About Jangara

I'm a senior computer engineering student at Fort Lewis College (math and business minors), and most of my work sits at the same junction: taking a capable model and making it do something in the physical world. Right now that means leading sim-to-real research on the Booster K1 humanoid under Dr. Yiyan Li — a system where you describe a task in natural language and the robot executes it. The architecture is two-tiered: a vision-language model handles perception and task planning at about 1 Hz, while a reinforcement-learned locomotion policy trained in NVIDIA Isaac Sim runs the legs at 50 Hz.

Before the humanoid, the pattern was already set. I led a four-person team building an autonomous 18-DoF hexapod that competed in NASA's Colorado Robotics Challenge at the Great Sand Dunes. I spent a summer under Dr. Kevin Wedeward reviving two dormant industrial robots — tracing a Sawyer's boot failure to a dead CMOS battery, rebuilding its OS from a corrupted encrypted SSD — and then built a YOLOv8 thermal-inspection pipeline on top of them. Under Dr. Matthew Welz I shipped a data platform that Fort Lewis's radio station staff use daily, then prototyped its applied-AI layer. Across three faculty labs, the lesson kept repeating: the model is rarely the hard part; the seams are.

The question that drives me is Moravec's paradox — why the hardest problems in AI turned out to be the ones a toddler solves effortlessly, and how we close the gap between what robots do in simulation and what they do in the real world. That's the problem I want to spend a career on: robots that generalize to new tasks in the physical world the way foundation models generalize in language.

I also come from an entrepreneurship track — co-founder and president of FLC's Entrepreneurial Ventures Association (New Registered Student Organization of the Year), a Goldman Sachs Emerging Leaders alum, and a business minor by design. I care about the sectors where physical AI could matter most: housing, food and agriculture, logistics, healthcare, manufacturing, and space infrastructure. Graduate school is how I get the theoretical depth to build in those spaces at a level I can't reach yet.