Teaching
Aiman Darwiche is an instructor at multiple universities, teaching graduate courses in computer & data sciences, business analytics, and information systems in both traditional and online formats.
Research
Aiman Darwiche is an active researcher in the areas of machine learning and predictive analytics with multiple publications.
To get more reserch details, load the research pdf. To get in depth details about the data science projects visit GitHub.
Data Science/Software Engineering
Aiman is a Data Scientist and Software Engineer leading teams to develop predictive models, machine learning algorithms and intelligent software.
To get recent professional details, load the professional pdf. To get in depth details about the data science projects visit GitHub.
Experiences
Aiman has extensive data science, research, software engineering, and database development experiences using Python, R, C#, .NET, and SQL Server. In addition, he has a passion transferring this experience and knowkedge in academic settings through teaching different courses.
University of Cincinnati
Adjunct Instructor teaching graduate courses at Carl H. Lindner College of Business:
- BANA 4143: Data Management for Analytics
- BANA 4090: Forecasting and Risk Analysis
- BANA 6043: Statistical Computing
- BANA 7025: Data Wrangling
- BANA 7042: Statistical Modeling
Compu-House
Chief Data Scientist/Researcher
- Studying ensemble classification to predict the occurrence of medical issues with Python and R utilizing Random Forest, Ada Boost, and XtraTrees Classifier
- Directing and managing a team of Data Scientists and researchers to create prediction models using Python and R
Walden University
Contributing Faculty
- Teaching graduate courses at the College of Management and Technology
- Serving as Doctorate Committee chair and Committee member
Compu-House
Data Science/ML Researcher
- Researched and improved the prediction accuracy of Septic Shock by 12%
- Improved the lead time to predict Septic Shock from 4 hours to 20 hours
Grand Canyon University
Adjunct Instructor
- Teaching online graduate Computer and Data Sciences courses
- Working with Master's student on their final Capstone Projects
Cincinnati Insurance Companies
Software Developer
- Developed, supported, and improved Commercial and Personnel Insurance Rating Applications using C#.
- Managed multiple requests to develop different lines of businesses in parallel.
To get more profile details, load the pdf CV or visit LinkedIn. To get in depth details about the data science projects visit GitHub.
Education
Education is the most powerful weapon which you can use to change the world.
Nelson Mandela
Nova Southeastern University
PhD Computer Science
Dissertation: Machine Learning Methods for Septic Shock Prediction
Johns Hopkins University
Data Science Specialization - through
Regis University
MS Software Engineering
Dissertation: Design Patterns in Mobile Software Development
American University of Beirut
BS with minor in Computer Science
To get more profile details, load the pdf CV or visit LinkedIn. To get in depth details about the data science projects visit GitHub.
Publications
- El-Geneidy, A., Mukherjee, S., & Darwiche, A. (April 2021). Prediction of Sudden Cardiac Death using Ensemble Classifiers. Proceedings of the Future of Information and Communication Conference (FICC) 2021, Vancouver, Canada.
- Darwiche, A., El-Geneidy, A., & Mukherjee, S. (2021). Improving Septic Shock Prediction with AdaBoost and Cox Regression Model. 2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE), Guangzhou, China, pp. 522-527, doi: 10.1109/ICCECE51280.2021.9342457.
- Darwiche, A., & Mukherjee, S. (2018). Machine Learning Methods for Septic Shock Prediction. In 2018 International Conference on Artificial Intelligence and Virtual Reality. New York, NY: ACM. doi: https://doi.org/10.1145/3293663.3293673
Speeches
- Paper Presentation (Virtual), "Improving Septic Shock Prediction with AdaBoost and Cox Regression Model", presented at the IEEE 2021 International Conference on Consumer Electronics and Computer Engineering, Guangzhou, China, January 2021.
- Invited Speaker, "Machine Learning Techniques to Predict the Characteristics of Zeolite", delivered at the 8th International Conference on Smart Materials and Structures, Dublin, Ireland, August 2019.
- Paper Presentation, "Machine Learning Methods for Septic Shock Prediction", presented at the ACM 2018 International Conference on Artificial Intelligence and Virtual Reality, Nagoya, Japan, November 2018.