cv

Exchange Scholar

National University of Singapore

• Awarded a merit-based placement through a highly competitive, university-wide application process.
• Graduate AI Coursework: Neural Networks & Deep Learning II (audit).
• Graduate Neuro Coursework: Frontiers in Neurotechnology (audit), Behavioral & Cognitive Neuroscience (audit).
• AI Coursework: AI Planning & Decision Making, Mind & Machine.
• Neuro/Bio Engineering Coursework: Bioinformatics, Organoid Engineering (audit), Mind & Machine.

Bachelor of Science in Computer Science

University of Wisconsin-Madison

• GPA: 3.79/4.0
• Honors: Letters & Science Dean's List, Honors in Computer Science Program, Letters & Science Honors Program
• Graduate AI Coursework: Foundation Models, Learning-Based Image Synthesis, Advanced Robotics, Advanced Reinforcement Learning, Advanced Seminar (audit), Theory of Multi-agent Machine Learning, Mathematical Foundations of ML (upcoming).
• AI Coursework: Directed Study on LLMs with Dr. Sala, Game AI, Artificial Neural Networks, Artificial Intelligence, Game Theory & Learning.
• Neuro Coursework: Molecular & Cellular Mechanisms of Memory, Neurobiology, Computational Neuroscience (upcoming), Nanotechnology in Neuroscience (upcoming).

NeuroAI Research Mentee

Dr. Michael Levin (Tufts University, Biology) - Allen Discovery Center

• Invited to mentorship from Dr. Levin to extend "Structural Plasticity as Active Inference" research [3].
• Designing embodied agents where the computational cells are the device and investigating model robustness to damage & topological changes.

NeuroAI Research Collaborator & AI Lead

Dr. Kumar-Singh (Tufts University, Neuroscience)

• Personally recruited by Dr. Kumar-Singh to serve as the AI lead for two proposed biomedical ventures.
• Authored comprehensive technical roadmaps analyzing competitive landscape, resource requirements, and strategic path for (1) a genAI platform for de novo AAV gene-therapy vector design & (2) a clinically-tailored AI vision aid for patients with AMD & Glaucoma.

Foundation Models Researcher

Dr. Sala's Sprocket Lab

• Researching and implementing novel methods for editing representations within large language models including coarse-to-fine pipelines.
• Worked with big data, GPU clusters, and high throughput systems.
• Publications from this research: [7], [8]

Founding Director & Research Lead

Wisconsin Neuromorphic Computing and NeuroAI Lab

• Established and direct a university-sanctioned entity to explore the intersection of neuroscience and artificial intelligence.
• Secured formal funding, dedicated space, support from Dr. Akhilesh Jaiswal as advisor, partnership with NeuroAI startup FinalSpark, and administrative support from UW-Madison.
• Delivered lectures on neuroAI (e.g., STDP) to audiences of over 100 including graduate students and professionals.
• Mentoring 15 researchers from initial project proposals to research papers and advised 100.
• Publications from this research: [2], [5], [3]

Reinforcement Learning Researcher

Dr. Hanna's Badger RL Lab

• Designing and implementing reinforcement learning policies to train physical robots for autonomous soccer, focusing on multi-agent coordination.
• Key Accomplishments: Top ranking in RoboCup International Robotics Competition (3rd place in the Standard Platform League 2025; 1st place in the Challenge Shield League 2024).
• Publications from this research: [1] (in collaboration with Dr. Berland's Lab), [6]

Reinforcement Learning Researcher

Dr. Berland's Complex Play Lab

• Architecting communication strategies between agents in multi-agent reinforcement learning (MARL) environments incorporating world models.
• Researched and developed a novel adversarial co-evolution framework to automatically generate curriculum for MARL.
• Publications from this research: [1] (in collaboration with Dr. Hanna's Lab), [4]

Software Engineer (Research Engineer)

Stealth Mode Startup

• Spearheaded the complete research and development lifecycle for a novel artificial intelligence system, taking the project from an ambiguous high-level goal to a fully deployed, production-ready system.
• Devised, prototyped, and implemented a custom, hardware-aware algorithm that significantly outperformed SOTA approaches by over 100x in accuracy on the system's hardware.

Quantum Software Intern (Research Engineer)

HRL Hughes Research Laboratories

• Architected a multi-pass compiler in Common Lisp to generate optimized binary directly for a custom quantum control processor (the QICK tProcessor ISA), creating a low-level pathway for direct FPGA execution to maximize performance and control flexibility.
• Designed and implemented a custom assembly language to bridge high-level experimental logic with the hardware instruction set, enabling advanced compiler optimizations, automatic resource allocation, and precise picosecond-level timing calculations.
• Awarded a return offer after each period with HRL in recognition of significant technical contributions and research impact.

Quantum Software Intern (Research Engineer)

HRL Hughes Research Laboratories

• Engineered a production-ready implementation of an exact pattern matching algorithm within the Quilc quantum compiler, translating a novel theoretical method into a high-impact optimization tool.
• Reduced quantum circuit depth by up to 37%, shortening execution time on quantum hardware, directly enhancing algorithmic fidelity by mitigating qubit decoherence.
• Project Link: https://github.com/quil-lang/quilc/tree/master/src/match
• Awarded a return offer after each period with HRL in recognition of significant technical contributions and research impact.

[1] Communicating Plans, Not Percepts: Scalable Multi-Agent Coordination with Embodied World Models

Brennen A. Hill , Mant Koh En Wei , Thangavel Jishnuanandh

In proceedings of NeurIPS 2025 Workshop on Scaling Environments for Agents; in NeurIPS 2025 Workshop on Embodied World Models for Decision Making; and in NeurIPS 2025 Workshop on Optimization for Machine Learning

Developed a novel intention communication framework in MARL that achieved >96% success in a complex coordination task using a learned world model for latent trajectory planning and a self-attention mechanism to encode and share agent intentions, significantly outperforming emergent protocols.

[2] The Geometry of Cortical Computation: Manifold Disentanglement and Predictive Dynamics in VCNet

Brennen A. Hill , Zhang Xinyu , Timothy Putra Prasetio

In proceedings of NeurIPS 2025 Workshop on Symmetry and Geometry in Neural Representations and in NeurIPS 2025 Workshop on Interpreting Cognition in Deep Learning Models

Designed VCNet, a novel architecture emulating the primate visual cortex, achieving state-of-the-art accuracy on two vision benchmarks with over 10x greater parameter efficiency than standard models.

[3] Structural Plasticity as Active Inference: A Biologically-Inspired Architecture for Homeostatic Control

Brennen A. Hill

In National Science Foundation (NSF) Workshop on Brain-Inspired Dynamics for Engineering Energy-Efficient Circuits and Artificial Intelligence

One of two undergraduates selected to present alongside principal investigators. Developed a novel architecture that integrates synaptic and structural plasticity, demonstrating that computational agents can solve tasks by physically migrating processing units to minimize local prediction error, driven solely by an intrinsic, active inference-based objective.

[4] Co-Evolving Complexity: An Adversarial Framework for Automatic MARL Curricula

Brennen A. Hill

In proceedings of NeurIPS 2025 Workshop on Scaling Environments for Agents

Invited to attend, then submitted the paper. Developed a novel architecture that integrates synaptic and structural plasticity, demonstrating that computational agents can solve tasks by physically migrating their processing units on a grid to minimize local prediction error, driven solely by an intrinsic, active inference-based objective.

[5] The Physical Basis of Prediction: World Model Formation in Neural Organoids via an LLM-Generated Curriculum

Brennen A. Hill

In proceedings of NeurIPS 2025 Workshop on Scaling Environments for Agents and in NeurIPS 2025 Workshop on Embodied World Models for Decision Making

[6] Generative World Models of Tasks: LLM-Driven Hierarchical Scaffolding for Embodied Agents

Brennen A. Hill

In NeurIPS 2025 Workshop on Embodied World Models for Decision Making

[7] HEFT: A Coarse-to-Fine Hierarchy for Enhancing the Efficiency and Accuracy of Language Model Reasoning

Brennen A. Hill

In review

[8] Breaking to Build: A Threat Model of Prompt-Based Attacks for Securing LLMs

Brennen A. Hill , Surendra Parla , Venkata Abhijeeth Balabhadruni , Atharv Prajod Padmalayam , Sujay Chandra Shekara Sharma

In review

Representation Fine-Tuning for Vision-Language Models

• Investigated Representation Fine-Tuning, a parameter-efficient fine-tuning method, on a vision-language model (nanoLLaVA) for a spatial reasoning task.
• Co-authored a research paper demonstrating that ReFT achieved accuracy comparable to LoRA (65.7% vs. 66.0%) while using nearly 10x fewer trainable parameters (0.019% of the model).

Reinforcement Learning for Quadruped Roller Skating

• Co-authored a research paper on training a Unitree Go1 quadruped robot with passive wheels to skate using reinforcement learning in the Isaac Gym simulator.
• Developed an RL policy that resulted in emergent complex behaviors, including automatic gait switching from a stable diagonal gait at low speeds to a dynamic galloping gait at high speeds (3 m/s).

Presenter

National University of Singapore School of Computing Showcase

• Selected to present a self-developed 3D videogame to an audience of over 100 students and faculty.
• The game featured AI-driven monster agents that used complex pathfinding algorithms to navigate dynamic 3D environments and make strategic targeting decisions; complex player abilities including harvesting resources, crafting equipment, and placing structures; and representing a unique mix of PvE, survival, resource management, and tower defense.

Winner (awarded $2,500)

Hack Midwest 2024

• Won (of over 300 developers), awarded $2,500, and noted for Best Enterprise-Scale Business Solution.
• Designed and built Badger Vision, an AI-powered assistive tool to help individuals with prosopagnosia (face blindness) by providing real-time audio cues for face identification and emotion recognition.
• Implemented a computer vision pipeline using deep learning (convolutional neural networks) to identify individuals and classify their emotional expressions from a live low-level video stream.

Honorable Mention

NASA International Space Apps Challenge 2024

• Received a global Honorable Mention, only awarded to 19 of 93,520 (0.02%) global participants.
• Processed large-scale NASA/ESA astronomical data and implemented the 3D visualization, rendering, and user interface.
• Won the Chicago hackathon and advanced to global finals; additionally awarded Best Presentation.

3rd Place (Standard Platform League 2025), 1st Place (Shield 2024)

RoboCup International Robotics Competition

• Achieved top placements in a competition that serves as an international scientific benchmark for multi-agent AI in adversarial environments, using fully autonomous, identical NAO robots.
• Guided the team's technical strategy by conducting a comprehensive literature review on multi-robot soccer, leading to a publication on language-driven world models [6]
• Designed and implemented the multi-agent coordination protocols for collaborative passing that formed a component of our team's winning strategy, applying concepts from my research [1]

Dean's List, Honors in Computer Science Program, Letters & Science Honors Program

University of Wisconsin-Madison

Valedictorian of 600, 4.6/4.0 GPA, International Baccalaureate Diploma, State Golden State Seal Merit Award, State Seal of Biliteracy, 4-year Scholar Athlete

Agoura High School

Peer Reviewer

Served as a peer reviewer upon nomination by the respective program committees:

• AAAI 2026 Workshop on Neuro for AI & AI for Neuro: Towards Multi-Modal Natural Intelligence (NeuroAI)

Peer Reviewer

Served as a peer reviewer upon nomination by the respective program committees:

• Neurips 2025 Workshop on Scaling Environments for Agents (SEA)
• Neurips 2025 Workshop on Aligning Reinforcement Learning Experimentalists and Theorists (ARLET)
• Neurips 2025 Workshop on Interpreting Cognition in Deep Learning Models (CogInterp)
• Neurips 2025 Workshop on Efficient Reasoning (ER)
• Neurips 2025 Workshop on Data on the Brain and Mind Findings (DBM)
• Neurips 2025 Workshop on Symmetry and Geometry in Neural Representations (NeurReps)

Journal Club Host and speaker

• Presented a critical analysis on the origins of intelligence, synthesizing concepts of scale-free cognition and developmental bioelectricity, and referencing work by Dr. Levin to discuss how higher-level agency evolves from the homeostatic, problem-solving capabilities of cellular collectives.
• Facilitated a post-talk discussion with researchers on the future of synthetic biological intelligence and the applications of the mechanisms presented.
• Invited to give future talks in recognition of the presentation's quality and the engaging discussion.

Co-Founder

Madison Machine Learning

• Co-organizing and growing a new community hub connecting machine learning researchers.
• Co-leading weekly technical deep-dives and critical discussions on SOTA papers in machine learning.

Head of AI

Badger Solar Racing

Executive Boardmember and Webmaster

AI Club

• Organized projects, designed a website, and managed resources to support students interested in artificial intelligence.

Vice President and Vice-Captain

Badger Ballroom Dance Team

• Organized and lead instructional workshops in collaboration with faculty and professionals across multiple universities and companies.

Executive Boardmember and Webmaster

Ballroom Association UW-Madison

• Designed and built a user-focused website to facilitate member communication.

Volunteer Leadership

Slow Food UW

• Mobilized and coordinated a team of 30 dormitory students to partner with Slow Food UW.
• Prepared and distributed pay-what-you-can meals to address local food insecurity.

Science Tutor

Agoura Highschool Science Honors Society

• Taught students advanced science concepts, raising understanding and exam scores.

Math Tutor

Agoura Highschool Math Honors Society

• Taught advanced math concepts to students, improving understanding and exam scores.

Lead Developer and Founder

Thunder Warrior Gaming

• Designed, built, self-published, and marketed the video game Thunder Warrior: Genesis.
• Achieved net profit.
• Engineered a custom game engine, multiplayer server, database, 3D models, and animations.