Shaymaa Khater
Brambleton,USA
Summary
Experienced data science professional with a passion for driving innovation and making a meaningful impact. Demonstrated expertise in research, with a track record of publications in reputable international journals and conferences. Skilled in developing advanced machine learning and deep learning models, computer vision, natural language processing (NLP), large language models (LLM), recommendation systems, and predictive modeling. Proven ability to effectively handle large datasets, both structured and unstructured, while delivering impactful data visualization solutions.
Overview
15
15
years of professional experience
Work History
PhD Principal Data Scientist
Mosaic ATM
12.2023 - 03.2025
- Developed and deployed machine learning solutions to enhance predictive analytics and operational efficiency, leveraging automated workflows , cloud-based infrastructures, and advanced modeling techniques.
- Developed AI-powered solutions using Large Language Models (LLMs), including Retrieval-Augmented Generation (RAG) and agent-based systems, to address real-world challenges. Applied NLP and LLMs to analyze extensive exemptions and waivers documents, extracting actionable insights to enhance decision-making.
- Developed a delay estimation model for flights and implemented robust pipelines using MLFlow.
- Developed a deep learning-based computer vision model to estimate path loss in Air-Ground communication systems, improving prediction accuracy and operational efficiency."
PhD Senior Data Scientist
Mosaic ATM
11.2019 - 11.2023
- Designed and implemented predictive modeling solutions with production pipelines, utilizing deep learning, MLflow, and Kedro frameworks to enhance aviation analytics and operational efficiency.
- Improved industrial operations through fault detection, predictive maintenance, and computer vision applications.
- Analyzed large datasets to identify trends and patterns in customer behaviors, and to drive business decisions.
- Developed a loan risk scoring and alerting model to to improve accuracy and operational efficiency in retail banking.
- Lead research and development in pet genetics, leveraging genetic data to explore potential diagnostic applications for various pet health conditions.
- Designed data pipelines, and cloud-based solutions with platforms like Azure and AWS to ensure seamless integration and deployment
Senior Data Scientist- Consultant
The College Board
02.2019 - 05.2019
- Developed predictive models and learning algorithms for exam scoring level prediction, incorporating feature engineering to enhance the model's performance and flexibility.
Senior Data Scientist
Chelfie – Solebrity Inc
05.2017 - 07.2018
- Designed and utilized Deep Learning frameworks as Caffe & Tensorflow for building image-based object detection , visual similarity search. and recommendation system for Chelfie app (http://www.chelfieapp.com/).
- Developed statistical analysis models on large datasets using Python and Bokeh for visualization, enabling insights into user activities, shopping behaviors, and retailer data analysis.
- Mentored and coached junior data scientists on machine learning development projects, providing technical support, best practices, and hands-on experience in model development and deployment.
- Collaborated with cross-functional teams to test, refine, and implement real-time models, ensuring seamless integration and operational efficiency.
Data Scientist
Chelfie – Solebrity Inc
01.2016 - 05.2017
- Designed and implemented NLP-driven automation for fashion product tagging using text processing with NLTK. Developed classification and clustering models to categorize unlabeled data, enhancing data organization and retrieval.
PhD Researcher
College of Engineering, Virginia Tech University
08.2010 - 12.2015
- Research & develop Machine Learning models for problems in the area of online Social Networks.
- Proposed a new dynamic recommendation system model that provides better customized social network (Twitter) content to the user.
- Presented TrendFusion, an innovative model that analyzes the geographical trending topics propagation, predicts the localized diffusion of trends in social networks and recommends the most interesting trends to the user.
Education
Ph.D - Computer Science and Applications
Virginia Tech
Virginia12.2015
M. Sc. - Computer Science
Ain Shams University
Egypt06.2006
B. Sc. - Computer Science
Ain Shams University
Egypt05.2000
Skills
- Python
- Mongo DB
- Microsoft SQL Server
- Oracle
- PostGres
- MySql
- OrientDB
- Tensorflow
- Pytorch
- Caffe
- Kedro
- Amazon EC2
- AWS
- Azure
- MlFlow
- Matplotlib
- Bokeh
- Shapely
- Weka
- R
- Git
- Linux
- Windows
Community Service
- Program Committee Member, 14th ACS/IEEE International Conference on Computer Systems and Applications - AICCSA, 2017
- Program Committee Member, 13th ACS/IEEE International Conference on Computer Systems and Applications - AICCSA, 2016
Publications
- F. Wieland, S. Khater, J. Rebollo, D. Matolak and Z. Afroze, "Predicting AAM Path Loss through Neural Networks and Statistical Modeling," in IEEE Integrated Communication, Navigation, and Surveillance (I- CNS) Conference, Dulles, VA, April 2024.
- J. Rebollo, S. Khater and F. Wieland, "Using Sector Complexity Metrics to Predict Sector Capacity," 2023 IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC), Barcelona, Spain, 2023
- S.Khater, J. Rebollo, William J. Coupe “A Recursive Multi-step Machine Learning Approach for Airport Configuration Prediction”. AIAA Conference, August 2021
- Personalized Recommendation for Online Social Networks Information: Personal Preferences and Location-Based Community Trends, IEEE Transactions on Computational Social Systems, 4, 3, 104-120, 09/01/17, 10.1109/TCSS.2017.2720632
- TrendFusion: Trends and Influences Among Geographically Colocated Large User Communities, SocialCom, 2015, CA, USA
- Tweets You Like: Personalized Tweets Recommendation based on Dynamic Users Interests, Proceedings of the Third ASE International Conference on Social Informatics, 12/01/14, Cambridge, MA, USA
- Personalized Microblogs Corpus Recommendation Based on Dynamic Users Interests, SocialCom, 2013
- TRUPI: Twitter Recommendation Based on Users' Personal Interests, CICLing, 2015
Timeline
PhD Principal Data Scientist
Mosaic ATM
12.2023 - 03.2025
PhD Senior Data Scientist
Mosaic ATM
11.2019 - 11.2023
Senior Data Scientist- Consultant
The College Board
02.2019 - 05.2019
Senior Data Scientist
Chelfie – Solebrity Inc
05.2017 - 07.2018
Data Scientist
Chelfie – Solebrity Inc
01.2016 - 05.2017
PhD Researcher
College of Engineering, Virginia Tech University
08.2010 - 12.2015
Ph.D - Computer Science and Applications
Virginia Tech
M. Sc. - Computer Science
Ain Shams University
B. Sc. - Computer Science
Ain Shams University
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