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tirthsvora/README.md

Hello 👋, I'm Tirth

My experience centers around developing robust proof-of-concepts in AI/ML and data analysis, conducting machine learning research, designing AI-driven agent systems, and building reliable backends!

🔭 Current Focus

  • 🖥️ I’m currently working at OpenLocus.ai and my work focuses on exploring new technologies and contributing to advancements in AI and Data Analysis.
  • 🔭 I've researched on autonomous agents and their applications in scientific discovery and industry. My work involved developing solutions that use large generative models to improve scientific discovery and problem-solving capabilities.

📚 Authored Papers & Contributions

  • DiscoveryBench: Towards Data-Driven Discovery with Large Language Models - Link
  • Data-driven Discovery with Large Generative Models: Accepted at ICML'24 - Link

Experience

  • I've interned and am joining Apollo Global Management as an Analyst in 2025, where I've worked on developing ETL pipelines and creating real-time monitoring dashboards, (tested and deployed) automated testing of platforms and APIs to reduce admin tasks!
  • I have participated in multiple hackathons and have created projects like Attornify, Transverse, AssessGuard etc.
  • ⚡Fun fact I learn very fast and come up with very unique perspectives on solving problems!

📫 You can can reach me at vora.tirth09@gmail.com

Connect with me:

tiirthvoratiirthvoratirthvoraatirthhvoratirthvora

Languages and Tools:

awscdockerflaskjavakafkakubernetesmysqlpandaspythonscikit_learnspring

tirthhvora

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  1. Data_Extraction_and_NLPData_Extraction_and_NLPPublic

    Automated scraping article text from 100 URLs along with sentiment and readability analysis in each

    Python 1

  2. MLOpsMLOpsPublic

    Jupyter Notebook 1

  3. AttornifyAttornifyPublic

    Jupyter Notebook 1

  4. Ettarra-Sales-Analysis-and-BackendEttarra-Sales-Analysis-and-BackendPublic

    I created this backend in a hackathon where I performed exhaustive analysis of a coffee-chain, and created a backend for sending visualization data to the frontend

  5. Laptop_Price_PredictionLaptop_Price_PredictionPublic

    Jupyter Notebook

  6. Regression-with-DeploymentRegression-with-DeploymentPublic

    I've made this complete end-to-end project with the aim of learning how to deploy a machine learning model. Here I pre-processed, explored and statistically examined the Boston_house_price dataset …

    Jupyter Notebook