Brandon Rozek

Photo of Brandon Rozek

PhD Student @ RPI studying Automated Reasoning in AI and Linux Enthusiast.

Quick List of Publications

Broad Research Interests: Automated Reasoning, Automated Planning, Artificial Intelligence, Formal Methods

Planning under Uncertainty

During my PhD I have been primarily focused on investigating planning and sequential decision making under uncertainty through integrative methods:


Underlying my work in artificial intelligence and cryptography is computational logic. In that regard, I have been able work on problems from the underlying logic formalisms, unification algorithms, to building tools for interactive theorem provers.

Related Notes:

Symbolic Methods for Cryptography

Worked with Andrew Marshall and others in applying term reasoning within computational logic towards cryptography. This collaboration was previously funded under an ONR grant. We are interested in applying techniques such as unification and term rewriting to the following areas:

Together we built CryptoSolve, a symbolic cryptographic analysis tool, and made it publically available on GitHub. I wrote the term algebra and rewrite libraries, and contributed to the mode of operation library and some unification algorithms. I still help maintain the codebase. We previously presented our work at UNIF 2020 (slides), FROCOS 2021 (slides), WRLA 2022 (slides), and GandALF 2022.


Group Website: https://cryptosolvers.github.io

Reinforcement Learning

During my undergraduate degree, I worked with Dr. Ron Zacharski on making deep reinforcement learning algorithms more sample efficient with human feedback.

In my experimentation, I built out a Reinforcement Learning library in PyTorch.


RL Library on Github Interactive Demonstrations Library Undergraduate Honors Thesis (Eagle Scholar Entry)
Undergraduate Honors Defense QEP Algorithm Slides More…

Dr. Stephen Davies guided my study of the fundamentals of reinforcement learning. We went over value functions, policy functions, how we can describe our environment as a markov decision processes, and other concepts.

Notes and Other Goodies / Github Code

Other Research and Academic Activities

Excitation of Rb87: Worked in a Quantum Research lab alongside fellow student Hannah Killian under the guidance of Dr. Hai Nguyen. I provided software tools and assisted in understanding the mathematics behind the phenomena.

Modeling Population Dynamics of Incoherent and Coherent Excitation

Coherent Control of Atomic Population Using the Genetic Algorithm

Beowulf Cluster: In order to circumvent the frustrations I had with simulation code taking a while, I applied and received funding to build out a Beowulf cluster for the Physics department. Dr. Maia Magrakvilidze was the advisor for this project. LUNA-C Poster

Cluster Analysis: The study of grouping similar observations without any prior knowledge. I studied this topic by deep diving Wikipedia articles under the guidance of Dr. Melody Denhere during Spring 2018. Extensive notes

Programming Languages: Back in the Fall of 2018, under the guidance of Ian Finlayson, I worked towards creating a programming language similar to SLOTH (Simple Language of Tiny Heft). SLOTH Code

Before this study, I worked through a great book called “Build your own Lisp”.

Competitive Programming: Studying algorithms and data structures necessary for competitive programming. Attended ACM ICPC in November 2018/2019 with a team of two other students.