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I'm a passionate Data scientist at NASA space administration. I love how machine learning has leveraged our life. Over the past four years after my PhD, I had this great opportunity to work on a variety of exciting projects ranging from deploying and training ML models, analyzing telescope datasets to visializating the findings and reporting them to technical and non-technical audiance. This way I share the joy of having insights driven from the data with others.

▪ Raised $1.1 Million dollars for analyzing data from the US space missions
▪ Led research programs to develop and deploy machine learning models and deep learning techniques
▪ Experienced in simplifying complex problems and collaborating with cross-functional teams to leverage products\

The first programming language I learned in academia was Fortran which I used for doing my class projects in undergrad. However, after I started my PhD, Python became my daily language as it is extremely versatile and it enables implimenting complex tasks such as training classifiers and regressors as well as generate statstical models.

Below is a list of some of the skills that I've gained throughout my 10+ years of experience of working as a research scientist at Arizona State University and then as a data scientist at NASA. As I'm a fond of Python and its packages, I have also created open scource libraries and online tutorials which you could check in the following:

▪ Programming Languages/Tools: Python, Scikit-learn, TensorFlow, Keras, SQL

▪ Data Manipulation/ Visualizations/ Documentation: Pandas, NumPy, SciPy, Matplotlib, Seaborn, Bokeh, Sphinx

▪ ML/ Deep Learning: XGBoost, Random Forest, Support Vector Machine, Convolutional Neural Networks (CNNs), DNNs

▪ Statistics: Bayesian optimization (MCMC), Time series analysis, Predictive/Descriptive statistics

My several years of research and work experience in astrophysics and computer science have provided me with this great opportunity to expert several ML packages, building strong statistical foundation, and learn project management and building high-performance team on several machine learning, deep learning, and natural language processing. I invite you to check out the descriptions at the bottom of this website. My portfolio shows diversity and depth of knowledge in supervised (classification, __regression__and more.

Reddit_Pandemic_Covid_NLP

Methodlology: Binary classification
Algorithims: XGBoost, SVM, RF, kNN
Performance: >96%
Summary: benchmarked several traditional ML models to train a binary classifier to read the Reddit Covid19 Pandemic-related 30,000+ Pandemic-related posts and label their origin.

DNA Sequencing ML Classifier

Methodlology: Multi-class classification
Algorithims: RF, DNN
Performance: >73%
Summary: Accuratly label the DNA 7 family genes

Housing Sales Price Prediction

Methodlology: Regression
Algorithims: LR
Performance: >73%
Summary: Accuratly label the DNA 7 family genes

Americal Sign Language Image Classification

Methodlology: Multi-Class Classification
Algorithims: Conv Neural Network
Performance: >77%
Summary: Built CNN classifier to recognize Americal Sign Language (ASL) alphabets