The ISO Lab advances the science of intelligent systems by bridging optimization, machine learning, and adaptive modeling for impactful real-world solutions.

Openings

We currently have no openings in the ISO lab. However, if you are interested in any data analytics projects, have any specific ideas, and are looking for guidance, feel free to reach out.

Research Objectives

Intelligent Systems and Optimization (ISO) 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...

Team

Fahim Faysal

Phd Student (Dec 2025 - )

Rahath Ahmed

Phd Student (Dec 2025 - )

Caden Edward

MS Student (Sep 2025 - )

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