Abhinav Reddy

Data Science & Artificial Intelligence

Exploring the frontiers of Graph Neural Networks, Deep Learning in Healthcare, and Generative Models

Explore My Work

About Me

Abhinav Reddy

Personal Information

I'm a passionate 3rd-year B.Tech student in Data Science & Artificial Intelligence at IIIT Sri City, with a deep fascination for the intersection of machine learning and real-world applications. My academic journey is driven by a curiosity to explore how AI can solve complex problems in healthcare, neuroscience, and beyond.

Full Name: Abhinav Reddy
Roll Number: S20230030379
Institution: IIIT Sri City
Program: B.Tech in Data Science & AI
Year: 3rd Year (2025)

Education

B.Tech in Data Science & Artificial Intelligence

IIIT Sri City
2023 - 2027 (Expected)

Specialized coursework in machine learning, deep learning, data structures, and algorithms. Focused on developing expertise in Graph Neural Networks, Generative Models, and applications in healthcare and neuroscience.

Relevant Coursework: Data Structures & Algorithms, Machine Learning, Deep Learning, Database Management Systems, Probability & Statistics, Linear Algebra.

Research Interests

Graph Neural Networks

Exploring structural motif learning and graph representations for complex data analysis and knowledge extraction.

Deep Learning in Neuroscience

Applying neural networks to understand brain patterns and develop AI solutions for neurological disorders.

Generative Models

Research on GANs, Autoencoders, and their applications in creating synthetic data and content generation.

Federated Learning

Exploring privacy-preserving machine learning techniques for distributed data environments.

Cloud Computing

Designing intelligent systems leveraging cloud infrastructure for scalable AI solutions.

Edge AI

Developing efficient AI models that can run on edge devices with limited computational resources.

Technical Skills

Programming Languages

  • Python
  • C
  • Java
  • SQL
  • R
  • Rust

Libraries & Frameworks

  • TensorFlow
  • Keras
  • scikit-learn
  • OpenCV
  • PyTorch (Basic)

Tools & Platforms

  • Google Colab
  • Kaggle
  • IntelliJ IDEA
  • Git

Domains

  • Deep Learning
  • Graph AI
  • Generative Models
  • Cloud Computing
  • Data Structures

Projects & Achievements

SMS Classification using SVM

Machine Learning

Applied Support Vector Machine algorithms for text classification to categorize SMS messages as spam or ham. Achieved high accuracy through feature engineering and model optimization.

Code Report

Tree Data Structures in C

Data Structures

Implemented advanced tree data structures including B+ Trees, Red-Black Trees, and 2-4 Trees using array-based logic. Focused on optimization of search, insert, and delete operations.

Code

College Application System

Java, OOP

Developed a modular system for student admission and faculty management using object-oriented principles in Java. Implemented classes for applications, reviews, and administrative functions.

Code

Neural Networks for Plant Disease Detection

Deep Learning

Designed a multi-layer neural network to identify plant diseases from leaf images. Implemented data preprocessing, model training, and evaluation for agricultural analysis applications.

Code Report

Deepfake Talking Head Generator

GANs, Autoencoders

Designed an Autoencoder + GAN-based system for generating realistic talking head videos. Implemented on Google Colab/Kaggle platforms using deep learning frameworks.

Code Demo

Hierarchical Molecular Graph Generation

Graph Neural Networks

Research paper focusing on structural motifs in molecular graphs. Developed novel approaches for generating molecular structures with hierarchical representations.

Paper Slides

Key Achievements

Deep Learning in Neuroscience

Authored a comprehensive 12-page technical report exploring AI applications in brain research and neurological disorder diagnosis.

2023

Graph Neural Networks Presentation

Delivered an insightful seminar covering node features, graph kernels, and embeddings, demonstrating deep understanding of graph-based machine learning.

2023

Dynamic Motif Extraction Research

Leading ongoing research initiative on "Dynamic Motif Extraction with Graph Cellular Automata" exploring novel approaches to pattern recognition in graph data.

2024

Resume & References

Download a complete copy of my resume in PDF format for offline viewing and sharing.

Download Resume

Professional References

Dr. Amilpur Santhosh

Assistant Professor, IIIT Sri City
Email: santhosh@iiits.in

Dr. Abhishek Hazra

Assistant Professor, IIIT Sri City
Email: abhishek@iiits.in

Dr. Annushree Bablani

Assistant Professor, IIIT Sri City
Email: annushree@iiits.in

Faculty Collaboration Topics

Cancer Subtype Classification

Dr. Amilpur Santhosh

Research on applying Graph Neural Networks for precise classification of cancer subtypes using molecular data and patient information.

Federated Learning for UAV Applications

Dr. Abhishek Hazra

Exploring privacy-preserving machine learning techniques for Unmanned Aerial Vehicle systems in distributed environments.

Sentiment Analysis in Medical Applications

Dr. Annushree Bablani

Developing NLP models for analyzing patient sentiment and feedback to improve healthcare services and patient outcomes.

Sequential Recommendation using LLMs

Dr. Rajendra Prasath

Research on leveraging Large Language Models for sequential recommendation systems in e-commerce and content platforms.

Reflections & Personal Statement

My Journey in Data Science & AI

My academic journey in Data Science and Artificial Intelligence has been driven by a fascination with how machine learning can solve complex real-world problems. From my initial projects in basic classification to my current research in Graph Neural Networks, each step has expanded my understanding of what's possible with AI.

What excites me most about this field is its interdisciplinary nature. My work in neuroscience applications has shown me how AI can help us understand the most complex system we know—the human brain. Meanwhile, my research in molecular graphs demonstrates how machine learning can accelerate scientific discovery in chemistry and medicine.

"The true power of AI lies not just in its technical sophistication, but in its ability to address meaningful challenges in healthcare, science, and society."

Looking forward, I aim to continue exploring the frontiers of generative models and federated learning, with a focus on developing AI solutions that are not only technically advanced but also ethically designed and practically applicable. I believe that the future of AI lies in collaborative, interdisciplinary approaches that bring together diverse perspectives and expertise.

As I progress in my academic journey, I'm seeking opportunities to contribute to research that pushes the boundaries of what's possible with AI while maintaining a strong focus on responsible innovation and real-world impact.

Contact & Links

Get In Touch

I'm always interested in connecting with fellow researchers, collaborators, and opportunities in the field of Data Science and AI. Feel free to reach out!

abhinavreddy.g23@iiits.in

IIIT Sri City, Andhra Pradesh, India

linkedin.com/in/abhinav-reddy

github.com/abhinavg-23

kaggle.com/abhinav-reddy

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