2017-18 was the second cohort of the NRT ICGE program. Browse the material below for more information about the course materials, project teams, and more.
Follow the links below to see more detailed information about the program launch and the NRT ICGE course as a whole.
2017-18 Course Modules
Lead faculty: Zatz
Format: In addition to the orientation, four 30-minute instructional sessions plus continuous hands-on experience in project teams and at final group presentation.
Objectives: Provide students expectations and goals for graduate school and beyond. Student Learning Objectives: 1 (Professionalization) and 5 (Career Preparation).
Description: This module will provide students the fundamental, non-technical skills needed in graduate school such as clarifying the nature of the Ph.D. and how it differs from undergraduate studies, ethical practices in research, and preparing publications, presentations, webpages, curriculum vitae, etc. through participation in discussions and activities with an inclusive community of scholars. In addition, students will be introduced to the value of interdisciplinary and transdisciplinary research and to the broad spectrum of career opportunities in the computational and data sciences.
To hone their oral communication skills, project participants will participate in GradSlam, a UC system-wide competition in which students must present their research in three minutes. Writing skills will be addressed through Dissertation Boot Camp and through the publishing and grant writing workshops offered by the Graduate Division. Students may also participate in our Preparing Future Faculty and Preparing Future Professionals series, which include forums on choosing between academic and nonacademic careers, the postdoctoral research experience, interviewing for academic positions and negotiating the job offer, surviving and thriving as faculty of color, employment opportunities for Ph.D.s in industry, business, government, and nongovernmental organizations, preparing for jobs in industry, and National Labs Day (see http://graduatedivision.ucmerced.edu/GEARS).
In addition, UC Merced has a subscription to the National Center for Faculty Development and Diversity and the Versatile Ph.D. and we will draw on webinars and other resources from these clearinghouses.
Outcomes: Upon completing this module, students will have adjusted to graduate school, and will have developed a curriculum vitae, personal webpage, and Independent Development Plan.
Module Resources & Materials:
- Surviving & Thriving in Graduate School
- Seven Steps to Surviving Grad School
- Getting Things Done
- Tips on Giving Talks
- Presentation Tips
- General ICGE Resources
- "Social science, Today" (Science, 1/5/2018 vol 359, issue 6371) by David Lazar
Module 2: Interactive Programming
Lead faculty: Colvin and Spivey, assisted by Jeffrey Weekley (Director of Cyber Infrastructure and Research Computing)
Format: Four 45-minute instructional sessions plus continuous hands-on experience in project teams.
Objectives: Provide experience successfully writing, testing, and validating programs in several interactive and scripting programming environments such as Matlab, R, Python, and CalVR. Student Learning Objectives: 2 (Team Science), 3 (Research Skills) and 4 (Computational Skills).
Description: This module will teach students fundamentals of programming such as data structures, logical operations, loops, and data management and visualization using interactive programming environments. Data visualization will include virtual immersion demonstrations in our Virtual Reality CAVE (Computer Assisted Virtual Environment), an intracampus facility housed in the Digital Humanities Lab.
Outcomes: Upon completing this module, teams of students will have developed, tested and cross-validated codes in Matlab, R, Python, and CalVR to solve problems relevant to their own research and, in so doing, gained team science skills.
Module Resources & Materials:
- Session 3: Python Programming
- Session 4: Python Programming
- Session 5: Statistical Modeling
- MatLab Project: Scale Free Net
- Matlab Project: ErdosRenyi
- Matlab Project: LorenzAttractor
Module 3: The Linux Operating System and Shell Scripting
Lead faculty: Sindi
Format: Four 45-minute instructional sessions plus continuous hands-on experience in project teams.
Objectives: Provide experience working with the Linux operating system and developing shell scripts. Student Learning Objectives: 3 (Research Skills) and 4 (Computational Skills).
Description: This module will teach students how to manage files, transfer data, and execute programs in the Linux operating system.
Outcomes: Upon completing this module, the students will be able to use commands in the Linux operating system to organize and parse data files, to transfer data between computer systems, and write scripts to automate program execution and data analysis.
Module Resources & Materials:
Module 4: High Performance Clusters and Remote Supercomputers
Lead faculty: Martini and Singhal, assisted by Jeffrey Weekley (Director of Cyber Infrastructure and Research Computing) and Sarvani Chadalapaka (HPC Administrator)
Format: Two 60-minute instructional sessions plus continuous hands-on experience in project teams.
Objectives: Provide experience accessing and using high performance clusters and remote supercomputer systems, such as those on the NSF-funded XSEDE network. Student Learning Objective: 4 (Computational Skills).
Description: Each student will be provided an account on an XSEDE supercomputer as part of an educational allocation, learn about accessing and using this computer, write scripts to run programs in the supercomputer’s queuing system, and run a series of benchmark simulations.
Outcomes Achieved: Upon completing this module, students will be able to effectively use local and remote supercomputing resources for their graduate research.
Module Resources & Materials:
Module 5: Team Science and Project Management
Lead faculty: Maglio
Format: In addition to the orientation, four 30-minute instructional sessions plus continuous hands-on experience in project teams and at final group presentation.
Objectives: Provide experience with managing projects using a team science approach, and provide deep understanding of the technological and social challenges and opportunities associated with team science. Student Learning Objectives: 1 (Professionalization) 2 (Team Science), 3 (Research Skills), and 5 (Career Preparation).
Description: In this module, students will learn project management and teamwork skills. The weekly project team activities will teach participants about the technology-based tools that enable collaboration and project management and how to identify and structure a project, organize the team, break the work into subprojects, and assess team performance. They will learn to identify and address different types of problems and the scientific skills necessary to complete those projects. We will also familiarize students with basic team science tools, skills and principles as well as different frameworks for developing solutions to real-world problems, thus enabling our students to transition from incremental research to transformational breakthroughs. Students will utilize various cloud-based tools and platforms for cooperation and coordination.
Outcomes Achieved: Upon completing this module, students will be able to efficiently and effectively participate in team science projects, and be able to assess and diagnose issues related to team effectiveness and efficiency.
Module Resources & Materials:
2017-18 NRT ICGE Alumni
Christina Acosta (Sociology)
Heather Daniels (Sociology)
Dominique Davenport (Physics)
William Delmas (Physics)
Anais Guillem (IH)
Lesly Lopez (QSB)
Akshay D. Paropkari (QSB)
Jonathan Rice (QSB)
Sara Schneider (CIS)
Ana Simoes (Psych)
Tyrome Sweet (QSB)
Alauna Wheeler (Physics)
Rhondene Wint (QSB)
2017-18 Project Teams
Project Name: “Twitter Scraping to Analyze Hashtags on Mass Shootings”
Team Name: “#T1”
Team: Sara Schneider (CIS), William Delmas (Physics) and Christina Acosta (Sociology)
Advisory Board Mentor: Karl Lieber (HPE)
Faculty Mentors: Michael Spivey and Arnold Kim
Project Name: “To Build Machine lLarning Algorithm to Optimize Trading Strategies”
Team Name: “MoneyMaker”
Team: Akshay D. Paropkari (QSB), Jonathan Rice (QSB) and Heather Daniels (Sociology)
Advisory Board Mentor: Mihai Anitescu
Faculty Mentors: Paul Maglio and Suzanne Sindi
Project Name: “Phishing Email Detector”
Team Name: “Barracuda”
Team: Rhondene Wint (QSB), Alauna Wheeler(Sociology) and Lesly Lopez(QSB)
Advisory Board Mentor: Sean Peisert (LBNL)
Faculty Mentors: Mukesh Singhal and Ashlie Martini
Project Name: “Convolutional Neural Network to Identify Mayan Numbers Located on Mayan Glyphs”
Team Name: “Maya Gif”
Team:Dominique Davenport (Physics), Anais Guillem (IH), Ana Simoes (Psych) and Tyrome Sweet (QSB)
Advisory Board Mentor: Prabhat (LBNL)
Faculty Mentors: Michael Colvin and Sayantani Ghosh
2017-18 Photos and Media
"UC Merced Graduate Students Visit," InTheLoop, the weekly newsletter for Berkeley Lab Computing Sciences, April 23, 2018
UC Merced's 2017-18 NRT ICGE students at Lawrence Berkeley National Laboratory.
2017-18 NRT ICGE students visiting the Cori supercomputer in NERSC machine room.
