Mui Group @ ASDRP

AI Agents Research

Welcome to our research portal!

Our goals for this year's cohort include:

Learn foundations of AI/ML and agentic techniques
Appreciate the advances in LLMs and become familiar with toolchains for using them as consumers
Understand what is algorithmic bias, and in particular bias in AI/ML/LLMs
Study a few major algorithmic faux pas made by well intentioned engineers. We will study (possibly) unintentional consequences of algorithms leading to unfair biases.
Hypothesize how to mitigate as much as possible biases inherent in computer algorithms and data sets, as as to minimize harm to society.

We intend for you to engage in serious scientific investigation in groups, and to learn how to leverage each group member in your research. No major research is done alone in the real world. If you are interested in more specificity, here are our minimal research expectations for this group.

Research Assistant: this term, we have the pleasure of having Ananya G. and Theodore M. be our research assistants. They will be sharing their current research with you as well as trying to help each of your group research effort.

2026 Spring Schedule

Our first meeting will be January 3, 2026 (Saturday) to welcome the spring cohorts of researchers!

2026/01/03

Project Reviews
Vision
slides: [link]
repo: github.com/philmui/research2026
recording: [link]

Topics that we will try to cover through our weekend meetings in the next few months:

Neural Networks (ANN, CNN)
Transfer Learning: ResNet + Vision Transformers, VGG
Object Detection: YOLO, DETR
Generative Adversarial Networks (GAN) & Diffusion Models
Visual Language Models (VLM)
Keras & Tensorflow, PyTorch + HuggingFace

2026/01/10

Welcome back!
slides: [link]
repo: github.com/philmui/research2026
recording: [link]
Reading:
- Yann LeCun, Leon Bottou, Yoshua Bengio,Patrick Haner, GradientBased Learning Applied to Document Recognition, Proceedings of the IEEE, November, 1998. [link]

2026/01/17

slides: [link]
Neural Network Architecture & TensorFlow
repo: github.com/philmui/research2026
recording: [link]
Reading:
- Pragati Baheti. The Essential Guide to Neural Network Architectures. V7Labs, July 8, 2021. [link]

2026/01/24

slides: [link]
repo: github.com/philmui/research2026
recording: [link]
Reading:
- A Krizhevsky, I Sutskever, GE Hinton. ImageNet Classification with Deep Convolutional Neural Networks, Advances in neural information processing systems 25, 2012. [link]
- ICDAR 2026 Competition on Document Visual Question Answering. [link]

2026/01/31

slides: [link]
repo: github.com/philmui/research2026
project reviews:
- Racial bias in dermatology AI models (Pradyumna and team)
- MemAgent project review (Eric and team)
recording: [link]
Reading:
- Jiaqi Liu, Yaofeng Su, Peng Xia, Siwei Han, Zeyu Zheng, Cihang Xie, Mingyu Ding, Huaxiu Yao (2026) SimpleMem: Efficient Lifelong Memory for LLM Agents, arXiv:2601.02553 [cs.AI], Jan 29, 2026. [link]