ALLEN RESEARCH
Founder 2023 - Present
I conduct independent research in the areas of generative AI and knowledge representation.
ACRISURE CAPITAL
Chief Scientist 2021 - 2023
Acrisure Capital is a small, fast-paced team of engineers and scientists in Austin who are building a quantitative investment firm from the ground up.
ACRICURE TECHNOLOGY GROUP
Chief Technology Officer 2019 - 2021
ATG is the technology arm of Acrisure, consisting of engineering, product, and AI research teams.
TULCO LABS
Chief Technology Officer 2019 - 2020
Tulco Labs served as the technology arm of Tulco Holdings, employing AI and technology to accelerate growth of a portfolio of companies including FIGS, Edgeworth, Road Runner, and the Tulco-initiated startups Altway Insurance and BlueNote AI. Acrisure acquired Altway, BlueNote, and other Tulco assets in August 2019 as part of a $400 million dollar transaction.
ALTWAY INSURANCE
Chief Technology Officer 2019 - 2020
Employee #1 and CTO of startup Altway Insurance, founded as a joint venture by Tulco Holdings and Acrisure to apply artificial intelligence to insurance distribution. Achieved 10% week-over-week growth in active users for 35 weeks before being fully acquired by Acrisure.
BLUENOTE AI
Chief Technology Officer 2019 - 2020
Employee #1 and CTO of startup of BlueNote AI, founded by Tulco Holdings. Whereas Altway focused on applying AI to insurance distribution, BlueNote focused on applying predictive modeling to the carrier side of insurance. Acquired by Acrisure along with Altway and components of Tulco Labs.
TWO SIGMA INVESTMENTS
Senior Vice President / Artificial Intelligence Researcher 2017 - 2019
Promoted to Senior Vice President. Joined the nascent AI Core Team at Two Sigma as a senior researcher focusing on deep reinforcement learning and its application to finance.
Vice President / Head of Houston Data Engineering 2015 - 2017
Promoted to VP and Head of Houston Data Engineering, an organization of roughly 40 engineers and five teams focused on predictive modeling, distributed computing, data ingestion, and anomaly detection.
Engineering Manager / Analytics and Alpha Capture 2014 - 2015
Built and managed a new team in the Houston office charged with collecting and maintaining alpha capture data, and applying machine learning and predictive modeling to our data sets.
RETAILMENOT
Lead Data Scientist 2013 - 2014
Drove, managed, and set strategic direction for the RetailMeNot Data Science team. Employed machine learning, natural language processing, and statistical analysis to find patterns in large datasets. Projects prioritized based on the largest potential impact to revenue.
BAZAARVOICE
Engineering Manager, Data Science 2011 - 2013
Initiated the formation of, assembled, and led a dedicated Data Science team using machine learning and natural language processing to analyze unstructured data and productize the results in high volume, low latency web services for online advertising.
SUN MICROSYSTEMS
Principal Investigator 2003 - 2011
Promoted four times over an eight year tenure. Directed Project Fortress, an open source project initiated by Sun Labs to develop a next generation language for distributed computing over large data sets, as part of the DARPA HPCS Project.
CYCORP
Software Engineer 2000 - 2001
Constructed a word-sense disambiguation engine based on concept proximity in the Cyc knowledge graph. Designed and implemented a JVM-based blackboard interface for remote access to the Cyc system.
CORNELL UNIVERSITY
Undergraduate Research Assistant 1995 - 1996
Served as a programmer and research assistant to Professor Claire Cardie's Natural Language Processing Research Group. Constructed NLP tools for automatically identifying citations in unstructured text and embedding hypertext links to corresponding references.
RICE UNIVERSITY
Adjunct Professor of Computer Science 2014 - 2016
Taught courses on functional programming, as well as parallel and distributed computing. The functional programming curriculum was inspired by multiple sources including How to Design Programs, The Structure and Interpretation of Computer Programs, and Martin Odersky's Cousera course: Functional Programming in Scala.
THE UNIVERSITY OF TEXAS AT AUSTIN
Adjunct Professor of Computer Science 2008 - 2009
Taught honors and graduate courses on operational semantics and type systems. Curriculum roughly followed Benjamin Pierce's Types and Programming Languages. Served as a member of the SIGPLAN-Sponsored Curriculum Workshop on Programming Language Education.
RICE UNIVERSITY
Doctor of Philosophy (PhD) 1997 - 2003
Computer Science, Advisor: Professor Robert Cartwright
Thesis: A First-Class Approach to Genericity. Published and awarded Best Student Paper at OOPSLA 2003.
UNIVERSITY OF TEXAS AT AUSTIN
Master of Business Administration (MBA) 2009 - 2011
General Management Executive MBA Program at the Red McCombs School of Business.
CORNELL UNIVERSITY
Cornell College Scholar 1993 - 1996
Dual Bachelor’s Degrees in Mathematics and Computer Science. Concentration in Cognitive Studies.
DISPATCH PREDICATE FOR OVERLOADED FUNCTIONS USING TYPE INTERVALS
US Patent: US20140068556A1 · Inventors: Karl B. Naden, Justin R. Hilburn, David R. Chase, Guy L. Steele, Victor M. Luchangco, Eric Allen
The disclosed embodiments provide a system that facilitates the development and execution of a software program. During runtime of the software program, the system obtains a function call associated with an overloaded function and a generic type hierarchy. Next, the system determines an applicability of an implementation of the overloaded function to the function call. Finally, the system selects the implementation for invocation by the function call based on the determined applicability and a partial order of implementations for the overloaded function.
NON-LINEAR CLASSIFICATION OF TEXT SAMPLES
US Patent: 9342794 · Inventors: Eric Allen, Daniel Mahler, Milos Curcic, Eric Scott
Non-linear classifiers and dimension reduction techniques may be applied to text classification. Non-linear classifiers such as random forest, Nystrom/Fisher, and others, may be used to determine criteria usable to classify text into one of a plurality of categories. Dimension reduction techniques may also be used to reduce feature space size. Machine learning techniques may be used to develop criteria (e.g., trained models) that can be used to automatically classify text. Automatic classification rates may be improved and result in fewer numbers of text samples being unclassifiable or being incorrectly classified. User-generated content may be classified, in some embodiments.
METHOD AND APPARATUS FOR EXPRESSING AND CHECKING
US Patent: 8225294 · Inventors: Eric Allen, Sukyoung Ryu, Victor Luchangco, Joe Hallett, Sam Tobin-Hochstadt
One embodiment of the present invention provides a system for generating executable code. During operation, the system receives source code, wherein the source code can include declarations for types and operations, wherein the type declarations may be parameterized, and wherein the source code may specify subtyping relationships between declared types. Next, the system compiles or interprets the source code to produce executable code, wherein the type parameters may be instantiated by different types during execution, and wherein the result of executing operations may depend upon the instantiations of the type parameters. While compiling or interpreting the source code, the system checks the types and operations in the source code to ensure that the executable code generated is type-safe, and hence will not generate type errors during execution.
METHOD AND APPARATUS FOR DIMENSIONAL ANALYSIS ENCODED IN
US Patent: 7530051 · Inventors: Eric Allen, Guy L. Steele, Jr., David Chase, Victor Luchangco, Jan-Willem Maessen
In general, in one aspect, the invention relates to a method for integrating dimensional analysis in a program comprising defining a specific dimension class within the program, wherein the specific dimension class is an instance of the dimension meta-class, defining an instantiation of a unit class within the program, wherein the instantiation of the unit class comprises the specific dimension class as a type parameter associated with the instantiation of the unit class, defining a method within the program using the instantiation of the unit class and the specific dimension class, and compiling the program to generate an executable code corresponding to the program, wherein the program is written in an object-oriented language.
FIRST PLACE: NEW VENTURE CREATIONS ANNUAL BUSINESS PLAN COMPETITION
In concert with Nathan Baumeister and Zaz Floreani. The Red McCombs School of Business at UT Austin, 2010. Business plan and presentation selected by an independent panel of venture capitalists, earning an automatic A in New Venture Creation course taught by Professor Rob Adams.
BEST STUDENT PAPER
The 18th Annual ACM Sigplan Conference on Object-Oriented Programming, Systems, Languages, and Applications, 2003.
MATH LEAGUE CHAMPION
Buffalo Public Schools Mathematics League, 1992.
DEBATE LEAGUE BEST SPEAKER
Buffalo Public Schools Debate League, 1992.
DALE CARNEGIE COURSE — HIGHEST AWARD FOR ACHIEVEMENT
Dale Carnegie and Associates, 1991.