Aaron Tan

I recently finished my PhD at the University of Toronto, where I worked on robot control using RL, diffusion, and multi-modal language models with Dr. Goldie Nejat.

I am an incoming postdoctoral fellow at Stanford (Spring 2025). Previously, I was nominated as a PhD Apple Scholar in AI/ML.

Updated: 11/24

Email  /  X  /  CV  /  Resume  /  Scholar

We present a novel robot exploration map prediction method called Confidence-Aware Contrastive Conditional Consistency Model (4CNet), to predict (foresee) unknown spatial configurations in unknown unstructured multi- robot environments with irregularly shaped obstacles.

We introduce OLiVia-Nav, an online lifelong vision language architecture for mobile robot social navigation. By leveraging large vision-language models (VLMs) and a novel distillation process called SC-CLIP, OLiVia-Nav efficiently encodes social and environmental contexts, adapting to dynamic human environments.

We propose NavFormer, a novel end-to-end DL architecture consisting of a dual-visual encoder module and a transformer-based navigation network to address for the first time the problem of TDN in unknown and dynamic environments.

The first Macro Action Decentralized Exploration Network (MADE-Net) using multi-agent deep reinforcement learning to address the challenges of communication dropouts during multi-robot exploration in unseen, unstructured, and cluttered environments.

The first extensive investigation of mobile robot inference problems in unknown environments with limited sensor and communication range and propose a new taxonomy to classify the different environment and task inference methods for single- and multi-robot systems.

The development of a novel sim-to-real pipeline for a mobile robot to effectively learn how to navigate real-world 3D rough terrain environments.

A 1:6 scale, multi-wheeled mobile robotic platform with independent suspension, steering and actuation for off-terrain operations.

• Accelerating the scholarship application process via LLM agents to help students secure funding while focusing on their studies.

• Selected by Microsoft Startup Hub Program, receiving grants worth $150k.

• An all-in-one service built in to iMessage aimed at lowering the barrier of entry for LLMs and Generative AI.