8+ year research experience on large-scale data mining and machine learning with big data (petabyte scale) hands-on experiences. • Coding/hacking: - Writing production code in Scala/Java with a focus on large-scale real-time data science features, e.g. clustering, classification, anomaly detection, ranking and recommendation. - Judge (2013), 1st prize winner (2012), 2nd prize winner (2011), Bay Area Intern Open Hackathon, hosted by Linkedin • Research Results: (1) published in premier conferences and journals, including KDD, WWW, ICDE, ICDM, CIKM, SDM, TKDE and SADM (2) papers been selected as Best of Conference: ICDE (2012) and SDM (2010). best paper runner up award in APWeb (2014). (3) a number of US patents filed (by eBay, Linkedin and Sumo Logic, respectively) based on my research (4) Professional activities: - Program committees: KDD'13, CIKM'13, KDD'14, KDD'15, IJCAI'15, CIKM'15, KDD'16 - Session chair of "Learning and applications"​ track in CIKM'13. - (External) reviewers of a number of conferences and journals, including ICDM, WWW, WSDM, ECML, SDM, ER, APWEB, PAKDD, DMKD, TKDD, TKDE, KAIS, etc. • Types of data I am working on: Massive Graphs, Links, Social Networks, Social Media, Streams, Text, Uncertain Data, Metrics, APM, Unstructured Data (e.g. log), etc. • Research Problems I am solving: Clustering, Classification, Regression, Outlier Detection (Anomaly Detection), Stream Mining, Data Representation, Compression, Visualization, etc. • Tools I am using: Java, Scala, Spark, Elastisearch, MapReduce (Hadoop), Pig, Hive, R, C, C++, C#, SQL, Python, Weka, etc.

Yuchen Z. is skilled in: Data Mining, Data Science, Data Analysis, Machine Learning, Social Computing, Graph Algorithms, Clustering, Classification, Anomaly Detection, Information Retrieval, Text Mining, Business Intelligence, Hadoop, MapReduce, Weka