activity
20192026
most citedUsing Machine Learning to Reduce Observational Biases When Detecting New Impacts on Mars

15 citations · 25 across the 6 of their papers we have counts for

collaborators

7 papers

cs.RO2026

STARS: From Spatiotemporal Dynamics to Social Representations in Human-Robot Interaction

Nathan Tsoi, Michael J. Munje, Tejas Oberoi +5

Robot navigation in dynamic, human-centered environments requires socially-compliant decisions grounded in robust scene understanding. Recent Vision-Language Models (VLMs) exhibit…

cs.CY2025

The Essentials of AI for Life and Society: A Full-Scale AI Literacy Course Accessible to All

Zifan Xu, Kristen Procko, Michael Munje +4

In Fall 2023, we introduced a new AI Literacy class called The Essentials of AI for Life and Society (CS 109), a one-credit, seminar course consisting mainly of guest lectures, whi…

cs.RO2025

ComposableNav: Instruction-Following Navigation in Dynamic Environments via Composable Diffusion

Zichao Hu, Chen Tang, Michael J. Munje +6

This paper considers the problem of enabling robots to navigate dynamic environments while following instructions. The challenge lies in the combinatorial nature of instruction spe…

cs.RO2025

SocialNav-SUB: Benchmarking VLMs for Scene Understanding in Social Robot Navigation

Michael J. Munje, Chen Tang, Shuijing Liu +6

Robot navigation in dynamic, human-centered environments requires socially-compliant decisions grounded in robust scene understanding. Recent Vision-Language Models (VLMs) exhibit…

cs.RO2024

Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning

Caleb Chuck, Carl Qi, Michael J. Munje +13

Reinforcement Learning is a promising tool for learning complex policies even in fast-moving and object-interactive domains where human teleoperation or hard-coded policies might f…

cs.LG2022★ 15 cited

Using Machine Learning to Reduce Observational Biases When Detecting New Impacts on Mars

Kiri L. Wagstaff, Ingrid J. Daubar, Gary Doran +5

The current inventory of recent (fresh) impacts on Mars shows a strong bias towards areas of low thermal inertia. These areas are generally visually bright, and impacts create dark…

cs.DM2019★ 10 cited

Reconfiguration of Connected Graph Partitions

Hugo A. Akitaya, Matthew D. Jones, Matias Korman +5

Motivated by recent computational models for redistricting and detection of gerrymandering, we study the following problem on graph partitions. Given a graph and an integer $k\…