Teaching — Autonomous Systems @ SJSU

Teaching at SJSU

Fall 2026: CS 156 (Introduction to Artificial Intelligence, 2 sections), CS 297 (Preparation for Writing Thesis)
Spring 2026: CS 298 (Master's Writing Project), CS 180 (Individual Studies)
Fall 2025: CS 146 (Introduction to Data Structures and Algorithms, 2 sections), CS 297 (Preparation for Writing Thesis), CS 298 (Master's Writing Project)
Spring 2025: CS 256 (Topics in Artificial Intelligence), CS 146 (Introduction to Data Structures and Algorithms, 2 sections), CS 297 (Preparation for Writing Thesis), CS 180 (Individual Studies)
Fall 2024: CS 256 (Topics in Artificial Intelligence, 2 sections), CS 146 (Introduction to Data Structures and Algorithms)

In addition to classroom teaching, I have advised graduate and undergraduate students through thesis, writing project, and independent study courses.

Assistant Professor, San Jose State University - June 2024 to Present
Lecturer and Graduate Teaching Assistant, University of California, Merced - Fall 2020, Spring 2021, and Spring 2023
Teaching Fellow, CETL (Center for Engaged Teaching and Learning), University of California, Merced - Fall 2021
Recitation Instructor and Graduate Lab Assistant, University of Colorado Denver and MERC Lab-CU Denver - 2018

Coordinator for Advanced AI Certificate; Research Internship Advisor , SJSU Research Foundation Corporation - January 2025 to present
Vehicle Diagnostics Engineer, Rivian Automotive, Palo Alto, CA - May 2023 to August 2023
Doctoral Research Assistant, University of California, Merced - 2019 to November 2023
Student Supervision, Advised 6 graduate students and 6 undergraduate students on AI research and industry internship projects, SJSU - September 2024 - present

Multi-Agent Navigation & Path Planning - SJSU & UC Merced, 2019–2025
Led research on robot navigation and motion planning, resulting in 4+ IEEE publications. Developed and evaluated classical (RRT, Bezier curves, convex optimization) and learning-based approaches for collision-free and efficient multi-agent systems. Designed simulation-based evaluation pipelines with potential for sim-to-real transfer in robotic environments.
Machine Learning for Healthcare - SJSU, 2024–2025
Conducted statistical analysis and machine learning research on lung adenocarcinoma, Alzheimer’s disease, and heart disease datasets. Developed predictive models to support interpretable clinical risk assessment and healthcare decision-making.
Traffic & Environmental Analytics - SJSU, 2025
Developed machine learning models for traffic congestion analysis, urban pollution assessment, and disease prediction. Applied XGBoost, LightGBM, and interpretable analytics to generate data-driven insights.
Machine Learning, NLP & AI Projects - SJSU, 2025–2026
Supervised and mentored 10 undergraduate students on projects involving machine learning, reinforcement learning, natural language processing, artificial intelligence, and data analytics. Developed predictive systems and applied quantitative research methods to large-scale datasets for real-world applications.

Modeling a Hierarchical Object - University of California, Merced, Fall 2019 (Computer Graphics)
Modeled a hierarchical object with five interconnected joints producing global and joint motion in three dimensions. Tools: C++, OpenGL.
Animating a Hierarchical Object - University of California, Merced, Fall 2019 (Computer Graphics)
Modeling and animating a hierarchical object with camera fly-through. Tools: C++, OpenGL.
Baseball Elimination Project - University of California, Merced, Fall 2019 (Advanced Algorithms)
Determined which teams have a chance to win a baseball league using a Max-Flow / Min-Cut algorithm. Tools: C++.
Minimum Spanning Tree (Kruskal, Prim, Dijkstra, Borůvka) - University of Colorado Denver, 2018 (Network Flow)
Applications: reducing data storage in amino-acid sequencing and network design (communication, electrical, hydraulic, computer, road).
Master’s Thesis - University of Colorado Denver
Numerical solution of the two-dimensional coupled viscous Burgers equation using a modified cubic B-spline differential quadrature method.