UCSB CS Early Research Scholars Program

Welcome! This is the homepage for the UCSB CS Early Research Scholars Program (ERSP).

ERSP is a year-long research apprenticeship program designed for students early in their undergraduate studies (typically in their second year) to gain foundational knowledge and skills for engaging in research in the discipline. Students work in a team (of typically four peers) with a Computer Science faculty on a project that ties into the faculty's research area. ERSP students are additionally supported by the program coordinator and a graduate assistant, as well as the graduate student(s) of their assigned CS faculty mentor. In Fall, ERSP students take a 4-unit research methods course to develop a research proposal and gain the knowledge and skills required to carry out the research. In Winter and Spring, they continue working on their project for 2-units of credit. The program wraps up with a poster presentation at the end of Spring.

Many thanks to the faculty and graduate mentors of the 2018/19 and 2019/20 cohorts:

  • Professors Elizabeth Belding, Tobias Hollerer, Tevfik Bultan, Tim Sherwood, and William Wang;
  • Graduate students: Mai ElSherief, Deeksha Dangwal, Ehsan Sayyad, Alvin Glova, Sharon Levy, Yi Ding, and William Eiers.

If you are a CS faculty interested in being a research mentor for ERSP, please email me (diba@ucsb.edu). More information for faculty is available here .

Student applications for the 2020/21 ERSP-UCSB cohort are now open!

Information for students

The goal of ERSP is to give you the opportunity to learn about computer science research, improve and apply your core CS knowledge, gain skills important to your future as a computer scientist, and interact closely with our amazing faculty mentors and a supportive group of peers in ERSP. Expect it to be challenging and lots of fun !

Read more here.

Information for faculty

ERSP engages a diverse and highly motivated group of undergraduates in research apprenticeships to get them excited about the field.

Faculty mentors open their research group meetings or 1 on 1 student meetings to allow ERSP students to sit in. Mentors (or their grad students) also take an active but well-supported role in guiding students' research during one academic year.

Read more here.

Highlights from the 2018/19 academic year

  • ERSP students Jacqueline Mai, Maggie Lim present their team's paper titled " PyRTLMatrix: an Object-Oriented Hardware Design Pattern for Prototyping ML Accelerators" at Workshop on Energy Efficient Machine Learning and Cognitive Computing, Phoenix, AZ. ERSP student co-authors include Dawit Aboye and Dylan Kupsh. Many thanks to their research adviors: Deeksha Dangwal and Professor Tim Sherwood
  • ERSP students Andrew Gaut and Tony Sun present their team's paper titled " Mitigating Gender Bias in Natural Language Processing: Literature Review" at the 57th Annual Meeting of the Association for Computational Linguistics (ACL) in Florence, Italy. ERSP student co-authors include Shirlyn Tang and Yuxin Huang. Many thanks to their research adviors: Mai ElSherief, and Professors William Wang and Elizabeth Belding.
  • ERSP HCI team: April Sanchez, Cynthia Zhang, Bella Yue, Nathan Wu demo their research project on visualizing environmental data in virtual reality at the 2019 Media Arts and Technology End of Year showcase. Many thanks to their research mentors: Ehsan Sayyad and Professor Tobias Hollerer
  • ERSP student Jacqueline Mai wins the 2019 CS Outstanding Undergraduate Research award. Congratulations to Jacqui and her advisor Professor Tim Sherwood! Read more about the event here: https://cs.ucsb.edu/news/3471.
  • ERSP students present their research at the CS Spring Undergraduate Research Showcase. Read more about the event here: https://cs.ucsb.edu/news/3473
UCSB-ERSP is supported by the National Science Foundation (award Number: 1821415): Scaling the Early Research Scholars Program. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.