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Lisa O'Bryan

Lisa O'Bryan

Assistant Research Professor, Electrical and Computer Engineering

Electrical and Computer Engineering

CONTACT

obryan@rice.edu

WEBSITE(S)| Profile

SURF Mentoring

Potential projects/topics: Students have the opportunity to select from the following research projects:

  • Project 1: This project focuses on developing and evaluating methods for identifying and classifying vocalizations or behaviors from raw wearable sensor data from animals (wild baboons, goats, sheep). The student will compare different classification approaches using an existing dataset. Emphasis will be on assessing the performance and tradeoffs of different classification approaches, but students may also use processed data to answer behavioral questions, if interested

  • Project 2: This project focuses on applying an existing computational model of conversational dynamics to conversation data to evaluate the underlying social dynamics. The student may work with either publicly available annotated datasets (e.g., television shows, podcasts) or synthetically generated conversations (LLMs) to examine how the model behaves under different data conditions. The project will focus on evaluating how model outputs are shaped by conversational characteristics.

  • Project 3: This project focuses on developing and evaluating methods for representing the semantic content of individual speaking turns within a conversation. Using an existing dataset collected from student teams, the student will use different language models to embed conversational statements in semantic space to evaluate how well they capture the underlying intent and opinions of speakers.

Potential skills gained: data analysis, machine learning, computational modeling, natural language processing, data visualization, programming in Python or R

Required qualifications: Some programming experience in Python or R is preferable. Best suited to majors in ECE, Biosciences, or Cognitive Sciences

Direct mentor: Faculty/P.I.

Research Areas

Dr. O’Bryan's interdisciplinary research spans complex systems science, behavioral ecology, psychology, and engineering. Her research is centered on understanding the mechanism and function of the communication systems underlying collective social behaviors (behavioral coordination, collective decision-making) across both non-human and human species. As part of her work, Dr. O’Bryan develops novel methodological and computational approaches for understanding and predicting collective social behaviors. By employing new technologies (e.g., wearable dataloggers, audio-visual recording, web apps), she captures detailed data on individual and group behaviors, and analyses these data using statistical methods, computational models, and machine learning. Past studies have explored collective movement and decision-making in free-ranging animal groups and collective intelligence in human teams. Her long-term goal is to conduct comparative research across social groups to illuminate the shared (and unique) communication mechanisms underlying collective social behaviors. By harnessing this knowledge, she aims to address important social challenges, such as enhancing collective intelligence in human groups, improving the conservation or management of animal groups, and informing the design of distributed artificial systems. Dr. O’Bryan’s research areas include collective behavior, collective intelligence, behavioral measurement and tracking, computational modeling, and machine learning.