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105 lines
6.5 KiB
Markdown
105 lines
6.5 KiB
Markdown
---
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Title: Research
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Description: A list of my research Projects
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---
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**[Quick List of Publications](/publications)**
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**Broad Research Interests:** Automated Reasoning, Artificial Intelligence, Formal Methods
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## Logic-Based AI
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Working with [Dr. Selmer Bringsjord](https://homepages.rpi.edu/~brings/) and others in the [RAIR Lab](https://rair.cogsci.rpi.edu/) to
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design and implement artificial intelligent agents using computational logic. I'm particularly interested in:
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- Explainability through verifiable chains of inference
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- Defeasible reasoning under uncertainty
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- Reasoning about agents and their cognitive states
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[Notes on Automated Theorem Proving](atp)
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## Integrated Planning and Reinforcement Learning
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Working with [Junkyu Lee](https://researcher.ibm.com/researcher/view.php?person=ibm-Junkyu.Lee),
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[Michael Katz](https://researcher.watson.ibm.com/researcher/view.php?person=ibm-Michael.Katz1),
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and [Shirin Sohrabi](https://researcher.watson.ibm.com/researcher/view.php?person=us-ssohrab)
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on extending and relaxing assumptions within their existing
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[Planning Annotated Reinforcement Learning Framework](https://prl-theworkshop.github.io/prl2021/papers/PRL2021_paper_36.pdf) developed at IBM Research.
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In this framework, automated planning is used on a higher-level version of the overall
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problem with a surjective function mapping RL states to AP states. The agent is
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based on the options framework in Hiearchical Reinforcement Learning where options
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are defined as the grounded actions in the planning model.
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More to come...
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## Symbolic Methods for Cryptography
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Working with [Dr. 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
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as unification and term rewriting to the following areas:
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- Block Ciphers
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- Secure Multi-party Computation
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- Authentication
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- 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, as well as contribute to our current work on Garbled Circuits. 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)), and [WRLA 2022](http://sv.postech.ac.kr/wrla2022/assets/files/pre-proceedings-WRLA2022.pdf#page=12) ([slides](/files/slides/wrla2022-slides.pdf)).
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I've written a few [notes](termreasoning) about term reasoning.
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Current 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/), Kim Cornell
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- Clarkson University: [Christopher Lynch](https://people.clarkson.edu/~clynch/)
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Group Website: [https://cryptosolvers.github.io](https://cryptosolvers.github.io)
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## Reinforcement Learning
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**Deep Reinforcement Learning:** With [Dr. Ron Zacharski](http://zacharski.org/) I focused on how to make deep reinforcement learning
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algorithms more sample efficient. That is, how can we make it so that the RL agent learns more from every observation to make it so that
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we achieve our goal faster. With that goal in mind, I built out a Reinforcement Learning library written in PyTorch to help benchmark
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my ideas.
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*Links:*
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| ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
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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/)) |
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| [Undergraduate Honors Defense](/files/research/ExpeditedLearningInteractiveDemo.pptx) | [QEP Algorithm Slides](/files/research/QEP.pptx) | [More...](deepreinforcementlearning) |
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**Reinforcement Learning:** Studied the fundamentals of reinforcement learning with [Dr. Stephen Davies](http://stephendavies.org/). We went over the fundamentals such as value functions, policy functions, how we can describe our environment as a markov decision processes, etc.
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[Notes and Other Goodies](reinforcementlearning) / [Github Code](https://github.com/brandon-rozek/ReinforcementLearning)
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## Other
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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)
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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.
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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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[**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.
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[Modeling Population Dynamics of Incoherent and Coherent Excitation](/files/research/modellingpopulationdynamics.pdf)
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[Coherent Control of Atomic Population Using the Genetic Algorithm](/files/research/coherentcontrolofatomicpopulation.pdf)
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[**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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