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General Information
Full Name | Masoud Khani |
Education
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2021 - Present
PhD
University of Wisconsin-Milwaukee
- Currently pursuing a Ph.D. in Biomedical and Health Informatics with a focus on machine learning and data analytics.
- Currently maintaining a GPA of 4.0.
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2020 - 2021
Master of Science in Computer Science
University of Wisconsin-Milwaukee
- Conducted research on medical image segmentation using machine learning techniques, resulting in a thesis titled "Medical Image Segmentation using Machine Learning."
- Graduated with a GPA of 3.9 and received the Outstanding Graduate Student Award in Computer Science.
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2014-2018
Bachelor of Computer Software Engineering
Tehran Azad University
- Conducted research on fall detection in the elderly using machine learning techniques, resulting in a thesis titled "Fall Detection in Elderly with Smartphones via Machine Learning Techniques."
- Graduated with a GPA of 3.5.
Experience
-
2021
Research Assistant
University of Wisconsin Milwaukee - Biomedical Data and Language Processing (BioDLP) Lab
- Analyzed data using machine-learning algorithms, including data mining, natural language processing, and knowledge representation and modeling.
- Implemented a pipeline for preprocessing the Healthcare Cost and Utilization Project (HCUP) dataset to reduce preprocessing wait time by 80%.
- Developed systems to integrate biomedical language processing into industrial applications such as electronic medical records (EMR) data to make accurate disease predictions.
- Built a pipeline to extract data from Froedtert Hospital and Children’s Hospital of Wisconsin and statistically analyzed patients' demographics.
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2021
Project Assistant
University of Wisconsin Milwaukee - Northwestern Mutual Data Science Institute
- Collected and analyzed student enrollment and behavior data for each semester for data science disciplines.
- Developed an open-source repository for data science applications in different disciplines.
PUBLICATIONS
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2023
- Tong, L., Khani, M., Lu, Q., Taylor, B., Osinski, K., Luo, J. (2023). Association between body-mass index, patient characteristics, and obesity-related comorbidities among COVID-19 patients. A prospective cohort study. Obesity Research Clinical Practice, 17(1), 47-57. DOI. 10.1016/j.orcp.2022.12.003
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2023
- Feller, C. N., Adams, J. A., Friedland, D. R., Khani, M., Luo, J., Poetker, D. M. (2023). Impacts of socioeconomic status on dentoalveolar trauma. WMJ, 122(1), 32-37
Awards
-
2020
- Chancellor’s Graduate Student Award ($6000)
FOCUS AREA
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- Utilizing machine learning techniques and optimization methods
- Analyzing the performance of machine learning models using statistical metrics
- Modeling and analyzing features in neural networks
- Analyzing big data using partitioning and approximation algorithms to provide visual representations.
PROGRAMMING SKILLS
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Machine Learning Techniques
- TensorFlow 2.x
- Keras
- Scikit-learn
- PySpark
- Ensemble traditional and pre-trained models
- Transfer Learning
- LSTM
- YOLO
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Languages
- Python 3.x
- R
- Java
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Databases
- MySQL
- PostgreSQL
- SQL Server
- BigQuery
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Data Visualization
- Matplotlib
- Seaborn
- ggplot2
- Tableau
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Big Data
- Spark
- Dask
- Rapids
- Ray
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Cloud Technologies
- AWS EC2
- AWS S3
- Google Colab
- Google Compute Engine
- Google BigQuery.