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Early Research Scholars Program

About ERSP

The BYU Computer Science Early Research Scholars Program (ERSP) is a team-based research apprentice experience for computer science majors in their second year of the program.

Students get a chance to learn how to conduct research early in their program of study, enabling them to better understand the field of computer science and to consider whether academic research and a graduate degree may be part of their future path.

Students work in teams of four, and each team is matched with an active research project in the department. Students learn about research in computer science and then propose and carry out an independent research project over the course of an academic year.

Over the course of the program, ERSP groups will attend a research group’s normal weekly meetings to observe and learn from (and eventually contribute to) this research group. At the same time, ERSP students attend a weekly support class with all other students in the ERSP program that helps them learn the basics of research and make sense of what they are hearing and learning about in their research groups.

The ERSP was started at UCSD, with partners now at UIC, UC Santa Barbara, Stanford University, and several other universities.

ERSP Objectives

  • To excite participants through early exposure to research in computer science and the challenges facing CS researchers today.
  • To teach participants the fundamental skills involved in conducting CS research.
  • To create a diverse and supportive community within the CSE department, with a particular focus on engaging students from groups currently underrepresented in computer science including women, African Americans, Hispanics, Native Americans and indigenous peoples.

Overview of the Program

Over the course of a year, ERSP students enroll in two courses. We will work with students to have both of these courses count for credit in their current major, whenever possible.

Winter Term: CS 301R Introduction to Computer Science Research (3 credits)

Main outcome: Completion of a proposal for an original group project

Activities: Class discussion, weekly meetings with research adviser and grad student adviser


  • Identifying and formulating research problems
  • Reading research papers
  • Working effectively in a team
  • Literature searching
  • Self-guided learning
  • Designing research studies
  • Data analysis
  • Time management, goal setting and activity logging
  • Communicating about research, both orally and in written form
  • Effective teamwork communication and skills
  • Peer review
  • Research ethics
  • Learning tools/methods for their research project (e.g. online courses, tutorials)

Spring: CS 497R Independent Research (3 credits)

Main outcome: Completion of a group research project, culminating in a poster session Activities: Work on research project, 10 hours per week, joint mentoring with grad student TA and research faculty

Mentoring: Grad student TA meets weekly with each group for an hour, helping them set goals, choose tasks, organize time, hold them accountable, ERSP central adviser meets weekly with each team

Meetings: How to design and present a poster


During the course of the program students are dual mentored by a central ERSP director/adviser and by a research advisor. The central ERSP adviser is usually assisted by a graduate student assistant ERSP adviser. The diagram below gives an overview of the overall program structure (the grad student assistant is not shown in the diagram, but would assist the ERSP Central Adviser with her or his tasks). The specific role of each adviser is discussed in more detail below.

mentoring organization

Current Research Groups

Currently, the following research groups will be participating in the coming year. We will add more if possible.

  • Ryan Farrell – Fine-Grained Visual Categorization. Training computers to find the highly-localized and often subtle characteristics that allow precise identification at the level of fine-grained categories.

  • Nancy Fulda – DRAGN Lab. DRAGN Lab focuses on neural architectures for Conversational AI, in addition to machine learning, neural language models, and natural language understanding.

  • Amanda Hughes – Crisis Informatics Lab. The Crisis Informatics Lab seeks to understand how people use information and communication technology (ICT) during crises and mass emergencies, with particular attention on social media. AN overarching goal of this research is to inform, design, implement, and deploy software systems that improve crisis communications.

  • Mike Jones – Advanced Interactive Lab. Builds interactive systems from emerging technology. They are currently working on presenting sports motion data in the context of the coach-athlete relationship and on mobile phone apps that enhance rather than minimize the benefits of hiking.

  • Xinru Page – Social Technology and Privacy Lab (STaPL). STaPL is a human computer interaction lab that focuses on understanding how people use social technologies. We design technologies that facilitate social needs balanced against privacy and online safety in areas such as social media, mobile, health, and IOT.