About me

Hi, I'm Siddhartha Mahajan, a student researcher in IT, Math, and Computational Biology at the Cluster Innovation Centre, University of Delhi. I'm passionate about data-driven research and healthcare advancements.

My work spans developing predictive models for antiseizure medication outcomes, investigating antibody-antigen binding affinities, and analyzing disease networks using SNP data. I also have hands-on experience as a Machine Learning Intern, where I built models to classify YouTube videos using a self-scraped dataset.

What I'm Doing

  • Research icon

    Interdisciplinary Research

    Integrating IT, mathematics, and computational biology to drive innovations in healthcare.

  • Machine Learning icon

    Machine Learning & Data Analysis

    Creating predictive models and data analytics pipelines using advanced ML techniques.

  • Software Development icon

    Software Development

    Building robust software solutions to support research and practical applications.

  • Mentoring icon

    Mentoring & Outreach

    Sharing knowledge and guiding future researchers through mentoring and public speaking.

Current and Past Associations

Resume

Education

  1. Cluster Innovation Centre, University of Delhi

    2021 - 2025 (Ongoing)

    Bachelor of Technology (B.Tech.) in Information Technology, Mathematical Innovations & Computational Biology
    Current CGPA: 8.7
    Relevant Courses: Calculus, DSA/DAA, ODEs/PDEs, Probability, AI-ML, DBMS (SQL), Statistics, Graph Theory, Linear Algebra, In-Silico Biology, Systems Biology, Complex Analysis, Group Theory, Numerical Methods.

Research Experience

  1. Predicting Efficacy of Antiseizure Medication Treatment

    Epilepsy Research, Sep 2024

    Developed predictive models using six ML algorithms (Python, scikit-learn, Pandas) on patient data from North India, achieving over 70% accuracy. DOI: 10.1016/j.eplepsyres.2024.107404

  2. Predicting Binding Affinities in Antibody-Antigen Binding

    Under Prof. Prabal Maiti, IISC

    Employed computational tools such as ChimeraX, Modeller, and GROMACS to simulate molecular interactions and analyze antibody-antigen binding affinities.

  3. Disease-Disease SNP Network Analysis & Community Detection

    Research Project

    Analyzed disease networks using SNP data, built graphs with NetworkX, applied community detection algorithms (Louvain, SLPA), and visualized results with Matplotlib & PyVis.

Work Experience

  1. Machine Learning Intern - Beyond Exams

    May 2022 - November 2022

    Built ML models to classify YouTube videos into educational vs. non-educational categories using a self-scraped dataset. Handled data scraping (YouTube V3 API, BeautifulSoup, Selenium), cleaning, and implemented algorithms in ML.NET (C#).

Projects

  1. Semantic Search Engine

    Streamlit, SentenceTransformers, Huggingface

    Developed a semantic search engine integrating cosine similarity, a Streamlit interface, and SerpApi’s Google Search API for top results.

  2. Chronicles of Alexandria

    Flask, Pinecone, Web Scraping

    Created a documentary library with semantic search capabilities using Pinecone and SentenceTransformers for efficient content retrieval.

  3. AI Adversarial Agent

    PyTorch, TensorFlow

    Developed a web extension employing an adversarial model to cloak images and protect user identity from facial recognition systems.

  4. Data Analyzer with AI

    Flask, Streamlit, Pandas, Matplotlib

    Designed an AI-powered data analyzer that intelligently selects and displays appropriate visualizations for a given dataset.

Volunteering & Mentoring

  1. Mentor/Speaker - DYOD Induction Program

    Jammu University, 20th - 23rd September 2023

    Mentored 40+ students on project development, presentation skills, and innovative thinking at the Design Your Own Degree program.

My Skills

  • Programming Languages
    90%
  • Data Analysis & ML
    90%
  • Software & Tools
    85%
  • Research & Analytical Skills
    90%