CyberTraining Spring 2020

Introduction

Projects

Team 1 Project

Team 2 Project

Team 3 Project

Team 4 Project

Team 5 Project

Team 6 Project

Team 7 Project

Team 8 Project

Team 1 Project: Stochastic Precipitation Generation for the Potomac River Basin Using Hidden Markov Models

Team 2 Project: Studying Anomalous Discrepancies between MODIS and CALIOP Cloud Observations

Team 3 Project: Evaluation of Tropical Cloud Simulations between CMIP6 Models and Satellite Observations

Team 4 Project: Use of Deep Learning to Classify Compton Camera Based Prompt Gamma Imaging for Proton Radiotherapy

Team 5 Project: Machine Learning for Retrieving Cloud Optical Thickness from Observed Reflectance: 3D Effects

Team 6 Project: Benchmarking of Data-Driven Causality Discovery Approaches in the Interactions of Arctic Sea Ice and Atmosphere

Team 7 Project: Image Segmentation for Dust Detection Using Unsupervised Machine Learning

Team 8 Project: Tornado Prediction using Environmental Sounding Data: Comparing Random Forest to CNN

Some testimonials from anonymous evaluations

• “It has offered me a new dimension to consider moving forward in my PhD research. It also equipped me with some of the most important research skills required in my field of Computing, such as Big Data and Machine Learning foundations and quantitative analysis.”
• “This experience was like no other for me, and it was especially valuable because of the research experience I got out of it. I have always been interested in atmospheric data, so being able to work with that and apply big data and machine learning to it was amazing.”
• “I learned a lot of techniques which will extend my research fields. Another valuable aspect of taking this cyber training course is that I have the opportunity to work with so many professionals. I learned a lot from them.”
• “As an undergraduate, the CyberTraining program exposes students to many methods and techniques used in research within the fields of High-Performance Computing, Big Data, and Atmospheric Physics. These tools are extremely valuable and will be used in my future courses and research at UMBC and beyond.”
• “This is my first time attend an online course and it's a nice experience. The instructors are really fun, friendly and smart.”
• “It provides us a good opportunity to work on interdisciplinary research project with people from different background.”
• “As an undergraduate, it was great to see a course not lecture heavy, and more focused on learning via hands-on practice. In many ways, this method of learning can be superior to lecture-based learning, as students tend to retain more of the information. Additionally, this course does an excellent job of combining concepts from several different disciplines. In contrast, many undergraduate and graduate courses are focused on specific topics from an individual domain of science. I wish there were more courses like this offered and I believe there will be in the future.”
• “The team building was really useful during the first 10 weeks when we were doing the homework. Different persons in the team have different strengths, and we see that clearly during the first 10 weeks. And then we became real teammates while doing the homework. Then when we start with the project development, it really helps.”