Lukas Biewald

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Lukas Biewald 823 Capp St., San Francisco, CA 94110 (650) 804 5470 lukas@crowdflower.com Awards Netexplorateur of the Year http://www.netexplorateur.org/ (2010) TechCrunch 50 http://techcrunch50.com (2009) First Place, Caltech Turing Tournament http://turing.ssel.caltech.edu Work Founder, CEO: CrowdFlower 2008 — Present • Built leading Labor-on-Demand company from the ground up. Designed and coded core technology. Built customer base up from nothing to 100 customers including several Fortune-500 companies. Hired 25 employees. • Raised two rounds of financing totalling $6.2 million in 2009 in tough economic climate from well-known angels and VCs including Trinity, Bessemer, Founders´ Fund, Auren Hoffman, Aydin Senkut, Manu Kumar, Gary Kremen and Travis Kalanick. Senior Scientist: Powerset 2007 — 2008 • As the 20th employee, created and led two core teams: metrics and search ranking. • Developed the Amazon Mechanical Turk interface, identified as a key technology in Microsoft’s $100 million acquisition. Relevance Engineer, Engineering Manager: Yahoo! Inc. 2005 — 2007 • Technical lead for research, development and deployment of new web search ranking functions in five major markets. • Chosen as most productive employee in Applied Science business unit year end review. Research Assistant: Stanford AI Lab (sail.stanford.edu) 2003 — 2004 • Researched word-sense disambiguation, machine translation and Japanese word segmentation. • Published two papers with over 100 citations. Education Stanford University 1998 — 2004 BS in Mathematical and Computational Science with Honors (2003) MS in Computer Science with Concentration in Artificial Intelligence (2004) Publications David Vickrey, Lukas Biewald, Marc Teyssier, and Daphne Koller Word-Sense Disambiguation for Machine Translation. Conference on Empirical Methods in Natural Language Processing (EMNLP), 2005. Peter Bodik, Greg Friedman, Lukas Biewald, Helen Levine, George Candea, Kayur Patel, Gilman Tolle, Jon Hui, Armando Fox, Michael I. Jordan, David Patterson Combining Visualization and Statistical Analysis to Improve Operator Confidence and Efficiency for Failure Detection and Localization. International Conference on Autonomic Computing (ICAC), 2005. Brendan O’Connor, Lukas Biewald Superficial Data Analysis: Exploring Millions of Social Stereotypes. In Toby Segaran, Jeff Hammerbacher (ed) Beautiful Data. O’Reilly Media, 2009. Patents Bardige, Arthur H., Lukas Biewald Computerized System and Method for Visually Based Education. U.S #6,918,768. July, 2005 Franco Salvetti, Lorenzo Thione, Richard Crouch, David Ahn, Lukas Biewald, Brendan O’Connor, Barney Pell Browsing Knowledge on the Basis of Semantic Relationships. 12/201,978. Aug, 2008 Chad Walters, Nitay Joffe, Lukas Biewald, Andrew Alan James Browsing Knowledge on the Basis of Semantic Relationships. 12/201,051. Aug, 2008 Chad Walters, Lorenzo Thione, Barney Pell, Lukas Biewald, Brendan O’Connor Efficient Storage and Re- trieval of Posting Lists. 12/201,079. Aug, 2008 Hobbies Expert-level Go player (AGA 5-dan).

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AAAI 2008 Workshop Reports
University of Pennsylvania ScholarlyCommons Technical Reports (CIS) Department of Computer & Information Science 5-2009 AAAI 2008 Workshop Reports Mark Dredze University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/cis_reports Recommended Citation Mark Dredze, "AAAI 2008 Workshop Reports", . May 2009. Sarabjot Singh Anand, Razvan Bunescu, Vitor Carvalho, Jan Chomicki, Vincent Conitzer, Michael T Cox, Virginia Dignum, Zachary Dodds, Mark Dredze, David Furcy, Evgeniy Gabrilovich, Mehmet H Göker, Hans Guesgen, Haym Hirsh, Dietmar Jannach, Ulrich Junker. (2009, April). AAAI 2008 Workshop Reports. AI Magazine, 30(1), 108-118. Copyright AAAI 2009. The copies do not imply AAAI endorsement of a product or a service of the employer, and that the copies are not for sale. Publisher URL: http://proquest.umi.com/ pqdlink?did=1680350011&sid=1&Fmt=2&clientId=3748&RQT=309&VName=PQD This paper is posted at ScholarlyCommons. https://repository.upenn.edu/cis_reports/904 For more information, please contact [email protected]. AAAI 2008 Workshop Reports Abstract AAAI was pleased to present the AAAI-08 Workshop Program, held Sunday and Monday, July 13-14, in Chicago, Illinois, USA. The program included the following 15 workshops: Advancements in POMDP Solvers; AI Education Workshop Colloquium; Coordination, Organizations, Institutions, and Norms in Agent Systems, Enhanced Messaging; Human Implications of Human-Robot Interaction; Intelligent Techniques for Web Personalization and Recommender Systems; Metareasoning: Thinking about Thinking; Multidisciplinary Workshop on Advances in Preference Handling; Search in Artificial Intelligence and Robotics; Spatial and Temporal Reasoning; Trading Agent Design and Analysis; Transfer Learning for Complex Tasks; What Went Wrong and Why: Lessons from AI Research and Applications; and Wikipedia and Artificial Intelligence: An vE olving Synergy.
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The Founder of the Creative Destruction Lab Describes Its Moonshot Mission to Create a Canadian AI Ecosystem
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A Strategic Metagame Player for General Chesslike Games
From: AAAI Technical Report FS-93-02. Compilation copyright © 1993, AAAI (www.aaai.org). All rights reserved. A Strategic Metagame Player for General Chess-Like Games Barney Pell* Computer Laboratory University of Cambridge Cambridge, CB2 3QG, UK b dp((~cl c am. ac Abstract game will transfer also to new games. Such criteria in- clude the use of learning and planning, and the ability This paper reviews the concept of Metagameand to play more than one game. discusses the implelnentation of METAGAMER,a program which plays Metagame in the class of 1.1 Bias when using Existing Games symmetric chess-like games, which includes chess, However,even this generality-oriented research is sub- Chinese-chess, checkers, draughts, and Shogi. The ject to a potential methodological bias. As the human l)rogram takes as input the rules of a specific game researchers know at the time of program-development and analyses those rules to construct for that game which specific game or games the program will be tested an efficient representation and an evaluation func- on, it is possible that they import the results of their tion, both for use with a generic search engine. The own understanding of the game dh’ectly into their pro- strategic analysis performed by the program relates gn’am. In this case, it becomes difficult to determine a set of general knowledgesources to the details of whether the subsequent performance of the program the particular game. Amongother properties, this is due to the general theory it implements, or merely analysis determines the relative value of the differ- to the insightful observations of its developer about the eat pieces in a given game.
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Autonomous Horizons: the Way Forward Is a Product of the Office Air University Press 600 Chennault Circle, Bldg 1405 of the US Air Force Chief Scientist (AF/ST)
Autonomous Horizons The Way Forward A vision for Air Force senior leaders of the potential for autonomous systems, and a general framework for the science and technology community to advance the state of the art Dr. Greg L. Zacharias Chief Scientist of the United States Air Force 2015–2018 The second volume in a series introduced by: Autonomous Horizons: Autonomy in the Air Force – A Path to the Future, Volume 1: Human Autonomy Teaming (AF/ST TR 15-01) March 2019 Air University Press Curtis E. LeMay Center for Doctrine Development and Education Maxwell AFB, Alabama Chief of Staff, US Air Force Library of Congress Cataloging-in-Publication Data Gen David L. Goldfein Names: Zacharias, Greg, author. | Air University (U.S.). Press, publisher. Commander, Air Education and Training | United States. Department of Defense. United States Air Force. Command Title: Autonomous horizons : the way forward / by Dr. Greg L. Zacha- Lt Gen Steven L. Kwast rias. Description: First edition. | Maxwell Air Force Base, AL : AU Press, 2019. “Chief Scientist for the United States Air Force.” | Commander and President, Air University Lt Gen Anthony J. Cotton “January 2019.” |Includes bibliographical references. Identifiers: LCCN 2018061682 | ISBN 9781585662876 Commander, Curtis E. LeMay Center for Subjects: LCSH: Aeronautics, Military—Research—United States. | Doctrine Development and Education United States. Air Force—Automation. | Artificial intelligence— Maj Gen Michael D. Rothstein Military applications—United States. | Intelligent control systems. | Autonomic
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The Semantic
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Heuristic Evaluation Functions for General Game Playing
University of California Los Angeles Heuristic Evaluation Functions for General Game Playing A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Computer Science by James Edmond Clune III 2008 c Copyright by James Edmond Clune III 2008 The dissertation of James Edmond Clune III is approved. Adnan Y. Darwiche Thomas S. Ferguson Alan C. Kay Todd D. Millstein Richard E. Korf, Committee Chair University of California, Los Angeles 2008 ii Table of Contents 1 Introduction ................................ 1 1.1 General Game Playing: The Problem . 1 1.2 The Importance of General Game Playing . 2 1.2.1 Competitive Performance Metric . 2 1.2.2 Flexible Software Capabilities . 3 1.2.3 Game-Oriented Programming . 3 1.2.4 Generality as a Key Aspect of Intelligence . 4 1.2.5 A Timely Problem . 4 1.3 Overview of the Project . 5 1.4 Overview of the Dissertation . 6 2 Philosophy and Vision ......................... 8 2.1 The Ubiquity of Game Models . 8 2.2 Game-Oriented Programming . 10 3 Literature Review ............................ 13 3.1 General Game Playing . 13 3.1.1 Barney Pell’s Metagamer . 13 3.1.2 AAAI General Game Playing Competition . 14 3.1.3 Other General Game Playing Systems . 15 3.2 Automated Planning . 16 3.2.1 Classical Planning . 16 iii 3.2.2 International Planning Competition . 17 3.2.3 Planning Techniques . 18 3.3 Discovery Systems . 20 3.3.1 Feature Discovery . 20 3.3.2 AM and Eurisko . 21 3.3.3 Learning Heuristic Evaluation Functions . 23 4 General Game Playing Framework .................
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Will Impact Higher Education WEB
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Lorien Pratt, Ph.D. Curriculum Vita
Lorien Pratt, Ph.D. Curriculum Vita Sunnyvale, CA USA +1.303.589.7476 [email protected] Blog: www.lorienpratt.com SUMMARY Professional machine learning and decision intelligence consultant, developer, entrepreneur, writer, evangelist. Author of Link: How Decision Intelligence Connects Data, Actions, and Outcomes for a Better World. Co-organizer of the annual Responsible AI/DI Summit. Two TEDx talks. Inventor of machine learning inductive transfer. Co-Founder and Chief Scientist of Quantellia, LLC. Co-inventor and evangelist for Decision Intelligence. Over three decades delivering applied machine learning solutions, including for the Human Genome Project, the US Department of Energy, budget analysis for a $100 million annual spend for the Administrative Office (AO) of the US Courts, award-winning forensic analysis for the Colorado Bureau of Investigation, RBS, DARPA, and many more. EDUCATION Ph.D., Computer Science, Rutgers University, 5/93. Thesis: Transferring previously learned back-propagation neural networks to new learning tasks. M.S., Computer Science, Rutgers University, 5/88. A.B., Computer Science, Dartmouth College, 5/83. CONSULTING A variety of engagements including the following: Regular invited speaker to user groups, executive roundtables, keynotes, webinars, and workshops for organizations and companies like SAP, HP, Unisys, the TM Forum, Comptel, SAS. Machine learning consulting on a wide variety of projects for cyber security, web advertising, financial prediction, medical decision making, cable company capital expenditure, LIDAR image analysis, and more. Five-star rated consultant on the Experfy platform (www.experfy.com), from the Harvard Innovation Laboratory. Strategic consulting in decision intelligence, analytics, and telecom OSS/BSS to companies and organizations like the US Department of Defense, Solvina, ConceptWave, the Colorado Bureau of Investigation (CBI), Sun, IBM, Comptel, SAP, HP, Amdocs, Telcordia (now Ericsson).
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Knowledge-Based General Game Playing
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Ary, a General Game Playing Program
Ary, a general game playing program Jean Méhat,Tristan Cazenave Abstract We present our program Ary that won the 2009 and 2010 General Game Playing competition. In General Game Playing (GGP), players have to play games they never encountered before. The rules are trans- mitted as a description in a specific language and the player have to au- tomatically analyse the rules and select a method of playing. 1 Introduction The field of program playing games is an extensively explored field of computer science and more particularly of artificial intelligence as it is a domain where common methods of reasonning are to be applied, while offering a closed world, completely described by the game rules. Moreover the quality of the play is easy to evaluate quantitatively by observing the matches outcomes, and a human expertise has been developped. Great successes have been obtained: in many games, including chess, programs routinely outplay even the best human player. The program usually embed a important body of knowledge that is specific of the game they play. This knowledge is used by the designer beforehand and limit somewhat the generality of the program. While a program like Deep Blue is able to play well chess, it can not play a match of Checker, or even Tic Tac Toe: while an expert in its domain, the playing program is limited to one game in its abilities, and these are not easily extended to other domains or even to other games. The Logic Group at the university of Stanford addresses this limitation with GGP. In a GGP match, the players receive the rules of the game they have to play in a specific langage called Game Description Language from a Game Master.
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Barney Pell WSDM 2017 Conference Handout
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Design of the Remote Agent Experiment for Spacecraft Autonomy 1 3 3 1 3 3 Douglas E
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