Prospective graduate students

Thank you for considering RDCL!

Are you currently accepting students?

  • I am accepting graduate students for the fall 2026 entering class.

How do I apply?

  • See this page to start the application process.

What background, interests, and skills should I have?

  • Successful students can come from any background. Some experience with cognitive psychology or cognitive science is helpful.
  • Interest in issues relating to basic research in human reasoning, judgment, and decision making.
  • Students should be self-motivated, independent learners, and take charge of the direction of their education.
  • Strong quantitative skills, including basic programming, are helpful, but we will also development those skills together.
  • A strong commitment to the scientific process and a search for truth.

What is expected of graduate students?

  • See this page for coursework and research requirements.
  • You will jump right into research.
    • Early on you will probably work on an on-going project.
    • Once you’ve learned the basic skills and literature, you will start formulating your own research projects.
  • I love supporting student growth and discovery.

What can you expect from the program and me?

  • Our goal is to train a well-rounded researcher and teacher.
    • Research – Literature, tools, skills, research guidance.
    • Communication – Writing and presentation skills.
    • Publications – Journal publications and conference presentations.
    • Teaching – Teaching assistantships and/or independent classes.
    • Application – Skills needed to thrive in academia or industry.

What kind of research will I be involved in?

  • See this page for an overview.
  • Research projects are constantly evolving and are tailored to student interests, but most current research revolves around the following:
    • Eyewitness lineups. In particular, we are interested in better ways to measure lineup success and, using that measure, how lineups can be constructed to maximize information about suspect guilt or innocence,
      • Starns, J. J., Cohen, A. L., & Rotello, C. M. (2023). A complete method for assessing the effectiveness of eyewitness identification procedures: Expected information gain. Psychological Review, 130(3), 677.
      • Tuttle, M. D., Starns, J. J., & Cohen, A. L. (2025). Protecting the innocent in eyewitness identification: An analysis of simultaneous and ranking lineups. Journal of Memory and Language, 140, 104581.
    • Fingerprint analysis. This research is somewhat similar to the eyewitness work, in that we are generally applying similar concepts to a different domain. For example, we are considering how to best collect fingerprint examiner reports and how fingerprint database searches affect the evaluation process.
      • Cohen, A. L., Starns, J. J., Coon, M., Aggadi, N., & Busey, T. A. (2025). Evaluating reporting practices in fingerprint comparisons using information theory: five response categories are better than three. Law, Probability and Risk, 24(1), mgaf004.
    • Choice. The basic idea is to examine context effects, a set of phenomena that describe how choice is affected by the available options, and the relation to valuation, a judgement of the value of each option.
      • Conway, S. P., & Cohen, A. L. (2025). Testing Principles of Choice in Categorization. Computational Brain & Behavior, 1-28.
      • Cataldo, A. M., & Cohen, A. L. (2019). The comparison process as an account of variation in the attraction, compromise, and similarity effects. Psychonomic Bulletin & Review, 26(3), 934-942.

Is there much collaboration within the department and across campus?

  • Once settled, collaboration with other cognitive faculty, other departmental faculty, and even faculty from other departments (e.g., computer science) is strongly encouraged.
  • I work closely with Jeffrey Starns.

What is the program’s focus and major direction?

  • The program is strong in higher-level cognition (memory, language, decision-making), attention, computational modeling, and cognitive neuroscience.

Is there an opportunity to do imaging work?

  • I am happy to do imaging work where it is appropriate, advances theory, and funding is available.
  • The department has multiple ERP/EEG machines.
  • The university has an fMRI scanner.
  • Imaging work would be done in conjunction with another faculty member, it is not my primary line of research.

What other facilities are available?

  • Most of the work in the lab is done on computers or online in a range of software frameworks (psychtoolbox, psychopy, etc).
  • Most modeling and analysis is done in R.
  • Through the Eyetracking Lab, we have access to a number of eye trackers.

How can I learn more?

  • Please feel free to contact me via email.

How would I be supported?

  • The program and department are very careful to only admit students they can realistically support.
  • Although no department can guarantee funding, we have always been able to fund our students for at least 5 years.
  • This page summarizes TA and RA support.

What is Amherst like?

  • The Amherst area is a great attraction for many students.
  • Amherst is a medium-sized New England town of about 30,000.
  • The area is a mix of residential areas, woods, and farmland.
  • We are 2 hours from Boston and 1 hour from the nearest airport (Hartford, CT).
  • The thriving towns of Easthampton and Northampton are just across the river.
  • The fall here is beautiful. The winter is snowy.
  • There are 5 colleges nearby (Amherst, Hampshire, Smith, Mt. Holyoke, and UMass), so something is always going on.
  • Housing is addressed here.
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