👋 Hi there! I am Data Scientist with a PhD in Astrophysics and over 8 years of experience in developing innovative machine learning solutions, particularly in time series analysis, deep learning, and signal processing.
🔭 My research has focused on the detection and characterization of nascent planets, with published works on planet detection techniques using advanced time series analysis and statistical methods.
👨💻 I'm proficient in Python, Scikit-learn, Keras, TensorFlow, and have significant experience in data wrangling, signal processing, dynamic time warping (DTW), Gaussian Process modelling, and Bayesian optimization.
🚀 I enjoy tackling complex data problems, translating research into deployable solutions, and working with cross-functional teams to drive AI innovation.
- Programming Languages: Python, R
- Machine Learning Frameworks: TensorFlow, Keras, Scikit-learn
- Data Manipulation & Analysis: Pandas, NumPy, SQL/MySQL, Excel
- Time Series Analysis: Dynamic Time Warping (DTW), Fourier Analysis, Gaussian Processes, Bayesian Optimization
- Deep Learning: CNNs, RNNs, LSTMs, Time Series and Image Classification, Forecasting
- Development Tools: Git, GitHub
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Deep Learning for Chest X-ray Image Classification
- A deep learning project using convolutional neural networks (CNN) for classifying chest X-ray images.
- View Project
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Planet Detection using Time Series Analysis
- Detection limit of nascent planets in the presence of stellar spot activity using statistical methods.
- View Project
- Modeling bisectors using cross-correlation functions to illustrate the effect of Doppler shifts.
- https://github.com/rajeevzar/bisector_modelling_CITAU
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Time Series Forecasting using LSTM
- LSTM-based model for time series forecasting.
- View Project
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Earth Environment Analysis by country
- In this project, I utilized environmental data from NASA Earthdata (https://search.earthdata.nasa.gov/search) to develop a codebase that enables users to analyze environmental data for different countries.
- The code categorizes and classifies the data into three levels—Good, Moderate, and Severe—based on predefined thresholds, providing valuable insights into the environmental health and performance of each country.
- We can plot time series data to observe the trends in environmental indicators over time, helping to assess the amelioration or deterioration of environmental conditions by country.
- View Project
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Detecting Planets Around Young Stars Using Time Series Analysis
Link to paper -
Other Publications
Link to paper
Feel free to reach out if you'd like to collaborate on AI projects or discuss any exciting opportunities in data science and machine learning.
- 📧 Email: rajeevmnck@gmail.com
- 🔗 LinkedIn: https://www.linkedin.com/in/rajeev-manick-ph-d-a3284b44/