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Teanna "Anna" Sims

BSE in Data Science

University of Michigan, College of Engineering

My Blog Learning Resources

About Me

Hi, I'm Anna and I study data science at the University of Michigan exploring different ways computers and AI can interact with the real world. Currently, I am working on two exciting projects focused on research and development in multi-agent reinforcement learning and pose estimation for real-time video analysis.

I've had a pretty interesting journey so far when it comes to my professional pursuits. I've interned as a design engineer, quantitative trader, and even managed an XR lab. I've also been lucky enough to be part of some really cool research projects, from analyzing carbon emissions in developing countries to exploring applications of deep learning in computational finance, and exoplanet characterization.

Principles I Live By

Start Before You're Ready

Perfectionism is the enemy of progress. I've learned that waiting until I feel "ready" often means missing opportunities. The most valuable growth comes from jumping in, making mistakes, and iterating quickly.

See It Through to the End

Starting projects is easy; finishing them is hard. I commit to completing what I begin, even when motivation wanes. The discipline of following through has taught me more than any class ever could.

Create More than You Consume

In a world of endless consumption, I strive to be a contributor rather than just a consumer. Whether it's code, research, or just building something cool.

Try the Hard Thing

I deliberately seek out challenges that push my limits. The problems worth solving are rarely easy, and I've found that embracing difficulty—rather than avoiding it—leads to the most rewarding breakthroughs.

Career Goal

My ultimate goal is to become a Solutions Architect for Generative AI systems. This role would combine my technical expertise in machine learning with my passion for solving complex problems and building systems that can transform how people work and create.

Research Interests

  • Real-time Video Analysis
  • Cooperative Multi-agent Systems
  • AutoML for Predictive Modeling

What I'm Working On Now

Creating New Agent Architectures for Concordia

Summer 2025

Developing and open-sourcing innovative language model agent architectures for Google DeepMind's Concordia framework to advance cooperative AI research and lower barriers to entry for researchers.

DeJaye

Ongoing

Developing an intelligent DJ system for NeurIPS 2025 Creative AI Track that processes real-time depth video through pose estimation and GNNs to interpret crowd dynamics, automatically curating Spotify playlists responsive to audience mood.

CtrlZLearn

Ongoing

Aggregating opportunities and learning resources for aspiring SWE, MLE, and Data Scientist.

CodePath: Intermediate & Adv Technical Intervier Prep

Summer 2025

12 week program teaching students to ace technical interviewing and give them a preview of real-world challenges in the industry.

Projects

Concordia Agents
Concordia Agents
2025

architecture for cooperative multi-agent systems

Part of: Google DeepMind, Google Summer of Code

ArchaeoVLM
ArchaeoVLM
2025

VLM capable of detecting archaeological features in the Amazon

Part of: OpenAI to Z Challenge

DeJaye
DeJaye
2025

Event Music Curation using Real-Time Video Analysis

Part of: NeurIPS 2025 Creative AI