2017 Kaggle Involvement Program Results

2017 Kaggle Involvement Program

We are excited to honor the winners of the 2017 Kaggle Involvement Program. These SOA members and candidates accepted the challenge to create solutions for unique data science challenges, from improving cancer detection techniques to reducing the human footprint in the Amazon rain forest. They also received cash prizes for finishing within the top 10 or 25 percent of their respective competitions.

Competition

Data Science Bowl 2017: Can you improve lung cancer detection?

Using a data set with thousands of high-resolution lung scans, the Data Science Bowl asked participants to develop algorithms that could dramatically improve the accuracy of determining when lesions in the lungs are cancerous. Learn More

Member/Candidate Teams	Finish
Yashvir Kumar Prasad ASA,CERA	Top 25%
Michael Yue Xiao FSA,CERA,MAAA Martin Ball (Candidate) Tim Rimnac Yitong Gao	Top 25%

Intel & MobileODT Cervical Cancer Screening: Which cancer treatment will be most effective?

Challenged to improve the cervical screening process, Intel and MobileODT asked participants to develop an algorithm that uses images to identify a woman’s cervix type. Learn More

Member/Candidate Teams	Finish
Chen Yang ASA Yaofei Xiong	Top 10%
Michael Yue Xiao FSA,CERA,MAAA Tim Rimnac	Top 10%
Moshe Daniel Radinsky ASA,MAAA,ACA Mendel Friedman ASA,MAAA Tim Jarvis ASA,MAAA Ilana Radinsky	Top 25%
Nicholas Wei-Ming Hsu FSA,CERA,FCIA Udit Pareek (Candidate) Zijing Li (Candidate)	Top 25%

Planet: Understanding the Amazon from Space: Use satellite data to track the human footprint in the Amazon rainforest

Planet and its Brazilian partner SCCON challenged participants to label satellite image chips with atmospheric conditions and various classes of land cover to help solve the problem of global deforestation. Learn More

Member/Candidate Teams	Finish
Fan Fei Chong (Candidate) Charles David Cadman FSA,MAAA,CERA Alexander Matia	Top 10%
Kailan Shang FSA,ACIA	Top 10%
Benjamin Roberts ASA Justin Conant	Top 25%
Gary Stanford FSA, MAAA, FCA Jason Altieri ASA,MAAA Sarah Prusinski ASA,MAAA Ben Copeland (Candidate) Matthew Hawthorne Steve Gredell	Top 25%
Michael Yue Xiao, FSA,CERA,MAAA Martin Ball (Candidate)	Top 25%

The Nature Conservancy Fisheries Monitoring: Can you detect and classify species of fish?

Based on video footage, The Nature Conservancy asked participants to develop a model that automatically detects and classifies species of fish to better target conservation efforts. Learn More

Member/Candidate Teams	Finish
Dale Jacob Cap ASA,MAAA	Top 10%
Stuart James McCroden ASA,CERA,MAAA	Top 10%

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