Machine Learning Image Processing

SKILLS and QUALIFICATIONS

RELEVANT EXPERIENCE

RELEVANT COURSEWORKS

PROJECTS

Faria Jahin

Phone: 605-***-**** Brookings, South Dakota

*****.********@*****.*** https://www.linkedin.com/in/faria-jahin281998/ Recent Master's graduate in Electrical Engineering with expertise in statistical models, Python libraries, satellite image processing, satellite

radiometric calibration, and machine learning models. Strong analytical and problem-solving skills, with experience in data analysis and modeling, as well as hands-on experience with sensors and imaging systems. Masters in Electrical Engineering Expected: Spring,2023 South Dakota State University

B. Sc. in Mathematics September,2020

Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Bangladesh

• Skilled in Python, C/C++, MATLAB, ENVI, R, SQL, and SAS.

• Knowledgeable in Electrical Engineering Sciences: Remote Sensing, Image Processing, Signal Processing, Control System, Artificial Intelligence.

• Proficient in Statistical Analysis, Regression Models, Time Series Models and Data Assimilation.

• Have strong communication skill and can maintain excellent interaction with peoples. Graduate Research Assistant, South Dakota State University, August 2021 till now

• Conducted research in satellite image processing and radiometric calibration

• Developed and implemented machine learning models for data analysis and image processing, using Python and popular libraries such as TensorFlow and Scikit-learn.

• Assisted in the design and testing of sensors and imaging systems, Developed and wrote python scripts for data pre- processing, model training, and evaluation.

• Worked on the production of radiative transfer models like ROLO using python for the retrieval of atmospheric aerosol properties from sun-photometer measurements. Internship, Branstation 23, Bangladesh, March 2019-July 2020

• Worked on developing and implementing statistical models for predictive maintenance of industrial equipment, utilizing regression analysis and machine learning techniques.

• Assisted in the design and testing of sensors for industrial applications.

• Conducted data analysis and provided recommendations for process improvements based on statistical models

• Developed machine learning models to optimize sensor data collection and processing. Advanced Image Processing, Image Processing, Statistical Methods, Time Series Analysis, Optical Sensors, Statistical Programming, Seminar-Uncertainty Analysis, Seminar-Remote Sensing. Landsat Calibration App, South Dakota State University, 2021

• Developed a Python-based application to calibrate Landsat 7 and 8 satellite imagery using radiometric and atmospheric correction techniques.

• Utilized machine learning models to improve the accuracy of the calibration process.

• Implemented a user-friendly interface to facilitate the use of the app by remote sensing experts and non-experts. Geospatial Data Mining, South Dakota State University, 2023

• Worked on a project to mine geospatial data using Python and popular libraries such as GeoPandas and Rasterio

• Developed and implemented machine learning models for spatial data analysis and pattern recognition.

• Utilized data visualization techniques to present the results and insights from the analysis. Satellite Atmospheric Correction, South Dakota State University, 2022

• Worked on a project to correct atmospheric effects on satellite imagery using statistical regression techniques and dark object subtraction in MATLAB.

• Developed and implemented an algorithm to improve the accuracy of the atmospheric correction process.

• Evaluated the performance of the algorithm using ground-truth data and compared it with existing methods. EDUCATION

SUMMARY

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