- Location
- Los Angeles, California, United States
- Bio
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PhD in material science & engineering. I 3D-printed a metal to reduce the effects of osteoporosis in seniors with metal implants. As a materials sales representative, I received a request for a novel lubricant by an American manufacturing company that only provided requirements. After researching solutions, I negotiated a $1M deal to make the lubricant with a Chinese producer. I won the 2018 entrepreneurship award from the Materials Science & Engineering dept at Texas A&M and won the ASME South Scholarship award. At the 2018 ASEE conference, I presented a paper on “Interdisciplinary Research Experiences for Undergraduates”.
- Companies
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Woodland Hills, California, United States
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- Categories
- Lead generation Social media marketing Mobile app development Software development Machine learning
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Recent projects
CRM Strategy Blueprint for Multi-Segment User Engagement at FreeFuse
FreeFuse has a diverse user base that includes creators, educators, enterprise clients, and innovation partners. This project will help develop a CRM strategy blueprint that identifies key user segments, maps out lifecycle stages, and outlines communication cadences. Students will create a data-driven CRM engagement plan that addresses how to manage creators differently from enterprise contacts, and how to transition engaged leads into partner-level relationships. The focus will be on enabling FreeFuse to scale engagement without losing personalization.
Pathway Intelligence: Forecasting Interactive Journey Effectiveness on FreeFuse
FreeFuse is an AI-powered platform for building interactive, multi-path digital experiences. As the company expands into personalized content journeys and Agentic AI assistance, there is growing interest in understanding which types of interactive pathways lead to higher engagement and long-term user retention. This project will focus on analyzing and forecasting content journey effectiveness using structural data and behavioral metrics from FreeFuse pathways. In addition to traditional engagement data (e.g., completion rates, drop-offs), students will explore time-to-decision—how long a user takes between choice points—as a signal of content clarity, complexity, and user confidence. Learners will apply data science, predictive modeling, and visualization techniques to identify high-performing pathways, segment engagement styles, and forecast content success based on journey composition and user behavior.
SOC-2 Cybersecurity Compliance Assistance with Vanta
FreeFuse is seeking cybersecurity-focused learners to assist in achieving SOC-2 compliance using Vanta, our security compliance automation provider. This project will involve evaluating our security posture, reviewing policies, and assisting with technical implementation to meet compliance standards. Learners will work closely with Wendy Chen, FreeFuse’s Tech Lead, to identify vulnerabilities, document security controls, and ensure alignment with industry best practices. By completing this project, learners will gain hands-on experience in cybersecurity compliance, risk mitigation, and IT security governance, contributing to FreeFuse’s broader security infrastructure.
Strategic Development of AI-Driven Business Insights
The goal of this project is to develop a framework that enables businesses to extract actionable insights from AI-driven analytics. Students will explore how AI models can be leveraged to improve business decision-making, focusing on areas such as customer segmentation, predictive analytics, and data-driven strategy formulation. The project will involve building a prototype dashboard that visualizes AI-generated insights. This project is best suited for computer science, AI, or data analytics students interested in business intelligence and AI-driven decision-making.