadership, Curiosity
  • Languages: English, Hindi, Telugu, Elementary French
  • Feb 2024 - March 2024
    Cybersecurity based internship at The Red Users
  • 2024 – 2025
    TrojaNix - IIT Madras Malware Analysis Hackathon (Finalist)
    • Trained ML and DL models for malware classification, achieving ~98% detection accuracy.
    • Analyzed large malware datasets, refining feature extraction for better detection.
  • 2024 – 2025
    SafeSurf Junior - MP Police Cyber Safety Awareness Hackathon (3rd Place)
    • Developed a browser extension to filter harmful content for children, reducing exposure by ~90%.
    • Implemented an automated alert portal to notify law enforcement of potential violations.
    • Led a team of developers and coordinated end-to-end implementation.
  • 2016 – 2018
    International Robotics Competition (Group Leader)
    • Led a five-member team to design and build competitive robotics models; placed in the top 10 out of 150+ teams.
    • Managed task distribution and ensured timely completion for international showcases.
  • 2023 - 2027
    Vellore Institute of Technology CGPA: 8.04
    I’m currently a Sophomore at Vellore Institute of Technology, pursuing a Bachelor of Technology in Computer Science with a specialization in Artificial Intelligence and Machine Learning.
  • 2021 - 2023
    High Schooling at Excellencia Junior College 95.0%
    During my time at Excellencia Junior College, I built a solid foundation in mathematics, which played a crucial role in shaping my understanding of complex algorithms and problem-solving techniques. My focus on subjects like calculus, algebra, and statistics sparked my interest in data science and machine learning. This academic experience not only strengthened my quantitative skills but also prepared me for advanced studies in AI & ML.
  • 2019 - 2021
    Middle Schooling from Shantiketan Vidyalaya 94%
    During the 2019-2020 academic period, I engaged in a diverse range of activities that contributed significantly to my personal and academic growth.

What I do

GenAI projects

I explore the creative side of AI by working with generative models that produce text, images, and more. My projects involve leveraging state-of-the-art architectures like transformers and diffusion models to push the boundaries of what machines can create. I’m passionate about using GenAI to solve unique challenges and inspire innovation across domains.

Learn more

Machine Learning

I specialize in building robust machine learning models to solve real-world problems. My experience spans supervised and unsupervised learning, model evaluation, and feature engineering. I enjoy experimenting with new algorithms and optimizing solutions for accuracy and efficiency.

Learn more

Deep Learning

I leverage deep learning to tackle complex problems using neural networks and advanced architectures. My expertise includes building and fine-tuning models for tasks like image recognition, natural language processing, and generative AI. I enjoy exploring the latest research and applying state-of-the-art techniques to deliver impactful solutions.

Learn more

My Work

Pygame Map Generator

This is a little idea I got while thinking about applications of LLMs in game development, where we could use them to rapidly change our environment.

RoadVision

An AI-powered web application designed to detect and recognize license plates from images. It can identify speeding violations by comparing timestamps from multiple camera points and stores all data with visual proof for verification.

Zuck your very own AI hacker buddy

A cybersecurity-focused, Gemini based Agent. This project provides an interactive terminal interface for cybersecurity and system administration tasks on Linux systems.

Info Finder

Privacy-first app for local text/URL summarization and Q&A using Google's Gemma 3. Offers secure scraping, content chunking, and browser/CLI access.

Student Performance Analysis

This project analyzes various factors that influence student academic performance. The goal is to understand what impacts student success by examining relationships between grades and different aspects of students' lives and backgrounds.

Efficient MNIST Classifier using tf

This project implements and compares different Convolutional Neural Network (CNN) architectures for classifying fashion items from the Fashion MNIST dataset.

My GitHub Activity

GitHub Stats

0

Total Commits

0

Public Repos

0

Total Stars

0

Pull Requests

Recent Activity

My Resume

Download

Contact Me

telikicherlaadityasasidhar@gmail.com

+91 7428564847

Copyright © 2024 Aditya - All Rights Reserved.