Maria Paula Armenta Email & Phone Number

• Conducted an extensive literature review on reward-related behavior, neuroeconomics, and decision-making theories, with a focus on Prospect Theory and loss aversion.
• Designed and implemented an experiment to investigate how frustration influences decision-making in reward-driven tasks, particularly whether individuals prefer tasks associated with higher monetary rewards despite.
• Collected and analyzed experimental data using PsychoPy to assess task preferences and performance under conditions of gain and loss.

• Evaluated transcripts of speak-aloud protocols, including assigning accurate and reliable ratings to provide key contextual data for EEG analyses.
• Conducted literature review focused on cognitive flexibility in instrumental learning and suppression of automaticity.
• Ran participant study sessions to collect experimental data for understanding how individuals assess the importance of effort in various task settings.

West Lafayette, Indiana, United States

• Tracked data on enrollment, admissions, graduation rates, retention rates, degrees conferred, and career outcomes for undergraduate and graduate programs.
• Designed Tableau dashboards to visualize trends across various data points, including applicants, admits, and accepted students.
• Conducted year-by-year comparisons to highlight changes in student information and outcomes.

• Investigated the impact of neuropsychiatric copy number variants on chromatin conformation.
• Used brain cortex from five mouse models with human psychiatric copy number variants to study at a single-cell level.
• Performed nuclei isolation from mouse brain tissues, essential for subsequent assays using the single-cell split-pool recognition of interactions by tag extension (scSPRITE) approach.
• Learned and performed cell culture, RNA and nuclei isolation.
• Conducted animal training for experimental procedures.

United States

• Conducted multimodal, temporally-precise behavioral coding for both children and caregivers during caregiver-child interactions in telehealth PANDABox assessments.
• Performed behavioral analyses of children with typical development and neurodevelopmental conditions, including Angelman and Down syndromes.
• Preprocessed psychophysiological data, such as electrocardiography signals, for integration with behavioral and clinical data.
• Proposed and examined child engagement states in Angelman syndrome during caregiver-child interactions.

• Contributed to the development of a behavioral coding scheme for child engagement states during caregiver-child play interactions.
• Managed Purdue Early Phenotype Survey independently with major responsibilities of participant communication and compensation.

• Conducted behavioral coding using Maternal Behavior Q-Sort (MBQS) methodology to assess maternal sensitivity.
• Enhanced team-wide rating reliability by conducting regular comparative analyses of behavioral coding.
• Gained foundational understanding of empirical assessments of children vocabulary and maternal attachment.

West Lafayette, Indiana, United States

• Contributed to a data science project focused on predicting cardiac arrests in hospitalized adults four hours before the medical event using two neural networks (Multilayer Perceptron and Long Short-Term Memory).
• Optimized performance of neural network models and applied them to a medical-surgical dataset.
• Developed a program that could be deployed in electronic healthcare management systems to provide real-time alerts for patients in immediate danger of cardiac arrest.

West Lafayette, Indiana, United States

• Provided goal-setting assistance, career counseling and role modeling to two first-year students in the College of Health and Human Sciences.
• Engaged in collaborative interactions with other mentors, mentees, faculty, and staff in the College of Health and Human Sciences to foster a positive and supportive environment.