Experienced Machine (Deep Learning) Learning Specialist with a demonstrated history of working in the statistics, computer vision, and bioinformatics. Data Science Machine Learning Engineering Software Engineer [email protected] CORE COMPETENCIES: ● Fluency in Python, R, SQL, etc. ● ML model development (Computer Vision, NLP) ● Analytical Skills. ● Statistical analysis. ● Software engineering. ● Ph.D. in Bioinformatics ● MA in Applied Statistics. ACCOMPLISHMENTS: â–  Published multiple papers across different disciplines: education, biochemistry, computer science, and statistics. â–  Improved machine learning model performance of more than 5x as measured by accuracy and recall by integrating a video frame data-filtering pipeline and a two-output transfer learning model with CNN and LSTM. â–  Built a statistical base model for an estimate of reference correcting values for protein and surpassed the state-of-the-art performance as measured by reference error below +/- 0.22 ppm at 90% confidence interval. (State of the art is around 1ppm.) â–  Accomplished a state-of-the-art cancer detection and type classification performance as measured by the accuracy of >97% and the false positive/ negative rates of <0.2% by using transfer learning approach. Please contact me at ☏ (857) 209-1002 with any data science, machine learning, deep learning, and software engineering opportunities. ©