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---
Title: Research
Description: A list of my research Projects
---
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**[Quick List of Publications](/publications/)**
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**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:
- With [Selmer Bringsjord](https://homepages.rpi.edu/~brings/) in the [RAIR Lab](https://rair.cogsci.rpi.edu/) I have looked at planning through automated reasoning.
I further developed [Spectra](https://github.com/rairlab/spectra) and the underlying
planning with formulas framework to show classes of uncertainty problems that
are easy to encode. Additionally, I wrote a QA algorithm for ShadowProver to integrate to Spectra
for planning under epistemic uncertatinty.
- With [Junkyu Lee](https://researcher.ibm.com/researcher/view.php?person=ibm-Junkyu.Lee),
[Michael Katz](https://researcher.watson.ibm.com/researcher/view.php?person=ibm-Michael.Katz1),
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[Harsha Kokel](https://research.ibm.com/people/harsha-kokel), and [Shirin Sohrabi](https://researcher.watson.ibm.com/researcher/view.php?person=us-ssohrab) at IBM I developed an algorithm
for guiding hiearchical reinforcement agents under partial observability when domain knowledge
can be encoded for characterizing discovery of unknown predicates. This techinque
uses a fully-observable non-deterministic planner to generate a high-level policy
where each high-level action is an option that a reinforcement learning agent
needs to learn.
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- More to come...
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## Logic
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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.
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- With Andrew Marshall and Kimberly Cornell, we're currently developing a new syntactic AC algorithm.
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- With Thomas Ferguson and James Oswald we formaliezd a model theory for a fragment of the Deontic Cognitive Event Calculus.
- With James Oswald we've built interactive theorem provers and showed validity of large proofs in parallel using a high performance cluster.
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Related Notes:
- [Automated Theorem Proving](atp/)
- [Term Reasoning](termreasoning/)
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## Symbolic Methods for Cryptography
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Worked with [Andrew Marshall](https://www.marshallandrew.net/) and others in applying term reasoning within computational logic
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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:
- Block Ciphers
- Secure Multi-party Computation
- Authentication
- Commitment Schemes
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Together we built [CryptoSolve](https://github.com/cryptosolvers/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.
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I still help maintain the codebase. We previously presented our work
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at [UNIF 2020](https://www3.risc.jku.at/publications/download/risc_6129/proceedings-UNIF2020.pdf#page=58) ([slides](/files/research/UNIF2020-Slides.pdf)), [FROCOS 2021](https://link.springer.com/chapter/10.1007/978-3-030-86205-3_14) ([slides](/files/slides/FROCOS2021.pdf)), [WRLA 2022](http://sv.postech.ac.kr/wrla2022/assets/files/pre-proceedings-WRLA2022.pdf#page=12) ([slides](/files/slides/wrla2022-slides.pdf)),
and [GandALF 2022](/paper/2209.01/).
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Collaborators:
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- NRL: Catherine Meadows
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- UMW: [Andrew Marshall](https://www.marshallandrew.net/)
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- UT Dallas: Serdar Erbatur
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- SUNY Albany: [Paliath Narendran](https://www.cs.albany.edu/~dran/) and Kimberly Cornell
- Clarkson University: [Christopher Lynch](https://people.clarkson.edu/~clynch/) and Hai Lin
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Group Website: [https://cryptosolvers.github.io](https://cryptosolvers.github.io)
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## Reinforcement Learning
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During my undergraduate degree, I worked with [Dr. Ron Zacharski](http://zacharski.org/)
on making deep reinforcement learning algorithms more sample efficient with human feedback.
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In my experimentation, I built out a Reinforcement Learning library in PyTorch.
*Links:*
| | | |
| ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
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| [RL Library on Github](https://github.com/brandon-rozek/rltorch) | [Interactive Demonstrations Library](https://github.com/brandon-rozek/gyminteract) | [Undergraduate Honors Thesis](/files/research/honorsthesis.pdf) ([Eagle Scholar Entry](https://scholar.umw.edu/student_research/305/)) |
| [Undergraduate Honors Defense](/files/research/ExpeditedLearningInteractiveDemo.pptx) | [QEP Algorithm Slides](/files/research/QEP.pptx) | [More...](deepreinforcementlearning) |
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[Dr. Stephen Davies](http://stephendavies.org/) 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.
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[Notes and Other Goodies](reinforcementlearning/) / [Github Code](https://github.com/brandon-rozek/ReinforcementLearning)
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## Other Research and Academic Activities
[**Excitation of Rb87**](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](/files/research/modellingpopulationdynamics.pdf)
[Coherent Control of Atomic Population Using the Genetic Algorithm](/files/research/coherentcontrolofatomicpopulation.pdf)
[**Beowulf Cluster:**](lunac) 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](/files/research/LUNACposter.pdf)
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**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](clusteranalysis/)**
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[**Programming Languages:**](proglang/) 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](https://github.com/brandon-rozek/SLOTH)
Before this study, I worked through a great book called ["Build your own Lisp"](https://www.buildyourownlisp.com/).
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[**Competitive Programming:**](progcomp/) Studying algorithms and data structures necessary for competitive programming. Attended ACM ICPC in November 2018/2019 with a team of two other students.