Hamada S. Badr

Interests

• Machine Learning (ML) & Artificial Intelligence (AI)
• Natural Language Processing (NLP) & Computer Vision
• Interpretable Modeling & Uncertainty Quantification
• Computational Statistics & Bayesian Inference
• High Performance Computing (HPC)
• Computational Fluid Dynamics (CFD)
• Numerical Weather Prediction (NWP)
• Numerical Modeling & Data Assimilation
• Multiscale Hydroclimate Dynamics & Modeling
• Statistical & Dynamical Downscaling
• Satellite Remote Sensing & Earth Observation
• Spatiotemporal Analysis of Hydroclimate Variability
• Extreme Weather Events & Climate Change
• Environmental Health & Infectious Diseases
• Customer Journey Analytics & Business Intelligence

Education

2016  Ph.D. Earth and Planetary Sciences
Department of Earth and Planetary Sciences (EPS), Johns Hopkins University (JHU), Baltimore, Maryland, USA
Advisor(s): Benjamin F. Zaitchik
Dissertation: Applications of Climate Regionalization: Statistical Prediction & Patterns of Precipitation Variability in Observations & Global Climate Models

2013  M.A. Earth and Planetary Sciences
Department of Earth and Planetary Sciences (EPS), Johns Hopkins University (JHU), Baltimore, Maryland, USA
Advisor(s): Benjamin F. Zaitchik

2011  M.Sc. Aerospace Engineering
Department of Aerospace Engineering (AER), Cairo University (CU), Giza, Egypt
Advisor(s): Atef O. Sherif, Basman M. N. Elhadidi, and Hamdy A. Kandil
Thesis: Ensemble Forecasting & Data Assimilation in Numerical Weather Modeling for Egypt
Examining Committee: Atef O. Sherif, Jimy Dudhia, and Mohamed E. Elraey
PDF: M.Sc. Thesis 2011 & Evaluation Report

2003  B.Sc. Aerospace Engineering
Department of Aerospace Engineering (AER), Cairo University (CU), Giza, Egypt
Advisor(s): Atef O. Sherif
Graduation Project: Terrain Aerodynamics

Experience

2024 – Present Customer Contact Demand Forecasting
Forecasting Science, Worldwide Capacity Planning (WWCP), Amazon Customer Service (CS), Seattle, Washington, USA
Develop an automated, scalable, scientific workflow that significantly enhances customer service operational efficiency and decision-making, leading to optimized resource planning and cost management.

2022 – 2024 Customer Journey
Sales, Marketing & Global Services (SMGS) Ops – Data Platform & Infrastructure (DP&I) Science & Econ, Amazon Web Services (AWS), Herndon, Virginia, USA
Customer Journey enables the automation of actionable insights, predictions, and recommendation strategies. I started with a vague idea, just like building a successful startup, and delivered high-quality results with long-term vision. My solution uncovered the stages, inflection points, dwell times, insights, and drivers of end-to-end customer journeys.

2020 – 2022 Tracking and Modeling of COVID-19 Pandemic
Department of Earth and Planetary Sciences (EPS), Johns Hopkins University (JHU), Baltimore, Maryland, USA
COVID-19 Supplement to "Determinants of Enteric Infectious Disease: a GEO Platform for Analysis and Risk Assessment" is a project to develop an environmentally informed risk monitoring and early warning application that will inform decision makers for appropriate interventions and investments needed to prepare properly for potential reemergence of the disease as policy measures are relaxed. Machine learning and epidemic modeling are used for generating risk maps as well as prospective tracking and modeling of the impacts of hydrometeorological factors on COVID-19 pandemic.

2019 – 2023 Leveraging Earth Observations for Improved Climate Projections
Department of Earth and Planetary Sciences (EPS), Johns Hopkins University (JHU), Baltimore, Maryland, USA
GMELT Ahead: Leveraging Earth Observations for Improved Climate Projections in High Mountain Asia is a 3-year project to generate high-resolution projections of future climate and hydrology that grounded in best-available historical observations and understanding of atmospheric processes. Different approaches are used for downscaling, including regionalization and Convolutional Neural Network (CNN) pattern reconstruction.

2019 – 2022 Multi-scale Prediction of Flash Drought in the United States
Department of Earth and Planetary Sciences (EPS), Johns Hopkins University (JHU), Baltimore, Maryland, USA
PREEVENTS Track 2: Collaborative Research: Flash droughts: process, prediction, and the central role of vegetation in their evolution is a 3-year project to advance efforts to understand and forecast flash droughts (FD) by targeting three characteristic features: (1) land surface memory is a key component of FD, (2) evaporative demand is a leading driver of FD onset, (3) vegetation plays a central role in FD development through its influence on soil moisture and turbulent heat fluxes. Deep Learning algorithms are used for the prediction and classification of flash droughts.

2017 – 2020 Applications of Deep Learning to S2S Prediction & Downscaling
Department of Earth and Planetary Sciences (EPS), Johns Hopkins University (JHU), Baltimore, Maryland, USA
Convolutional Neural Networks (CNN) are implemented and optimized with a custom loss function (based on objective climate regionalization) to improve dynamical forecasts at subseasonal to seasonal (S2S) timescales. Training is performed using historical observations and the North American Multi-Model Ensemble (NMME) monthly forecasts.

2017 – 2020 Environmental Determinants of Enteric Infectious Disease
Department of Earth and Planetary Sciences (EPS), Johns Hopkins University (JHU), Baltimore, Maryland, USA
Determinants of Enteric Infectious Disease: a GEO Platform for Analysis and Risk Assessment is a 3-year project to develop an environmentally informed risk monitoring and early warning application that will inform decision makers for appropriate interventions and investments needed to reduce enteric infectious (EID) diseases. The project will leverage data from the MAL-ED project funding by the Bill and Melinda Gates Foundation and bridge this health information with environmental data from earth observations. Very comprehensive model development to include a wide range of predictor variables as well as targeting 8 countries within the MAL-ED sites, generating a global picture of EID.

2017 – 2018 Advanced Seminar in Remote Sensing
Department of Earth and Planetary Sciences (EPS), Johns Hopkins University (JHU), Baltimore, Maryland, USA
The fall 2017 iteration of Advanced Seminar in Remote Sensing focused on the application, interpretation, and visualization of Land Data Assimilation Systems (LDAS). Through lectures, exercises, and a semester project, students learnt the theory behind LDAS, run LDAS simulations using the NASA Land Information System (LIS), and built web visualization applications for LDAS output using the open-source Tethys scientific visualization platform.

2016 – 2018 The NASA Land Information System (LIS)
Department of Earth and Planetary Sciences (EPS), Johns Hopkins University (JHU), Baltimore, Maryland, USA
Contributions to the development and training workshops of the NASA Land Information System (LIS). For example, a workshop for Egyptian applications was held at the National Authority for Remote Sensing and Space Sciences (NARSS) in Cairo, Egypt, in August 2017. The program included a plenary session on August 6 and interagency technical working sessions on August 7-10. In addition, targeted technical preparatory activities were held in the week preceding the workshop and follow-up project oriented activities took place in the week after the formal workshop. A similar workshop was held at Korea Water Resources Corporation (K-Water), Daejeon, South Korea in January 2018.

2015 – 2016 Porting NU-WRF to HHPC & MARCC
Department of Earth and Planetary Sciences (EPS), Johns Hopkins University (JHU), Baltimore, Maryland, USA
Porting NASA-Unified Weather Research and Forecasting (NU-WRF) model to JHU Homewood High Performance Compute Cluster (HHPC) and to Maryland Advanced Research Computing Center (MARCC).

2015 – 2016 Climate Regionalization of Africa
Department of Earth and Planetary Sciences (EPS), Johns Hopkins University (JHU), Baltimore, Maryland, USA
Regionalizing Africa based on interannual variability of precipitation: spatial patterns of precipitation variability in observations and global climate models (GCMs) at different times from geological periods to historical simulations and future climate projections.

2013 – 2015 Objective Climate Regionalization
Department of Earth and Planetary Sciences (EPS), Johns Hopkins University (JHU), Baltimore, Maryland, USA
Development of an open-source R package for Hierarchical Climate Regionalization (HiClimR) to facilitate the application of rigorous regionalization for climate studies. It adds several features including multi-variate and hybrid clustering and a new clustering method (called, regional linkage) to hierarchical clustering (hclust function in stats library) in R, for climate regionalization. HiClimR is applicable to any correlation-based clustering.

2011 – 2013 Seasonal Precipitation Predictions
Department of Earth and Planetary Sciences (EPS), Johns Hopkins University (JHU), Baltimore, Maryland, USA
Application of different statistical models, including artificial neural networks (ANN), to understand and predict seasonal rainfall anomalies as a function of large-scale indices of surface air temperature anomalies (SATA), sea surface temperature (SST), surface pressure, and other variables.

2010 – 2011 Prediction of Dust/Sand Storms
National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt
Development of a framework for dust/sand storms prediction using numerical weather prediction and remote sensing technology.

2010 – 2010 Porting WRF to EUMEDGRID
Africa 4 2010 - Joint EUMEDGRID-Support / EPIKH School for Application Porting, Cairo, Egypt
Porting the Weather Research and Forecasting (WRF) model to EUMEDGRID.

2010 – 2010 High Performance Computing (HPC)
IBM-Egypt and National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt
IBM AIX 5L system administration and running Code_Saturne Computational Fluid Dynamics (CFD) Solver on NARSS Blue-Gene/L .

2008 – 2010 Ensemble Forecasting
National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt
Development of a preliminary ensemble forecasting system for Egypt, which can be developed for operational use.

2008 – 2008 Estimation of Evaporative Rates
National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt
Evaluation of Lake Nasser water loss by evaporation using numerical weather prediction and remote sensing technology.

2006 – 2008 Data Assimilation
National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt
Implementation of the conventional and remotely-sensed observational data into the numerical weather modeling system for Egypt using Four-Dimensional Data Assimilation (FDDA).

2005 – 2006 ATOVS Data Processing and Visualization
National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt
Development of an automatic framework for the processing and visualization of NOAA/ATOVS satellite data.

2001 – 2003 Terrain Aerodynamics
Department of Aerospace Engineering (AER), Cairo University (CU), Giza, Egypt
Generation of a surface grid for Cairo area from raster maps, measuring flow over prototypes in a wind tunnel, and comparing the numerical and experimental results.