Jianheng (Jaden) Hou

Hi, I’m currently a Senior Machine Learning Engineer at Tesla, where I lead initiatives in AI-powered smart automotive manufacturing. My work spans Multimodal Models, AI Agents, Recommendation Systems, ML Infrastructure, and Data Science—driving over $10M operational efficiency for auto manufacturing. In 2024, I was honored as one of the three most impactful contributors to Tesla Manufacturing.

Prior to Tesla, I worked at Comcast within the Enterprise Business Intelligence organization. As a Senior Data Scientist, I participated in a strategic rotation program, delivering end-to-end machine learning and data science solutions for Xfinity’s product growth, customer experience, pricing strategies, and workforce optimization.

Before that, I was a Research Data Scientist at Alpha Edison, a data-driven venture capital firm. I developed large-scale text mining pipelines and anomaly detection and causal inference frameworks to identify latent industry pain points and emerging market signals, supporting over $40M in investments across high-growth U.S. startups.

Earlier in my career, I served as a Research Assistant at the Information Sciences Institute – Center on Knowledge Graphs, where I contributed to the DARPA-funded THOR Project. This work focused on real-time global crisis management via dynamic knowledge graphs and situational awareness systems, and was successfully transitioned into U.S. Department of Defense applications.

I earned my M.S. in Applied Data Science from the Viterbi School of Engineering at the University of Southern California.

Research Interests

My interdisciplinary experience shapes a unique research perspective that blends product-driven data science intuition, industrial-scale ML engineering, and cutting-edge academic innovation. I focus on translating advanced AI concepts into real-world, high-impact solutions in complex enterprise settings. Specifically, my interests lie in:

• Multimodal Foundation Models — aligning proprietary domain data (text, image, sensor) to build scalable large model to enable personalized recommendation systems and classification applications
• AI Agents — orchestrating enterprise-level agentic workflows through tool and GraphRAG
• Applied Data Science — conducting user behavior analysis, building decision dashboards, and running causal inference experiments to guide product strategies
• Machine Learning Systems — designing and deploying full-stack ML pipelines (online/offline), including infrastructure, monitoring, and model lifecycle management

Life Beyond the Terminal

Outside of work, I thrive on pushing physical boundaries the same way I tackle technical ones:

• 🏔️ Alpine skiing — carving steep terrain with speed and precision
• 🌊 Scuba diving — free diving and catching lobster to share with friends
• 🏕️ Camping — finding stillness and clarity deep in nature
• 🏋️ Strength training — sustaining energy and balance with a daily endorphin boost

These pursuits keep me grounded, focused, and ready for the next challenge—whether in code or on a mountain.