The BIP Lab’s Chat2Learn program lacks the infrastructure to systematically analyze expanding SMS message repositories, making engagement tracking a manual, unscalable process. This project develops a unified analytic and visualization system to automate the extraction of behavioral indicators. Utilizing Python and Google BigQuery, we built a pipeline to classify sentiment, message types, and topics. Simultaneously, a Streamlit dashboard provides real-time visualization of participation trends. This solution enables the lab to monitor responsiveness at scale, streamlining operational decision-making and advancing research into data-driven interventions that support early childhood development and reduce social inequality.
Watch the team present this project at 2:11:38 in the session recording here.
Keywords: Natural Language Processing (NLP), Behavioral Science, Digital Intervention, Data Visualization, Parent Engagement, Automated Text Classification
Faculty Advisor
Shree Bharadwaj works at West Monroe, a management consulting company. As the AI Center of Excellence lead for M&A, he advises private equity and venture capital firms and C-level executives on value creation, post-close synergies, and data and analytics (BI/AI) strategies focused on business outcomes. In his previous executive leadership roles at Syndigo and IRI, he led the product ownership, data strategy, data science, next-gen platform and M&A integrations. His expertise revolves around growth and innovation, leadership and operational excellence. Additionally, his focus revolve around automation and driving decisioning using AI/ML, data engineering at scale using on-premise and cloud platforms, effective data visualizations, model-driven design, and algorithimic thinking.
Bharadwaj was elected to the Global Standards Architecture Board at GS1, where he worked with global industry leaders to develop standards, road maps, and governance and compliance requirements relating to food services, healthcare, retail, supply chain, and CPG/FMCG verticals. His experience spans across multiple industries that include AdTech, EdTech, Fintech, healthcare, MarTech, public safety, retail, and telecom in organizations that range from startups to Fortune 100 companies. His interests include His interests include Intelligent Systems and Robotics, Machine Learning at scale, Data Engineering, Data Visualization & Knowledge Engineering.