Mitchell Krawiec-Thayer
President & Chief Scientist at Geometry Labs- Claim this Profile
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English Native or bilingual proficiency
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Portuguese Elementary proficiency
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MATLAB Professional working proficiency
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Python Professional working proficiency
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Mathematica Professional working proficiency
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Flask Elementary proficiency
Topline Score
Bio
Experience
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Geometry Labs
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Software Development
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1 - 100 Employee
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President & Chief Scientist
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Feb 2021 - Present
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Noncesense Research Lab
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Decentralized team
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Volunteer Data Scientist, Research Lead
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Jul 2017 - Present
‣ Early Monreo results here: https://www.youtube.com/watch?v=XIrqyxU3k5Q ‣ Gathered a top-notch team to fill coding, analysis, and security/operational roles. ‣ Co-designed the Monero Archival Project's custom archival daemon. ‣ Discovered Big Bang attack on dynamic blocksize, subsequently mitigated in the Monero protocol. ‣ Quantified activity leaks through single-output transactions, resulting in Monero protocol modification. ‣ Uncovered transaction lock time anomalies, resulting in Monero protocol modification to prevent juvenile spending. ‣ Detected and documented selfish mining activity. ‣ Discovered anomalies such as Merlin blocks and non-latency-induced long alternative chains (e.g. routinely 30 blocks long). ‣ Quantified subtle (invisible) centralization due to IP bottlenecks. ‣ Discovered a new heuristic for tracking through Monero churn: identifying sets of transactions with non-standard decoy selection algorithms. ‣ Studied emergent behaviors arising from edge cases in game theory / financial incentivization. ‣ Began initiative to push for fixed fee options in future network upgrades. ‣ Learn more at https://noncesense-research-lab.github.io Show less
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Insight Data Science
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United States
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Higher Education
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1 - 100 Employee
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Head of Research, Developers in Residence
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Apr 2020 - Dec 2020
‣ Launched Insight's Developer in Residence initiative to connect specialized software engineers with high-impact problems in the open source software space‣ Projects have been funded by grants from:‣‣ Web 3 Foundation (load balanced endpoints)‣‣ Zcash Foundation (NetSec suite)‣‣ Harrmony grants (advanced blockchain explorer)‣‣ ICON Foundation (data pipeline and analytics)‣‣ Quantum Resistant Ledger (cryptography research on scalability and privacy)‣‣ Monero CCS (audit of Monero's cryptography in a post-quantum context)‣ Continuously building new partnerships to source interesting projects for developers in residence. (Drop me a message if you'd like to collaborate!) Show less
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Decentralized Consensus Lead
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Jul 2018 - Apr 2020
‣ Launched the Insight Decentralized Consensus Fellows Program‣ Mentored 30+ technical projects across the blockchain stack (from hardware to lightning...)‣ Fellowship alumni were hired by NEAR Protocol, Bolt Labs, IOV Labs, Binance, IBM, Unchained Capital, Gauntlet Network, Microsoft, Protonmail, BlockFi, and launched multiple startups. ‣ Hired, managed, and mentored two full-time specialized software architects as direct reports‣ Spearheaded the Insight Infrastructure endeavor, hired DevOps engineer, oversee ongoing validator operations and new partnerships‣ Initiated and maintained relationships with dozens of companies in the blockchain space Show less
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Insight Data Science Fellow
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Jun 2018 - Jul 2018
Designed and built OperatorAware, a quality assurance tool for 911 call center supervisor augmentation. OperatorAware listens to caller-dispatcher recordings and identifies emergencies that were not handled appropriately.
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Uncaged Potential
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United States
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Research
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Researcher & Technical Editor
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Jan 2018 - Sep 2018
‣ Founded the Monero Archival Project, which designed the first methods and tools that allowed detection of blockchain anomalies and study of network topology & latency ‣ Released the Seed Sieve algorithm, a modular text filter that allows any platform (e.g. social media, email, etc) to protect their users from accidentally revealing cryptocurrency seed mnemonic phrases. ‣ Copy edited Mastering Monero, the first official comprehensive guide for said cryptocurrency, to be published in fall 2018 as an electronic and hardcover resource. ‣ Invented machine learning classification tools for discerning evolutionary history and geographic origin from raw genetic data (consulting, led to patent exploration) ‣ Translated & copy edited technical articles (from Italian) ‣ Designed back-end signal processing (scaling and noising) of historical financial timeseries for use in an adrenalizing training simulator on cryptocurrency-fiat pairings ‣ Proposed improvements to Monero's fungibility by subjecting spend time distributions and decoy selection to improvement by generative adversarial network (GAN) learning Show less
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University of Wisconsin-Madison
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Higher Education
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700 & Above Employee
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Graduate Research Fellow
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Dec 2012 - Jan 2018
‣ Discovered several new ways to use machine learning tools to solve open problems in the geophysical domain ‣ Enhanced the value of field data by extracting underlying information through dimensionality reduction, feature extraction, feature selection, and other information-theoretic techniques. ‣ Leveraged data science imputation tools (e.g. neural networks, regression trees, lazy learners) to revolutionize methods for handling missing and messy data ‣ Invented cluster evaluation methods for identification of atmospheric structure ‣ Co-founded and directed ad-hoc atmospheric chemistry working group composed of of mathematics and CS graduate students ‣ Mentored development of advanced pollution detection models based on support vector machines, Markov models, and fuzzy logic-based decision engines. Show less
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Ohio Northern University
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United States
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Higher Education
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700 & Above Employee
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Research Assistant
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Aug 2009 - May 2012
‣ Synthesized novel substituted benzofluorenone dyes, in order to analyze their ability to induce and report the formation of G-quadruplex structures. ‣ Experimentally determined element-specific error for x-ray fluorescence spectroscopy, and subsequently developed an improved standardization procedure for the device ‣ Studied zigzag instability in small clusters with fewer than 10 microspheres. Studied wave propagation in chains of dust particles more than one particle wide. ‣ Paired images of galaxies from NASA/IPAC Extragalactic Database with data for telescope positions. Matched observed photometric features to corresponding kinematic features. ‣ Calculated stellar kinematics such as rotational velocity and velocity dispersion for the central objects for four galaxies. Show less
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Education
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University of Wisconsin-Madison
Doctor of Philosophy (Ph.D.), Physical Chemistry -
University of Wisconsin-Madison
Master of Science (M.S.), Physical Chemistry -
Ohio Northern University
2012, Chemistry, Physics, Applied Mathematics, Astronomy