• Through a series of video sessions, mentor students through a data science project of their choosing.• Create educational material and practice exercises to reinforce foundational data science knowledge necessary for the student's project. Walk through this material with the student, and point them to other potential sources of information.• Help students determine their project scale and avoid rookie mistakes, teaching statistical rigor and data integrity early.• Projects use skills ranging from data exploration to deep learning, including using Convolutional Neural Networks to identify basketball players by their photo, using Transformers to determine the sentiment of political tweets, and exploring the relationship between various variables, time, and Covid-19 hospitalizations.

• Leveraged a wide array of data to provide insights to pricing specialists and forecast key KPIs.• Oversaw projects from end-to-end, from wrangling and cleaning data to building models to productionalizing and automating end-results.• Built models to predict daily sold-fuel volume for each of 505 gas stations. Automated retraining as new data arrives.• Modeled previously unexplainable monthly profit and loss, identifying key variables and predicting future month values. • Developed easily accessible functions to query and clean API data from the Energy Information Administration.

• Develop weekly interactive Python notebooks to strengthen student understanding of important concepts in machine learning. Sometimes live-demo these notebooks, lecturing to a class of 145.• Grade assignments, including homework and a final project.• Individually mentor students through online questions and office hours.• Coordinate the work of 10 other teaching assistants, making sure deadlines are met and material releases are timely and organized.

• Created and managed HCD’s electroencephalography (EEG) lab, overseeing and executing processes such as protocol design, literature review, data collection, equipment maintenance, back-end data cleaning, and analysis.• Preprocessed, analyzed, and visualized both biometric and survey data on dozens of high-profile market research studies. Designed several experiments.• Analyzed data in Excel, SPSS, and R, using methods including PCA, Cluster Analysis, and MANOVA. • Preprocessed and coordinated time-series data-streams through Microsoft Access and SQL Server.• Automate signal processing techniques on biometric data via Acqknowledge and MATLAB. Such techniques included filtering, artifact detection/rejection/correction, Fourier transforms, and spectral power analyses.• Created coherent and aesthetic reports for clients. • Developed analytic algorithms and integrated new technologies into labs.• Helped organize Neuro U, an event to educate market researchers on neuromarketing. Spoke on the intersection of statistics, neuroscience, and market research, particularly in the context of EEG.• Published a scientific paper in Household and Personal Care Today (found here: https://www.teknoscienze.com/tks_article/shopping-habits-saving-retail-through-perception/).

• Examined the influence of social media posts on product affect and consumption.• Conducted literature reviews on social media marketing and cross-cultural consumption processes.• Used R and SPSS to analyze multivariate data, using methods including Factor Analysis and ANCOVA.• Presented findings at The College of New Jersey’s 2017 Celebration of Student Achievement.

• Used electroencephalography (EEG) to investigate various aspects of source memory.• Collected, organized, coded, and analyzed EEG data from student participants.• Mentored and supervised several younger student researchers, leading them through experimental protocol and educating them on fundamental concepts of EEG research.

• Managed a team of eight students to plan and oversee experimental research in cognitive psychology.• Designed and executed experiments. Analyzed data using ANOVAs and moderation analysis.• Presented findings at the Eastern Psychological Association’s 2016 and 2017 conferences, as well as at The College of New Jersey’s 2017 Celebration of Student Achievement.• Published a scientific paper in peer-reviewed journal Thinking Skills and Creativity (found here: https://www.sciencedirect.com/science/article/abs/pii/S1871187118300051).

• Collected and analyzed rodent data to assess mechanisms of Chemotherapy Induced Peripheral Neuropathy.• Assisted in various biological assays and procedures, such as Western Blots. • Presented findings to peers and faculty in the Center for Neuroscience.

• Experimentally assessed the potential for social media to encourage altruism and empathy, specifically in the context of the Syrian Refugee Crisis.• Designed and executed experimental protocol. Analyzed resulting data nonparametrically in SPSS.• Presented findings at the Eastern Communications Association’s 2016 James C. McCroskey and Virginia P. Richmond Undergraduate Scholars Conference.