Openings

I am actively seeking Ph.D. students to join my group in Fall 2025 or Spring 2026. Interested applicants are encouraged to fill out this form: Google Form

The next communication will likely be from my side if our interests and plans align.

Research Objectives

Industrial AI Lab is centered on tackling the challenges of developing advanced machine learning methodologies that are more accurate, adaptable, secure, and efficient. We drive innovations across critical engineering and science domains, such as agriculture, healthcare, manufacturing, and more, to improve our lives.

Research Areas

Illustration of Domain Adaptation

Improving Model Robustness

Given the widespread use of sensors and diverse data collection protocols, multi-source domain adaptation presents a promising solution for enhancing model robustness. We intend to explore the following areas for this purpose:

Robust Architecture Design: Creating architectures that can handle variations and resist adversarial conditions to ensure consistent performance.
Modular Components: Utilizing modular components that can be fine-tuned or replaced, allowing the model to adapt to different tasks or environments.

Tackling Challenges in Multi-modal Learning

Multi-modal learning involves integrating and processing information from multiple data types (modalities) to create more comprehensive and effective machine learning models. These modalities include text, images, audio, video, sensor data, and more. By leveraging complementary information from various modalities, multi-modal models can better generalize new and unseen data.

Long-term Plan

We strive to move towards the next generation of industrial AI by exploring these areas...

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