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ML, AI, Robotics
1: Deep Learning Workshop Series
Content: Interested in learning how ChatGPT and DALLE work? Join us for weekly presentations/projects covering exciting areas like neural networks, CNNs, transformers, and diffusion models! We will cover fundamentals and applications, giving you the skills to tackle real-world deep learning challenges in vision and language. Expect to spend 1 hour per week attending meetings, with extra time if you want to complete the projects.
Prerequisites: Basic programming experience (recommended)
Group Type: Hybrid (Reading + Project)
Mentors: Justin Sasek, Harshal Bharatia
Curriculum
Intro to Machine Learning and Neural Networks (3 weeks)
Intro to Computer Vision (CNN) (2 weeks)
Intro to Transformers (3 weeks)
Miscellaneous - Diffusion, VAE, RL, etc. (3 weeks)
https://docs.google.com/document/d/1-AgajxComiV7jNYe-l6Zog8ZUwlM3bfHVuW76Tq4cv8/edit?usp=sharing
Time/Location: Mondays at 5 pm. First meeting is in GDC 4.304 on 2/3
2: Reinforcement Learning
Content: Dive deep into deep reinforcement learning theory and practice. Learn how to design better RL systems for applications in robotics and games. We will discuss various seminal works and implement algorithms!
Prerequisites: Knowledge of RL, Python programming (required); Knowledge of how RL works, some basic experience implementing RL algorithms (recommended)
Group Type: Reading
Level: Advanced
Mentors: Sarthak Dayal
3: Agentic AI Systems
Content: Our group will explore agentic AI systems—agents that not only act but also communicate with humans and other agents while grounding their actions in real-world contexts. Through weekly paper readings and discussions, we’ll examine how such agents are defined (with LLMs, vision models, generative models, etc.), how to organize and orchestrate an agentic system with multiple modules, and the challenges that arise in their design. For those interested, there will also be opportunities to move beyond discussion and pursue hands-on research.
Prerequisites: Python Programming (required); Basic NLP knowledge, Development experience on LLM APIs, Ideally experience in agentic frameworks like Langchain (recommended)
Group Type: Reading
Level: Advanced
Mentors: Lunyiu Nie
Curriculum: https://docs.google.com/document/d/1LouzuBuzpQdZChs5E5GDz4wBj05nAfRb/edit#heading=h.p3j82qs77tly
4: Natural Language Optimization for LLM
Content: Natural‑Language Optimization (NLO) is any procedure that (a) elicits natural‑language evaluations of an LLM’s behavior—critiques, rationales, rules, rubrics, step‑level diagnoses—and (b) uses those textual signals to rewrite the controlling prompt(s), usually iteratively. The optimization variable is human‑readable text; the gradient signal is textual.
Prerequisites: Basics of LLM Prompting + Evaluation (recommended)
Group Type: Reading
Level: Advanced
Mentors: Anish Acharya
5: Preference-aware Robot Policies
Content: How can we build robots that learn to be our perfect partners, adapting to our unique habits and preferences instead of just following rigid commands? This reading group will explore the foundational concepts of preference-aware robotics, discussing how robot policies learn from human feedback and demonstration to become personalized collaborators.
Prerequisites: Basic understanding of transformer, diffusion, etc. (no need to implement, just know the gist)
Group Type: Reading
Level: Advanced
Mentors: Michael Zheng
6: Scientific machine learning
Content: Most of the step function progress in AI has been towards discrete sequence modeling. However, real problems in science and engineering are nondiscrete and require considerations like numerical precision. The purpose of this group is to understand what it takes and to make contributions toward the goal of moving scientific machine learning (sciml) forward.
Prerequisites: Has trained machine learning models (required); Numerical analysis course, knowledge of PDEs (recommended)
Group Type: Project
Level: Advanced
Mentors: Jeffrey Lai
Systems, Arch
7: Introduction to Architecture
Content: Want to learn about the modern features that make modern CPUs so fast? This is the group for you. This semester we will focus on reading and discussing the cutting edge work in academia that pushes the bounds of modern architecture.
Group Type: Reading
Level: Beginner
Mentors: Christopher Hill
8: Introduction to Operating Systems
Content: The operating system is the fundamental building block upon which all other computation relies, but how much thought do you give it on a daily basis? Understanding how the operating system works is applicable and helpful to anybody who uses a computer. In this group we will learn about the ins and outs of operating systems, the history of their design and how they’ve evolved over time, and modern developments. We will read landmark papers as well as newer developments in the field.
Group Type: Reading
Level: Beginner
Mentors: Sasha Huang
Curriculum: https://docs.google.com/document/d/14BPc8hqZKNSyj7jr_cNf8uH3NNUKvvexC-C4KCx3-Zs/edit?usp=sharing
9: Introduction to Security
Content: Exploring the world of security. We will read classic and modern papers, learning the techniques behind major exploits and the defenses built against them.
Prerequistes: Completion of 429 or equivalent or existing knowledge (required)
Group Type: Reading
Level: Beginner
Mentors: Caleb Eden
10: Distributed Systems
Content: Learn about how companies manage massive amounts of data and handle web-scale traffic. Distributed systems are the underpinning of all large-scale infrastructure, and these systems also introduce difficult (and sometimes impossible) problems for us to dissect.
Prerequisites: Some data structures knowledge (required)
Group Type: Reading
Level: Beginner
Mentors: Nicolas Garza
11: Distributed Training / SysML
Content: This group will go over SysML, covering topics such as LLM distributed training, optimizing ML infrastructure for training and inference, and other topics.
Prerequisites: Taken 429/439 (required); Students are expected to already have a good understanding of LLMs and a general idea of how they are currently deployed (recommended)
Group Type: Reading
Level: Advanced
Mentors: Nathan Barry
Curriculum: SOME of the papers will come from here:
https://utnslab.github.io/fa25-adv-topics-in-sys-genai/reading-list/
This gives a general idea of the topics we will be covering.
Theory
12: Quantum Computing
Content: This reading group will introduce students to the foundations of quantum computing, from linear algebra and the postulates of quantum mechanics to quantum gates and circuits. We will then explore landmark topics such as the Quantum Fourier Transform, quantum search, and error correction, building up to modern techniques like quantum signal processing and variational algorithms.
Prerequisites: Taken 429, 439 (required); Linear algebra, discrete math/mathematical maturity, such as understanding proofs (recommended)
Group Type: Reading
Level: Beginner
Mentors: Satvik Duddukuru
13: Computational Modeling
Content: In this beginner-friendly group, we will broadly explore the field of computational modeling: the kind of work done at the Oden Institute. We will practice both reading papers and coding simple projects. Emphasis will be on applications in storm surge modeling, my area of research, but other groups and topics will be considered.
Prerequisites: Programming fundamentals, calculus, understanding of basic matrix operations, willingness to learn new things (required); Python, vector calculus, linear algebra, differential equations, interest in domain outside of computer science, e.g. physics (recommended)
Group Type: Project
Level: Beginner
Mentors: Ashton Cole
Curriculum: https://github.com/ashtonvcole/DiRP/blob/main/Fall%202025/syllabus.pdf
14: The Lean 4 Language
Content: This DiRP is a chance to learn about the Lean4 language and what makes it useful for doing mathematics, as well as potentially new ways of thinking about programming. If you're a math nerd, programming languages nerd, or want to become one, you should join this group!
Prerequisites: Currently taking or have taken discrete mathematics, moderate programming background (recommended)
Group Type: Reading
Level: Beginner
Mentors: John Jennings
Curriculum: https://docs.google.com/document/d/12RbfLvY4C_M8SQu9dHxTxo_BlEbseTaQcFwpheAJjGE/
Miscellaneous
15: Research Skills
Content: This is the weekly meeting for the Research Skills DiRP group, in partnership with the LDOS grant to help students build engineering skills for research. In this group, students will build familiarity with Python scripting, Linux tools, data analysis, conducting experiments, version control, and effective use of AI tools. Graduate students and researchers from LDOS will assist the students during the 1 hour tutorial.
Prerequisites: Willingness to learn, some Python would be useful (recommended)
Group Type: Project
Level: Beginner
Mentors: Aryan Khatri
16: Critical Human-Computer Interaction Studies
Content: This reading group will explore how power structures are embedded in technological design. We’ll discuss who benefits from a technology, who might be excluded, and how technology shapes society and culture. We’ll draw on feminism, postcolonial theory, and critical race studies to theorize ways of designing technologies that are more just, inclusive, and reflective of diverse perspectives.
Prerequisites: Ideally some background in CS/ECE/IS or related STEM fields. Must be willing to critically engage with academic papers and lead a group discussion for a week (required)
Group Type: Reading
Level: Beginner
Mentors: Hana Frluckaj
17: Technologies in the Market
Content: Learn about technologies used in quantitative finance such as microwave transmissions and FPGAs.
Group Type: Reading
Level: Beginner
Mentors: Hudson River Trading
*tentative group with limited seats
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