Psychology Projects
This is the full list of all participating labs for the Fall 2024-Spring 2025 Psychology REP cohort.
Mentees should choose up to 2 projects of interest to select on the application.
If you would like to learn more about the different areas of Psychology research, check out the Psychology departments webpage here!
Alison Gopnik Lab (Developmental)
Mentor: Eunice Yiu
Research Topics: Child learning and exploration
Project Description: Active learning and hypothesis search: humans are quick and flexible learners. We readily figure out rules and patterns from our observations and would also actively intervene in the world based on those rules and patterns to learn new things and achieve new goals. How does this capability emerge across development? This research project explores children's and adults' selection of actions they want to take and evidence they want to see to figure out a complicated rule or win a challenging game.
Student Responsibilities: The research mentee will be involved in running fun, game-like experiments on both children and adults; recording and organizing collected human data; running analyses of human behavior. They will also have a chance to develop their independent project within this research agenda.
Preferred Mentee Skills: Passion for interacting with children; having some coding experience is great but not necessary.
Jan Engelmann Lab (1/2) (Developmental)
Mentor: Colin Jacobs
Research Topics: Cooperation, cognition, group-collaboration
Project Description: Humans achieve incredible things not through individual genius, but through collective thought. In this project, we are interested in how children begin to “think together,” across multiple societies. In particular, we are testing if children spontaneously pool cognitive resources with others to overcome individual limitations. For example, if there is too much to remember alone, how might you start to rely on friends to divide up the cognitive demand? Is the method in which you do so sensitive to cognitive constraints (individual working memory capacity), as well as cooperative ones (concern for fairness)?
Student Responsibilities: Students will primarily be collecting data at schools and museums with at least one other study team member (generally the graduate student, sometimes other research assistants). This means that we will go to local schools to run children through a set study procedure and record their behavior. Data analysis opportunities will be provided based on student's level of stats/coding expertise: either replicating data analysis and figures generated by the graduate student advisor, or working with the graduate student advisor to develop them in the first place.
Preferred Mentee Skills : Experience working with younger children is preferred, a genuine curiosity for this subject :)
Jan Engelmann Lab (2/2) (Developmental)
Mentor: Jan Engelmann
Research Topics: social cognition, comparative & evolutionary psychology
Project Description: We generally study the development and evolution of social thoughts and behaviors by studying children and chimpanzees. Some current developmental projects focus on how children develop an understanding of morality (fairness, etc.), their emotional and behavioral reactions to immorality/injustice, and how they form beliefs. Some current comparative projects focus on the origins of social curiosity, play behavior in chimpanzees, children, and adults, and how chimpanzees come to conclusions based on different kinds of evidence. Our research is interdisciplinary and often pulls from philosophy and evolutionary anthropology as well as developmental psychology.
Student Responsibilities: Student will be primarily responsible for data collection. In our lab, this means traveling to museums and schools in the Bay Area and conducting ~15 minute experiments with children aged 2-10. Student may also be responsible for coding data (which is usually simple 0/1 coding of behaviors in an excel sheet). Student may also be asked to conduct guided literature reviews, attend reading group meetings, and provide feedback on procedure design.
Mahesh Srinivasan Lab (Developmental)
Mentor: Nina Schoener
Research Topics: Language input, word learning, socio-economic status
Project Description: Across contexts, children grow up in vastly different language environments, and yet language learning appears to be a very robust process. One highly variable aspect of language environments is the amount of child-directed speech (CDS) that children receive, with low-SES caregivers speaking fewer words to their children on average than high-SES caregivers. This raises the critical question of what children are able to learn from an alternate source of input - overheard speech (OS). We will collect survey data about the child’s SES and home language environment, and assess their ability to learn from OS experimentally.
Student Responsibilities: The student’s primary responsibilities would include recruiting participants through online databases, and administering experimental protocols with preschool-aged child participants. The student would be trained on how to navigate these databases and correspond with prospective participants. Experimental protocols will involve the experimenter having a scripted conversation with the caregiver while the child plays with toys nearby. Certain features and facts about the toys will be mentioned in the “overheard conversation,” and afterwards, the experimenter will test the child on their learning of those facts. The student would also edit camcorder and head-mounted camera videos of experimental sessions for later analysis.
Preferred Mentee Skills: Video editing, naturalistic language coding, experience working with children
Fei Xu Lab (Developmental)
Mentor: Stephanie Alderete
Research Topics: cognitive development, decision-making, reasoning
Project Description: How do humans process information about the world in order to make informed and rational decisions? This project investigates the developmental origins of decision-making by studying how young children reason about the world around them. In this current study, preschoolers play a fun game where they help the experimenter collect gumballs from gumball machines. We also plan to run a version of this game with 10- to 12-month-old infants using looking time methods. Through these studies, we hope to better understand the developmental origins of inductive and deductive reasoning.
Student Responsibilities: Students will be responsible for aiding with data collection. This includes recruiting children from our developmental database and conducting online testing (via Zoom) and museum testing (Lawrence Hall of Science). Students may be working with children ranging from 10 months to 8 years of age. Students may also be assisting in coding infant-looking time via datavyu software. Students will be provided with all the training necessary to be successful, and are not expected to have any prior experience or knowledge.
Preferred Mentee Skills: none, but it's great is you have experience working with children!
David Whitney Lab (Cognitive Neuroscience)
Mentor: Jefferson Ortega
Research Topics: perception, social cognition, emotion
Project Description: The ability to quickly and accurately perceive emotion is essential in our daily lives. However, how does the brain process multiple sources of emotional information when making emotional judgments? Our research investigates how human observers perceive emotion by using dynamic stimuli (like Hollywood movies) that include much of the contextual information that we experience when making emotional inferences in the real world. To achieve this goal, we will investigate individual differences in emotion perception of dynamic context-rich stimuli. We will use eye-tracking and neuroimaging techniques like EEG while observers are watching various movies and images to answer our research questions.
Student Responsibilities: The research apprentice will be involved in running experiments and analyzing data. Students will be trained in research methods, statistics, and data analysis through the use of Python. Students may also be trained to collect and analyze data using eye-tracking and EEG. Students will also be expected to read the relevant literature and write reports on the ongoing results of the project. The student will also meet with the supervisor weekly/bi-weekly to discuss preliminary data and background literature, in addition to the opportunity to attend weekly lab meetings.
Preferred Mentee Skills: N/A
Anne Collins Lab (Cognition)
Mentor: Jing-Jing Li
Research Topics: Intelligence, cognition
Project Description: Can large language models (LLMs) like ChatGPT demonstrate human-level intelligence? Can we systematically and robustly evaluate the intelligence of LLMs like cognitive scientists have done on humans and animals? Using a set of behavioral tasks that target broad cognitive abilities, we will evaluate LLMs to characterize their intelligence, providing a benchmark for future AI models and a deeper understanding of how artificial intelligence measures up to humans.
Student Responsibilities: The student will contribute to data collection, which involves generating prompts, querying LLMs, parsing outputs, and streamlining the whole process. Depending on the student’s technical background and interest, they may also be involved in data analysis and (if applicable) modeling of the data. No prior experience is necessary.
Preferred Mentee Skills: Prefer someone who is organized and thorough. Coding skills are not necessary but a plus.
Iris Mauss Lab (Social & Personality)
Mentor: Kylie Cassutt
Research Topics: Emotion, Emotion Regulation, Close Relationships
Project Description: This project examines couples in multiple different tasks, including having stressful, positive, and conflict conversations. We are looking at different emotions, emotion regulation strategies, and behavioral expressions and dynamics within these conversations to learn more about how these variables affect relationship quality and other aspects of close relationships.
Student Responsibilities: The student would be responsible for data coding either behavior in these conversations, or looking at other aspects of the study, including participants watching emotionally influencing videos or engaging in other tasks with their partner.
Preferred Mentee Skills: Mentee does not need prior research experience or any particular skills. Anything we need them to do, I am happy to teach them.
Relationships & Social Cognition Lab (Social & Personality)
Mentor: Alejandro Campero-Oliart
Research Topics: Social Expressions of Personality & Emotion
Project Description:
Project 1. Psychophysiological and Behavioral Factors of Interpersonal Communication Apprehension — This project aims to examine the psychophysiological (e.g., arousal, vagal tone) and behavioral (e.g., social avoidance, delay discounting) experiences that are predicated by individuals' interpersonal communication apprehension, otherwise understood as a personality—type disposition which makes people vulnerable to stress when interacting with others.
Project 2. Interactionist Encodings of Meaningful Others — This project aims to examine the effect that different types of encodings of a romantic partner has on the encoder's emotions and attitudes towards their relationship. More specifically, we aim to assess the differences that thinking about partners in interactionist terms (e.g., my partner is____ when____), as opposed to global terms (e.g., my partner is ____), produces in emotions, thoughts, and actions towards one's relationship. This is also a psychophysiological study.
Student Responsibilities:
Note. Relevant training as well as ongoing guidance and support will be provided for the below responsibilities to be fulfilled successfully by the mentee.
1. Collect and analyze cardiac indices from ECG readings
2. Organized and curate collected data into coherent datasets for analyses
3. Analyze data and synthesize findings in written and visual forms
4. Code written trait descriptions/visual behavior during interpersonal interactions
5. Attend and annotate meetings and discussion sessions
Preferred Mentee Skills: Prepare for coding, statistics, data analysis, and research designs.
Rodolfo Mendoza-Denton Lab (Social & Personality)
Mentor: Lindsey Burnside
Research Topics: social stress, coping, inequity
Project Description: An investigation of what individuals believe are the maintenance factors of, and solutions to racial residential segregation. This is a mixed methods study, so students on this project will work with qualitative and quantitative data.
Student Responsibilities: Student will code open-ended responses on surveys, as well as learn to clean survey data and produce descriptives. Student will also review pertinent literature for background on the topic, and meet with supervisor. Depending on timing, student may be able to contribute to (round 2) survey development and testing.
Preferred Mentee Skills: No previous skill required, all necessary training will be provided. Interest in Stata or text analysis preferred.
Stephen Hinshaw Lab (Clinical Science)
Mentor: Nick Nguyen
Research Topics: neurodevelopmental condition (ADHD), developmental psychopathology, resilience, stigma
Project Description: The Berkeley Girls with ADHD Longitudinal Study (BGALS) began in the mid-1990s as a cross-sectional investigation—with the hope of turning it into a prospective, longitudinal project—of impairment and competence in a severely understudied population: girls with attention-deficit/hyperactivity disorder (ADHD). The project was proposed against a backdrop of a long, uphill battle that had been fought (and indeed is still being fought) for clinical and research recognition of the presence and impact of ADHD in females. Believed to be a male disorder for much of the 20th century, only recently has recognition been given to the reality of ADHD in girls and women.
Student Responsibilities: Student will mostly be expected to conduct a lit review on a topic of interest (but also related to what the lab's studying) and be able to identify gaps in the lit. Depending on skillsets, student can learn to conduct statistical analyses of old data and write up the results in prep for a conference abstract. There's also a potential involvement with data collection.
Preferred Mentee Skills: Just willingness to learn.
