Anisha Gajbahar

About

AI/ML Engineer with hands-on experience across machine learning, NLP, computer vision, and generative AI through internships. Published IEEE research on hybrid no-reference image quality assessment and built end-to-end ML applications using Python, Scikit-learn, Streamlit, and Git.

Experience

• Machine Learning Intern
  Unified Mentor
  Jun 2026 – Present
• Artificial Intelligence Intern
  Decode Labs
  Jul 2026 – Aug 2026
• Trainee Engineer
  Globeminds Technology Pvt Ltd
  Jun 2023 – Jul 2023

Education

• Diploma in Information Technology
  Government Polytechnic Pune
  Information Technology · 2022 – 2024
• Bachelor's in Computer Science
  Deccan Education Society
  Computer Science

Skills

• SQL
• Computer Vision
• Python
• Machine Learning
• Prompt Engineering
• Classification
• Feature Engineering
• Matplotlib
• Model Evaluation
• NumPy
• Pandas
• Streamlit
• scikit-learn
• OpenCV
• Natural Language Processing
• LLMs
• XGBoost
• Regression
• Generative AI (ChatGPT, Copilot, Gemini)

Projects

• Offline Resume Builder (Markdown-Based)
  Python, Markdown, Regex, File Handling

  Developed a Python-based Markdown parser to generate formatted resumes offline. Implemented structured input handling for customizable resume sections with lightweight usability.

• Internal Intrusion Detection System
  Python, Machine Learning, Anomaly Detection, Pandas, scikit-learn

  Designed a behavioral-analysis-based intrusion detection system for identifying suspicious activities. Implemented anomaly detection techniques, improving detection efficiency by 40% during testing.

• AI Notes Summarization System
  Python, NLP, NLTK, Pandas, Regular Expressions

  Built an NLP-based text summarization system using Python and preprocessing techniques. Generated concise summaries while preserving contextual meaning.

• Secure Data Transmission Using Blockchain Technology
  Python, SQLite, DBMS, SHA-256 hashing, cryptography

  Built a DBMS-based blockchain simulation for secure messaging and file transfer. Implemented hashing, authentication, encryption, and SQLite logging for secure and traceable communication.

• Saas Customer Churn Prediction Web Application
  Python, Pandas, Scikit-Learn, Streamlit, Git

  Built an end-to-end customer churn prediction system using Logistic Regression with ROC-AUC of 0.84. Performed preprocessing, feature engineering, class imbalance handling, and deployed an interactive prediction dashboard using Streamlit.

• Hybrid No-Reference Image Quality Assessment (NR-IQA)
  Python, OpenCV, XGBoost, HyperIQA, MANIQA

  Developed a hybrid IQA framework integrating BRISQUE, NIQE, PIQE, HyperIQA, and MANIQA. Implemented XGBoost-based dynamic model selection and evaluated using PLCC, SRCC, and RMSE.

Courses & certifications

• AWS Academy Cloud Foundations · AWS Academy · 2026
• AI & Machine Learning · Microsoft · 2026
• Python · Lernx · 2025
• Artificial Intelligence · Codsoft · 2025
• Data Analytics · Deloitte Australia · 2025

📚 Publications

• Adaptive Hybrid Architecture for NR-IQA ↗ · 2026