Research Assistant Data Scientist

Mona Esmaeili

Albuquerque, NM, USA LinkedIn +1-425-***-**** Google Scholar

*********@***.***

OBJECTIVE

Motivated and accomplished data scientist with a strong background in machine learning, and deep learning. Seeking a challenging position where I can apply my expertise in developing innovative solutions and contributing to cutting-edge research in the fields of artificial intelligence, data analysis, and computational biology. Dedicated to leveraging advanced techniques and technologies to extract meaningful insights from complex datasets and solve real-world problems. Committed to continuous learning and staying up-to-date with the latest advancements in the field.

WORK EXPERIENCE

University of NEW MEXICO Albuquerque, NM

Research Assistant in Internet of things, Signal Circuits, Health, Machine Learning 09/2019 - Current and Deep learning

● Designed and developed Contact Tracing for COVID-19 using Kalman Filter (KF) and Machine Learning models (Python).

● Developed a classification model for Covid19 from chest X-ray images using deep learning (Python)

● Developed a Deep Reinforcement Learning for Online Latency Workload Offloading in mobile edge computing. (Python, PyTorch)

● Developed a Fuzzy Deep Convolutional Neural Network for detection and classification of Tumors. (Python)

● Designed a new modulation for detecting the cause of failures in analog circuits by using the generative adversarial networks (GAN). (Python, Tensorflow)

Data Scientist-Computational Biologist at the Department of Pathology Albuquerque, NM Graduate Research Assistant (Part-time) 09/2020 – 11/2021

● Applied Deep Learning and Data Mining to Mount Sinai Brain Bank database to identify relevant Autophagy related genes.

● Conducted AI/ML modeling using AWS servers.

● Extracted data from archival from post-mortem brains of individuals with from AD and non-AD to compare herpesvirus load (DNA and viral activity (RNA) and identify host gene QTL that correlates with high activity/load.

● Compared the frequency of QTL in AD and non-AD specimens and used statistical models to determine statistically significant correlations.

Vizzia Technologies Albuquerque, NM

Data Scientist 06/2021 – 05/2022

● Designed and implemented modern applications for Periodic Automatic Replenishment (PAR) to optimize inventory management and avoid excess overstock.

● Predicted the minimum and maximum inventory needed to meet patient demand.

● Developed models to predict PAR level inventory for different seasons, holidays, and years. University of Washington Seattle, WA

Research Assistant (Full-time) 03/2018 – 06/2019

● Developed an artificial intelligence-powered software for conducting conversations and answering questions.

● Cleaned and processed the Amazon(Q,A) dataset and applied TF-IDF

● Applied information retrieval methods such as BM25, Glove Embeddings. Iran University of Science and Technology Tehran, Iran Software Developer (Full-time) 04/2014 – 10/2017

Developed a system to detect epileptic seizures and alert patients to evacuate dangerous places. ACADEMIC EXPERIENCES

University of New Mexico. Albuquerque, NM

Instructor-Teacher Assistant 08/2019 – Current

• Prepare course materials such as syllabi, homework assignments, and handouts.

• Deliver lectures to undergraduate and graduate students on subjects such as Data structure, Advance Networking, Machine Learning and Deep Learning.

• Evaluate and grade students' class work, laboratory assignments, and papers.

• Maintain records of student attendance, grades, and other necessary documentation.

• Supervise undergraduate and graduate student in teaching, internships, and research activities. INTERNSHIPS

Scipher Medicine Company Boston, MA

Data Science 06/2019 – 08/2019

● Developed a classifier to segregates patients with ulcerative colitis (UC) into two groups: responders and non-responders.

● Implemented a batch removal technique on the dataset to mitigate batch effects.

● Applied the Random Forest model through 100 iterations and extracted feature importance.

● Achieved and AUC 0.68 when the model was tested on an independent cohort.

● Wrote and submitted a comprehensive report to Scipher Medicinne company. CERTIFICATES AND AWARDS

Machine Learning (Certificate) Coursera

Supervised Machine Learning: Regression and Classification 2022 TensorFlow (Certificate) Coursera

Getting started with TensorFlow 2 2022

Neural Networks (Certificate) Coursera

Neural Networks and Deep Learning 2022

GAN (Certificate) Coursera

Build Basic Generative Adversarial Networks (GANs) 2022 Learning Algorithm (Certificate) Coursera

Advance Learning Algorithms 2023

Best Presenter in IEEE Conference (Certificate) Seattle, WA Artificial Intelligence and Machine Learning 2022

EDUCATION

University of NEW MEXICO Albuquerque, NM

Research Assistant 09/2019 - Current

● GPA: 4.03/4.00

● Studying Ph.D. of Electrical and Computer Science.

● Thesis Title: “Generative Adversarial Network for Fault Detection” University of Washington Seattle, WA

Research Assistant 03/2018 – 08/2019

● GPA: 3.85/4.00

● Master of Science in Computer Science

● Major: Data Science

SKILLS

Python (Scikit Learn, NumPy, Pandas,,Pytorch, TensorFlow), Java, MATLAB, C, Dr Scheme PHP-MYSQL

State estimation/ Kalman filter/ Object tracking Machine Learning – Deep Learning Computer vision & image processing

Signal Processing

PHP-MYSQL

State estimation/ Kalman filter/ Object tracking Machine Learning – Deep Learning Computer vision & image processing

Signal Processing

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