I'm Navodita Mathur, a passionate AI enthusiast with a strong foundation in Machine Learning, Computer Vision, and Natural Language Processing. I hold a Master of Science in Information Science from the University of Pittsburgh and a Bachelor of Technology in Information Technology from Mahatma Gandhi Institute of Technology. My professional journey has spanned roles such as AI Research Intern, Junior Machine Learning Engineer, and Web Developer, equipping me with diverse skills in building and fine-tuning models, data analysis, and software development.
- Machine Learning & Data Analysis
- Computer Vision (with applications in remote sensing and biodiversity monitoring)
- Natural Language Processing
- Generative AI
- Database & Software Development
Languages: Python, R, SQL
Frameworks: TensorFlow, PyTorch, Scikit-learn, LangChain
Technologies: Docker, Apache Hadoop, Tableau, Streamlit, Git, MLFlow
- Biodiversity Monitoring using Computer Vision: Leveraged multimodal learning integrating camera traps and bioacoustics for species dataset generation. This ongoing research aims to develop ecological foundation models for remote sensing and biodiversity applications.
- iNaturalist Species Classification: Working on an LLM-powered species classification pipeline with a question-answer format in Streamlit to provide detailed information about identified species.
- Deforestation Detection in the Congo Basin: Developed an end-to-end pipeline using satellite imagery and geospatial analysis to map and track deforestation.
- Flood Extent Mapping in Kenya: Applied remote sensing and geospatial libraries to measure the impact of flooding, aiding in disaster response and planning.
- Farming Recommendation System: Developed a machine learning model predicting optimal crop choices based on environmental inputs, with a web app for dealer registration and product management.
I am driven by the goal of advancing the field of Artificial Intelligence, particularly in the intersection of computer vision, ecology, and life sciences. My focus lies in developing novel algorithms and pushing the boundaries of existing techniques to address real-world challenges like biodiversity monitoring and climate change. In my PhD, I aim to explore the integration of remote sensing, multimodal learning, and bio-inspired algorithms to solve complex ecological problems.
I'm always open to exciting research collaborations and professional opportunities that allow me to contribute to innovative AI applications and make a tangible impact!
Feel free to explore my repositories or reach out for collaborations!