I am currently the TLM for the Google+ stream quality team. In the past, I have been a researcher in various fields of computer science and natural science * WARFT, India(computer architecture, supercomputing, benchmarking, computational neuroscience) * Duke University, USA (algorithms, algorithmic self-assembly, DNA self-assembly, DNA nanoscience * Microsoft Research Cambridge, UK (DNA self-assembly, computational simulations) * Google Inc., USA (BigData analysis, computational sociology, information retrieval)

Tech Lead Manager @ Google+ Stream Ranking, Google+ Search Ranking, Google+ Content Recommendations and YouTube Comment Ranking Lead and manage the engineering teams that power stream ranking (https://plus.google.com/), search ranking (https://plus.google.com/s/physics), content recommendations for Google+ (What'sHot and Recommended posts and https://plus.google.com/explore/_) and comment ranking on YouTube videos My team specializes in * Machine learning: Design of optimization functions, feature engineering, model generations using high dimensional regressions, online learning using multi-armed bandits, collaborative filtering and recommendation systems using clustering and high dimensional embedded models etc. * Data Science: Big data analysis of user behavior and behavioral modeling using standard techniques such as MapReduce etc. * Low Latency, Large Scale Information Retrieval: Design, implementation and evaluation of multiple low latency, high throughput, scalable algorithms for retrieving, scoring and ranking Google+ posts for both stream ranking and search ranking. From October 2015 to Present (3 months) San Francisco Bay AreaSenior Software Engineer @ Worked on Google+ Stream Ranking * Designed, implemented and evaluated multiple ranking algorithms * Design and implementations of multiple objective functions and feature engineering for high dimensional machine learnt models * Big data analysis of user behavior using MapReduce and logs analysis * Design and implementation of various low latency, high throughput, scalable algorithms for information retrieval From October 2014 to September 2015 (1 year) San Francisco Bay AreaSoftware Engineer @ Google+ Stream Ranking, Google+ Search Ranking, YouTube Comment Ranking From October 2012 to September 2014 (2 years) San Francisco Bay AreaTeaching Assistant @ Teaching assistant for multiple undergraduate and graduate level couses in algorithms: Design and Analysis of Algorithms Duke University (Fall 2008, 2009, 2011) Operating Systems Duke University (Spring 2011) Algorithms in the Real World Duke University (Spring 2011) From August 2007 to September 2012 (5 years 2 months) Research Assistant @ Research Assistant to Prof. John Reif with research into tiling theory, algorithmic self-assembly, complexity theory, probabilistic analysis, DNA self-assembly, DNA nanotechnology and synthetic biology From August 2007 to September 2012 (5 years 2 months) Research Intern @ Programed and model-checked various localized hybridization networks using various in house tools. Worked with other team members to extend the syntax and semantics of the tools and suggested vital performance improvements. From May 2011 to August 2011 (4 months) Cambridge, United Kingdom

PhD, Computer Science, GPA: 3.9 @ Duke University From 2007 to 2012 MS, Computer Science, GPA: 3.9 @ Duke University From 2007 to 2010 Certificate, Nanoscience, 4.00 @ Duke University From 2007 to 2012 BE, Computer Science and Engineering, GPA: 3.7 @ Anna University From 2003 to 2007 Harish Chandran is skilled in: Algorithms, C++, C, Java, Nanoscience, Information Retrieval, Big Data, Machine Learning, LaTeX, Algorithm Design, Computer Science, Distributed Systems, Scalability, MapReduce, High Performance Computing, Parallel Computing