"Data Wrangling for Kaggle Data Science Competitions – An etude" pycon 2014 tutorial http://goo.gl/Ih9a8f Data Science Folk Knowledge - http://www.slideshare.net/ksankar/data-science-folk-knowledge •• Programming Committee - KDD 2013/KDD2014 (Knowledge Discovery & Data Mining) http://goo.gl/2jdzR ••• Tutorial on Twitter at OSCON 2012 http://goo.gl/KyX16 ••• OSCON Interview http://goo.gl/86Qhc ••• pydata Tutorial : Naive Bayesian http://www.slideshare.net/ksankar/pydata-19 ••• Blog : "Is our Neocortex a giant Semantic Bloom Filter ? Of Natural Intelligence, Machine Learning & Jeff Hawkins" http://goo.gl/QLJnN ••• Blog : "Is it still #ArtificialIntelligence, if our Computers learn -to think- from the workings of our Brain ?" http://goo.gl/4JpeZ1 Top 2% Most Viewd Slideshare ! http://goo.gl/lcEYbP

Consulting Data Scientist @ Consulting : Data Science/Analytics Systems for Retail (Conn’s) – Credit Line Analysis, Next Purchase Prediction, Recommendation & Mailing List Analytics From June 2015 to Present (7 months) Chief Data Scientist @ Stealth Travel Startup : Building Recommendation of whom to meet, using social & interest graphs, time graph semantics for travel, NLP/DL & word2vec From March 2015 to Present (10 months) Chief Data Scientist @ Increased the ability to sell more ads deterministically (forecasting, decision systems); nudged towards audience aware TV Ad Control Plane for I3 – Insights, Inference & Intelligence o Decision Data Science: Analytics Dashboards for Platform Reach, Activity Inferences & Diagnostic Analytics, Ad Inventory Supply & Utilization o Product Data Science: Tuneaway/Audience clustering for higher CPM addressability, Target audience forecasting o Architecture & Design of Ad Inventory Forecasting Analytics - Model Performance Evaluation, Algorithms (ARIMA et al) & Parameters o E2E architecture, feature extraction & models for Ad Optimization & Engagement Analytics based on Kaplan-Meir Curves, Multi- armed Bandits (future), Composite Ad Maps & Reverse Recommendation and Inferred Complex Composite Profile generation o Time Distribution: 1/3rd work with Business/Customers, 1/3rd Data Wrangling and 1/3rd on Data Science Mechanisms/Algorithms o Architected & Bootstrapped Analytics Infrastructure [Hadoop, Spark, python & R] From March 2014 to June 2015 (1 year 4 months) Principal Architect/Data Scientist @ Projects: Data Science of Recommendation (Australian Bank/Spark framework), Common Learning Framework for 2-way Inference/Recommendation Engine across consumer products (Pharma/J&J), Predictive Analytics (Engine Manufacturing/Cummins), Social Media Analytics (CPG/Pepsi, Answered “Who is an NFL Fan” based on Twitter/Datasift), Retail Analytics across multiple brands (.com, brick & mortar for a Fortune 10 retailer/Walmart) & Device Log Analysis (computer manufacturer/HP) o Technical & Business Architecture of Data products – Interface (Google Glass et al), Inference (ML/AI) & Intelligence § A dual role of customer engagements & product/solution accelerators based on NLP, NLU, Hadoop, NOSQL, R, Contemporary AI (Deep Learning), Social Analytics & Data Science technologies o Founding Lead : AI & Robotics Group with Digital Enterprise Systems & Services Group o Architecture Head for a team of ~20 Big Data Architects/Data Scientists (April-Nov 2013) o Incubated projects with a team of ~30, mostly offshore o Increased awareness of company with students and conducted recruiting events at Stanford University for Recruiting & Academic Research Alliance From January 2013 to March 2014 (1 year 3 months) San Francisco Bay AreaDirector Engineering & Data Science @ Genetics/BioInformatics based Scientific/Consumer feature set, using Python, MongoDB & Java o Architecture, Design & Coding of SaaS application incl REST API stack, DevOps & ScrumMaster for the team o Developed Python based blackboard framework for Recommendation Engine (BioInformatics) & Risk Ranking o Design, Deployment & Ops : Operational & Analytics Infrastructure – AWS VPC Cloud & NOSQL - MongoDB w/replicasets o Cloud stack Forensic Analysis & Hardening; Inducted into Infraguard (CyberSecuity) group; Security with features incl 2 Factor authC & HIPAA compliance From July 2012 to December 2012 (6 months) Lead Software Engineer - Data Scientist @ Leading initial Engineering Team building a Big Data Platform for a combination of Scientific & Consumer feature sets in the genomic space From February 2012 to July 2012 (6 months) Lead Architect @ o Architecture, Implementation & Devops for Cloud Object Store layer - 10X scaling to 10Billion objects & 10 PB o Object store security services – Encryption & Key Infrastructure with granular security layers o Project Lead/SSO/SAML SaaS Integration & other cloud security primitives o Writing code for parts of the distributed horizontally scalable infrastructure incl ZooKeeper, last mile load test, MySQL & Key Infrastructure From April 2011 to February 2012 (11 months) Distinguished Engineer @ o Project Lead/Infrastructure optimization across compute-storage-network for Hadoop Cloud o Hadoop job qualification & quantification (CPU Intensive (e.g Blast-P), I/O intensive (map processing, cell phone device logs et al)); Design for optimization of shuffle by using Top Of Rack storage nodes o Built CTO Big Data Cloud Concept Lab (C3L)with Cisco UCS - Good hands on work, from scratch! o On different projects at CTO’s Office (Cloud Computing & Big Data Cloud), different BUs including Policy management, ApplicationOrientedNetworking (AON)-Internal Startup, Cisco Services (CA) & Global Government Solutions Group (Federal Projects) o Developed Compute & Data Cloud Architectures: o AWS, OpenStack Ref.Arch, Intercloud [http://goo.gl/C8WsC], SNIA CDMI, IETF RFC 6208 http://tools.ietf.org/html/rfc6208 o Architecture & implementation of Precision Distributed Time Sync (IEEE1588) & GPS interface for financial customers/trading desks o Worked with customers to solve time sync requirements of the order of 50 μs o Wrote code for implementing of IEEE1588v2 & completed interop-fest in Vienna Conference/Workshop o Designed & developed Network-protocol & algorithmic primitives for a strategic project with a logistics customer for Policy-Based Traffic-Shaper (for data access & time capsule primitives) including 1M element disk-based in-memory priority queues o Architecture & design of network-centric projects & contribution to standards for Federal Government; network & systems level presentations at Pentagon [http://goo.gl/iAUBD] (GGSC – Global Government Security Solutions Group) o Internalize, prototype and evangelize locus & trajectory of Sensor Networks; o Prototyped AON based solution, worked with BD to evaluate investment opportunities to the IRB & succeeded in getting investment in wireless sensor company CrossBow o Industry acceptance via collaboration with IBM on architecture specification (http://www.ibm.com/developerworks/autonomic/library/ac-summary/ac-cisco.html) From January 2000 to April 2011 (11 years 4 months) Technology Advisor @ * Startegic Architecture of wireless/fingerprint security products * Advise on pragmatic implementation of 802.1x, PKI and other security standards * We won one of the DEMO2006 INNY - INspiring INnovation awards! From July 2005 to January 2008 (2 years 7 months) Security Architect at eSpeak @ From 1995 to 1996 (1 year)

Master’s Degree, Computational Finance/Risk Management(CFRM) @ University of Washington From 2015 to 2018 Graduate Certificate-Data Mining/Statistics, Dept Of Statistics @ Stanford University From 2011 to 2016 Master of Business Administration (M.B.A.), Business Administration and Management, General, Finished ~40% with 3.8 GPA @ University of Michigan From 1991 to 1993 Master’s Degree, Computer Science, 4.0 @ University of Detroit Mercy From 1985 to 1985 Krishna Sankar is skilled in: Distributed Systems, Cloud Computing, Big Data, Hadoop, Scalability, SaaS, Java, Analytics, Agile Methodologies, Enterprise Software, Perl, Software Design, Linux, Architecture, Data Mining