Kaggle Ranks Data Scientists
Apr 13, 2012 (Close-Up Media via COMTEX) --
Kaggle, a platform for predictive modeling competitions, announced it is releasing its leaderboard of data scientists.
In a release, the Company noted the top ten data scientists active on Kaggle:
1. Alexander D'yakonov
An academic in the Faculty of Computational Mathematics and Cybernetics department at Moscow State University, D'yakonov modestly describes his favorite problem-solving technique as luck. Despite this, the Russian has earned a reputation for using methods known for their theoretical rigor and elegant simplicity. This helped him to win the dunnhumby Shopper Challenge, which asked competitors to predict the amount and timing of supermarket shoppers' next spends.
2. Sergey Yurgenson
Yurgenson has combined both of his areas of expertise to develop computational algorithms inspired by biology. Favoring neural networks, a type of learning algorithm modeled on how brain cells work, his best finish came in NASA's Mapping Dark Matter competition. To tackle the task of analyzing images of galaxies, Yurgenson combined several different kinds of neural networks.
3. Vivek Sharma
Sharma is now based in Delhi, where he has become one of Kaggle's most consistent performers. His recent best results were in the credit scoring competition Give Me Some Credit and in the Algorithmic Trading Challenge.
4. Jose Solorzano
Jose Solorzano is a software engineer based in Quito, Ecuador. He has previously worked on open source projects, including the robotics software behind Lego Mindstorms. Solorzano's software has been used to design a space junk collection system constructed entirely out of Lego pieces and put to test in orbit. His most notable Kaggle success was when he won Don't Overfit, a competition aimed at improving predictive algorithm strategies that attracted the attention of many of Kaggle's most enthusiastic users.
5. Xavier Conort
Conort is a French actuary whose adventures have taken him to Brazil, China, and Singapore, where he is currently based. He is the founder of Gear Analytics, a consulting firm that helps insurance firms and other companies use predictive modeling. His affinity for American car culture helped him win the hotly contested Don't Get Kicked competition, which asked Kaggle contestants to develop a mathematical model that can work out which used cars are most likely to be bad buys, or kicks.
6. Tim Salimans
Salimans is a Ph.D. candidate in econometrics at Erasmus University Rotterdam in the Netherlands. He triumphed in the World Chess Federation-sponsored Deloitte/FIDE Chess Rating Challenge on Kaggle. The task was to predict the outcomes of chess games, thus developing a better ratings system. Saliman's trick was to create a modified version of the method used by Microsoft to rate Xbox players, a variant that ended up being better than standard ranking algorithm.
7. Vladimir Nikulin
Nikulin has worked as an academic in Russia and Australia. A veteran of data mining competitions, he sees them as an essential part of the research process since they help researchers identify real from illusory progress in their methods. His best Kaggle finish was third place in the used car defect prediction challenge Don't Get Kicked.
8. David Slate
Slate holds more than half a century's experience in programming. He was building operating systems and cracking chess programs decades ago, winning the World Computer Chess Championship in 1977. A former academic at Northwestern University in Evanston, Ill., he spends his retirement entering Kaggle competitions under the moniker Old Dogs with New Tricks. His best performance on Kaggle came when he won the R Package Recommendation Engine competition for recommending software packages to users in the programming language R.
9. Yannis Sismanis
Sismanis is a researcher at IBM's Almaden Research Center in San Jose, Calif., where he works on data intensive analytics. Originally from Greece, his background is in electrical engineering and computer science. Sismanis won the first of two Kaggle competitions aimed at improving chess ratings systems, called Chess ratings - Elo versus the Rest of the World.
10. Jason Tigg
Tigg grew up on the Isle of Thanet in southeast England and goes by the alias PlanetThanet on Kaggle. At age 14, he used assembly language to build a program that could play Othello. He is based in London, where he works in the finance sector. Tigg's performances on Kaggle have been outstanding, notably in the Photo Quality Prediction competition and the Claim Prediction Challenge.
Kaggle runs predictive modeling competitions.
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