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NRT-ICGE 2019-2020 Information

2019-20 will be the fourth 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.

2020 Course Syllabus


2019-20 Planned Course Modules

Module 1: Practices and Habits of Successful Graduate Students in the Interdisciplinary Computational Sciences

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:


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:


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:


2019-20 NRT ICGE Participants

Fereshteh Memarian (Physics)

Michael Leveille (Physics)

Samuel Erickson (Physics)

Ignacio Romero (Bioengineering)

Azar Alizadeh (Electrical Engineering & Computer Science)

Gustavo Dourado (Environmental Systems)

Mehdi Masud (Physics)

Beatrice Morales Perez (Materials & Biomaterials Engineering)

Nabaraj Pokhrel (Physics)

Nasit Sony (Electrical Engineering & Computer Science)

Md. Humayun Kabir (Interdiciplinary Humanities)

Kamal Hossain (Physics)

Sergio Romero Garcia (Mechanical Engineering)

Sarina Qin (Quantitative & Systems Biology)

Kelly Otsuka (Quantitative & Systems Biology)

Yesdaulet Izenov (Electrical Engineering & Computer Science)

Matthew Robinson (Materials & Biomaterials Engineering)

Taylor Fugere (Management of Complex Systems)

Zunaira Iqbal (Cognititve & Information Sciences)

Harrison Ho (Quantitative & Systems Biology)

José Millan-Higuera (Mechanical Engineering)

 


2019-20 Project Teams

Project Name: UCM Traffic
Team: Fereshteh Memarian (Physics), Michael Leveille (Physics), Samuel Erickson (Physics), Ignacio Romero (Bioengineering), Azar Alizadeh (Electrical Engineering & Computer Science), Gustavo Dourado (Environmental Systems)
Advisory Board Mentor: Peter Nugent (LBNL)
Faculty Mentors: Paul Maglio, Arnold Kim

Project Name: UCM Student Data
Team: Mehdi Masud (Physics), Beatrice Morales Perez (Materials & Biomaterials Engineering), Nabaraj Pokhrel (Physics), Nasit Sony (Electrical Engineering & Computer Science), Md. Humayun Kabir (Interdiciplinary Humanities), Kamal Hossain (Physics)

Advisory Board Mentor:
Faculty Mentors: Michael Colvin and Mukesh Singhal

Project Name: Kaiser- CDC ACES (Trauma)
Team: Sergio Romero Garcia (Mechanical Engineering), Sarina Qin (Quantitative & Systems Biology), Kelly Otsuka (Quantitative & Systems Biology), Yesdaulet Izenov (Electrical Engineering & Computer Science), Matthew Robinson (Materials & Biomaterials Engineering)
Advisory Board Mentor: Steven W. Knowlton (Kaiser Foundation Health Plan)
Faculty Mentors: Ashlie Martini and Sai Ghosh

Project Name: Social Media Activism
Team: Taylor Fugere (Management of Complex Systems), Zunaira Iqbal (Cognititve & Information Sciences), Harrison Ho (Quantitative & Systems Biology), José Millan-Higuera (Mechanical Engineering)
Advisory Board Mentor: Dave Vinson (Accenture)
Faculty Mentors: Michael Spivey and Marjorie Zatz