Last updated: May 2026

Ganesh Talluri

[about me]    [bookshelf]

Hi! I'm Ganesh Talluri and I'm currently based in Phoenix, AZ. I'm currently a systems engineering intern at Axon and a machine learning researcher.

My research interests span foundation models, representation learning, distribution shift, and machine learning for scientific discovery. I have worked on foundation models, spectral optimizers, distributed training, and machine learning under distributional shift. More recently, I have become interested in low-level systems and kernel optimization for efficient large-scale model training and inference.

Most recently, I was a Research Assistant at Midwestern University, advised by Prof. Andrew Lee, a Venture Fellow at Harvard University and a Don Lavoie Fellow at George Mason University. I was also an Associate Scholar at the Masason Foundation and the co-founder of Luxen LLC.

Feel free to reach out if you are interested in my work.

Ganesh Talluri

Education

Aug 2022 – May 2026
High School Diploma
  • Cumulative GPA: 4.7/5.0
  • 15 APs, 1510 SAT
  • Attended the #1 ranked public high school in the U.S. (U.S. News 2024)
  • National Merit Scholarship Commended Scholar, AP Scholar with Distinction x2, CollegeBoard National Recognition Program
  • President of Science Olympiad, Captain of Academic Decathlon, and President of USABO Club

Experience

Scottsdale, AZ | June 2026
Systems Engineering Intern
Phoenix, AZ | March 2024 – Present
Co-founder and CEO
  • Founded an applied-AI lab with a focus autonomous agent development.
  • Raised $48K in grant funding and equipment from 1517 Fund, SoftBank Group, and BizWorld.
  • Reached 5K+ active users and over 1.5M media views.
Remote | January 2025 - May 2025
Don Lavoie Fellow
  • Selected as 1 of 48 fellows nationwide (<10% acceptance rate) for the Mercatus Center's Exploring Complex Solutions Fellowship in political economy and governance.
  • Participated in 20+ faculty-led roundtables and seminars covering economics, institutional analysis, governance, and entrepreneurship.
  • Awarded a fellowship stipend and completed a 5-month academic program focused on markets, institutions, and innovation.
Glendale, AZ | Aug 2024 – March 2026
Research Assistant
  • Co-developed BONe deep learning software modules for training, prediction, and evaluation of microCT bone segmentation models.
  • Evaluated model robustness using 5-fold cross-validation, 3 random seeds per fold, and 30 architecture/backbone/patch-size benchmarking experiments.
  • Achieved high segmentation performance with U-Net and UNet++ models approaching 0.97 mean IoU.
  • Published in Frontiers in Bioinformatics.
  • Poster presentation at Anatomy Connected 2026.

Publications

1. Tatsuhiro Nakamori, Laura Gomezjurado Gonzalez, Ganesh Talluri, Ansh Tiwari, Hideyuki Kawashima, Ioannis Mitliagkas, Guillaume Rabusseau, Hiroki Naganuma. "Orth-Dion: Eliminating Geometric Mismatch in Distributed Low-Rank Spectral Optimization." arXiv (05/2026). [Paper]
2. Ganesh Talluri. "Glyde: A Domain-Aware, Topology-Biased Glycan Language Model for Viral Receptor Binding." SSRN (04/2026). [Paper]
3. Sora Nakai, Youssef Fadhloun, Kacem Mathlouthi, Kotaro Yoshida, Ganesh Talluri, Hiroki Naganuma, Ioannis Mitliagkas. "Revisiting Generalization Measures Beyond IID: An Empirical Study under Distributional Shift." arXiv (02/2026). [Paper]
4. Andrew H. Lee, Ganesh Talluri, Manan Damani, Brandon Vera Covarrubias, Helena Hanna, Julian M. Moore, Jacob Baradarian, Jeremy Chavez, Michael Molgaard, Beau Nielson, Kalah Walden, Thomas L. Broderick, Layla Al-Nakkash. "New software and 2D models to segment bone in micro-CT scans." Frontiers in Bioinformatics (01/2026). [Paper]
5. Ganesh Talluri, Ashwin Rokkam. "A Novel Multi-Omics Deep Learning Framework for Spatiotemporal Cerebral Cortex Localization & Expression." SSRN (05/2025). [Paper]
6. Ganesh Talluri, Ashwin Rokkam. "Sculpt: Novel Multi-Omics AI for Neuronal Modeling." medRxiv (04/2025). [Paper]

Projects

Agent Tree

A framework for structuring, visualizing, and orchestrating agent behavior in a more interpretable tree-based form.

Interactive Transformer

An interactive visualization project for understanding transformer internals, attention behavior, and model structure more intuitively.

More projects on my GitHub.

Awards, Fellowships & Funding

Fellowships & Selective Programs

Honors

Miscellaneous Awards/Distinctions

Skills

Programming & Systems Python, Java, JavaScript, CUDA, HTML/CSS
ML & Training Infrastructure PyTorch, Transformer Architectures, LLM Training, FSDP/ZeRO
Optimization & Theory Optimizer efficiency, Numerical Linear Algebra in ML, Communication Bottlenecks & Quantization (GPTQ, QAT), Probability & Statistics for Machine Learning
Applied ML & Bio Biomedical Imaging (microCT), Segmentation Models (U-Net, DeepLab, SegFormer), Computational Biology, Biological Sequence Modeling