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SH

Sai Hareeka

B.Tech CSE (AI/ML) student · Aspiring AI/ML Engineer

Hyderabad, Telangana, India

@sai_hareeka

0 followers

🎓 B.Tech in Computer Science Engineering (Artificial Intelligence & Machine Learning) at Institute of Aeronautical Engineering · Graduating 2028

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About

AI/ML engineering student with a strong foundation in Python, Java, machine learning, and data analysis. Has hands-on experience building AI-powered applications and conducting computer vision and vision-language model experiments.

Education

  • B.Tech in Computer Science Engineering (Artificial Intelligence & Machine Learning)
    Institute of Aeronautical Engineering
    Artificial Intelligence and Machine Learning · Sep 2024 – 2028
  • Intermediate
    Gauthami Junior College
    2022 – 2024
  • SSC
    Narayana High School
    2022 – 2022

Skills

1 to 2 years 1 to 2 years A year or two of steady use.
Python Matplotlib
6 to 12 months 6 to 12 months Most of a year behind them.
Java
3 to 6 months 3 to 6 months A few months of practice with it.
SQL OpenCV Regression
<3 months <3 months Just getting started - under three months. This is also what shows when a level has not been set.
NumPy Flask Pandas Tf-Idf FastAPI PyTorch Seaborn JavaScript Clustering scikit-learn Classification Chrome Extensions Predictive Modeling Vision-Language Models API Integration Understanding

Tools / apps / platforms

<3 months <3 months Just getting started - under three months. This is also what shows when a level has not been set.
Git GitHub VS Code Hugging Face Jupyter Notebook

Projects

  • Dark Pattern Detector
    Chrome Extension, Flask, TF-IDF, SGDClassifier

    Built a Chrome Extension that detects potentially manipulative webpage text using a machine learning classification pipeline. Developed a Flask REST API with text preprocessing, TF-IDF feature extraction, and an SGDClassifier for binary dark-pattern detection.

  • Grounded-VLM
    YOLOv8, BLIP-base, PyTorch, Hugging Face Transformers, Ultralytics, OpenCV, NumPy, Pandas, Matplotlib

    Lightweight VLM for Grounded Prompting reproducible ablation study on object coverage in smart environments. Evaluated object coverage, semantic relationships, contextual understanding, and computational trade-offs using a curated COCO 2017 subset.

  • TRANA
    FastAPI, IBM Granite

    Built an AI-driven safety platform combining real-time risk analysis, emergency response, and personalized navigation. Developed REST APIs using FastAPI for user data, training modules, and risk analytics. Integrated IBM Granite for predictive risk assessment and intelligent recommendations.

Courses & certifications

  • Full Stack Web Development Workshop · IIT Hyderabad · 2026
  • Data Structures and Algorithms Using Java – An Interactive Way · Infosys Springboard · 2025

🏆 Achievements & awards

  • Hack Defence

    Top 1,000 / 3,000 teams

  • IndiaAI Impact Gen-AI Hackathon 2025 · 2025

    Participated in hackathon

  • Hack With AI · 2026

    KLH Bachupally ACM Student Chapter

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