Guillermo Angeris (Guille)

About

Head of research at Bain Capital Crypto. In a previous life, I did math and physics at Stanford. Not a real doctor.

Papers

A primer on perpetuals (Sep. 2022)
Guillermo Angeris, Tarun Chitra, Alex Evans, Matthew Lorig. (arXiv)
Dynamic pricing for non-fungible resources (Aug. 2022)
Theo Diamandis, Alex Evans, Tarun Chitra, Guillermo Angeris. (arXiv)
A note on generalizing power bounds for physical design (Aug. 2022)
Guillermo Angeris. (arXiv)
Bounds on efficiency metrics in photonics (Mar. 2022)
Guillermo Angeris*, Theo Diamandis*, Jelena Vučković, Stephen Boyd. (arXiv)
DeFi liquidity management via optimal control: Ohm as a case study (Feb. 2022)
Tarun Chitra, Kshitij Kulkarni, Guillermo Angeris, Alex Evans, Victor Xu.
Optimal routing for constant function market makers (Dec. 2021)
Guillermo Angeris, Alex Evans, Tarun Chitra, Stephen Boyd. (arXiv, code)
Presented at EC 2022.
Replicating monotonic payoffs without oracles (Sep. 2021)
Guillermo Angeris, Alex Evans, Tarun Chitra. (arXiv)
Presented at the DeFi workshop at FC 2022.
Differential privacy in constant function market makers (Aug. 2021)
Tarun Chitra, Guillermo Angeris, Alex Evans. (ePrint)
Presented at FC 2022.
Constant function market makers: multi-asset trades via convex optimization (Jul. 2021)
Guillermo Angeris, Akshay Agrawal, Alex Evans, Tarun Chitra, Stephen Boyd. (arXiv)
To appear as a chapter in Springer's Handbook on Blockchain, 2022.
Reciprocal multi-robot collision avoidance with asymmetric state uncertainty (May 2021)
Kunal Shah*, Guillermo Angeris*, Mac Schwager. (arXiv, code)
Replicating market makers (Mar. 2021)
Guillermo Angeris, Alex Evans, Tarun Chitra. (arXiv)
A note on privacy in constant function market makers (Feb. 2021)
Guillermo Angeris, Alex Evans, Tarun Chitra. (arXiv)
Optimal fees for geometric mean market makers (Jan. 2021)
Alex Evans, Guillermo Angeris, Tarun Chitra. (arXiv)
Presented in the DeFi workshop at FC 2021.
When does the tail wag the dog? Curvature and market making (Dec. 2020)
Guillermo Angeris, Alex Evans, Tarun Chitra. (arXiv)
Accepted in MIT's CES 2022.
LinRegOutliers: a Julia package for detecting outliers in linear regression (Dec. 2020)
Mehmet Satman, Shreesh Adiga, Guillermo Angeris, Emre Akadal. (code)
Published in the Journal of Open Source Software.
Heuristic methods and performance bounds for photonic design (Nov. 2020)
Guillermo Angeris, Jelena Vučković, Stephen Boyd. (arXiv, code)
Published in Optics Express.
Improved price oracles: constant function market makers (rewritten Jun. 2020)
Guillermo Angeris, Tarun Chitra. (arXiv, original version from Mar. 2020)
Presented in ACM's Advances in Financial Technologies 2020.
Optimal representative sample weighting (May 2020)
Shane Barratt, Guillermo Angeris, Stephen Boyd. (arXiv, code)
Published in Statistics and Computing.
Bounds for scattering from absorptionless electromagnetic structures (Mar. 2020)
Rahul Trivedi, Guillermo Angeris, Logan Su, Stephen Boyd, Shanhui Fan, Jelena Vučković. (arXiv, code)
Published in Physical Review Applied.
Convex restrictions in physical design (Feb. 2020)
Guillermo Angeris, Jelena Vučković, Stephen Boyd. (arXiv, code)
Published in Scientific Reports.
Automatic repair of convex optimization problems (Jan. 2020)
Shane Barratt, Guillermo Angeris, Stephen Boyd. (arXiv, code)
Published in Optimization and Engineering.
An analysis of Uniswap markets (Nov. 2019)
Guillermo Angeris, Hsien-Tang Kao, Rei Chiang, Charlie Noyes, Tarun Chitra. (arXiv)
Published in MIT's CES 2020. (reviews)
Minimizing a sum of clipped convex functions (Oct. 2019)
Shane Barratt, Guillermo Angeris, Stephen Boyd. (arXiv, code)
Published in Optimization Letters.
Fast reciprocal collision avoidance under measurement uncertainty (May 2019)
Guillermo Angeris*, Kunal Shah*, Mac Schwager. (arXiv, code)
Presented at ISRR 2019.
Computational bounds for photonic design (Nov. 2018, edited Dec. 2018)
Guillermo Angeris, Jelena Vučković, Stephen Boyd. (arXiv, code)
Published in ACS Photonics.

* Indicates equal authorship.

Short papers and other writings

How liveness separates CFMMs and order books (Oct. 2021)
Tarun Chitra, Guillermo Angeris, Alex Evans.
A note on bundle profit maximization (Jun. 2021)
Guillermo Angeris, Alex Evans, Tarun Chitra.
The Georeg regularizer (Apr. 2019)
Guillermo Angeris, Shane Barratt, Jonathan Tuck.*

* Indicates equal authorship.

Talks

Privacy in DeFi: challenges and constructions (Apr. 2022)
Guillermo Angeris.
ZK Summit 7.
Heuristics and bounds for photonic design (Mar. 2022)
Guillermo Angeris.
Defense presentation. Stanford University.
Bounds on achievable performance via Lagrange duality (Jul. 2021)
Guillermo Angeris, Rahul Trivedi, Logan Su, Jelena Vučković, Stephen Boyd. (summary)
Invited talk. META 2020, University of Warsaw.
Constant function market makers: Pushing Uniswap and friends to do more with lower fees (May 2020)
Guillermo Angeris, Tarun Chitra
DeFi Discussions. (recorded talk)
An analysis of Uniswap markets (Mar. 2020)
Guillermo Angeris, Hsien-Tang Kao, Rei Chiang, Charlie Noyes, Tarun Chitra.
CES 2020, MIT. (recorded talk)

More

During my Ph.D. (2019-2022) I worked on inverse design in the Nanoscale and Quantum Photonics lab with Prof. Jelena Vučković and Prof. Stephen Boyd. My thesis, Heuristics and bounds for photonic design, focused mostly on some applications of optimization to photonics. I also did my bachelor's and master's at Stanford, also in EE.

For other work and more info, my blog can be found here which I (sometimes) update. Additionally, most of my code can be found on my GitHub profile.

Teaching

CME/EE103: Introduction to Matrix Methods
TA'd on: Autumn 2015, Autumn 2016, Autumn 2017.

EE364A: Convex Optimization
TA'd on: Spring 2017, Winter 2018.

EE104: Introduction to Machine Learning
TA'd on: Spring 2018.

Class projects

LEigOpt.jl: A fast, first-order interior-point optimizer for eigenvalue optimization
We propose a new first-order interior-point method for eigenvalue optimization of matrices with common sparsity structure, which, in the current testing, outperforms SCS and CVXOPT by at least an order of magnitude of runtime. (pdf, code)

Electrical network approximation to constrained minimum k-cut (multiway cut)
We propose a novel, fast method for approximating the minimum k-Cut problem by using electrical networks. Our approach has similar performance to the current best LP approximation but much faster empirical runtime. (pdf, code)

DominAI: An AI for the imperfect information game of Dominoes
We develop an algorithm for approximating good play in imperfect information games and show an application of the algorithm to the team-based game of Venezuelan dominoes. (pdf, poster, code)

GameBoy emulator on bare metal Raspberri Pi
We developed a complete (though not cycle-accurate) CPU/GPU emulator for the original GameBoy, built on top of the Raspberry Pi without an operating system. (code)

Unsupervised learning for brain tumor categorization
We correctly infer tumour regions without reference to masked examples by using unsupervised learning, showing that a simple approach for unknown or little-known classes of tumors can yield possibly useful insights into these classes. (pdf, poster, code)

Other Projects

Autonomous, multi-objective path planner for the AUVSI–SUAS competition
Currently working on a path-planning algorithm for fixed-wing search-and-rescue UAVs with real-time objective creation, modification, and updating. No code will be available until the end of the competition, but progress and mathematical descriptions of the solution can be found on my blog. (blog, competition)

Chocolate-Arch: A tiny 8-bit processor
I designed an 8-bit architecture made to fit on a Lattice iCEStick (with 1K LUTs). A small team of us began a complete implementation on an FPGA along with an external Arduino-based debugger during a hackathon. (code)

Frequently asked questions

Wait, so how do I pronounce your nickname, Guille?

Gee (like geese) - ye (like yet, but without the t).

Have you ever not been in school or writing papers?

Temporarily, I guess.

I spent my 2016 and 2017 summers at D.E. Shaw Research (DESRES) doing work on fast algorithms for protein folding detection ('16) and some other work on information-limited labelling schemes ('17). I spent my summer of 2018 at Facebook doing work in scam detection. I consulted for Gauntlet from 2019 to 2021.

Do you do anything other than research or program? E.g., anything useful?

Probably not, to be honest.

I do like to make pizza, listen to music, and hike, though.