o PI (Principal Investigator) for the NIST AI Safety Institute focussing on AI Red Teaming, Guardrailso Incubating Generative AI Guardrails, Augmentation & Explainability as well as LLM Red Teamingo Leading the E3 COE (Experimentation, Explainability & Ethics) incl Feature Store and MLOps o Previously part of the "fraud squad" team reporting chain to the Chief Analytics Officer, developing & deploying business critical AI/ML systems for Credit Card Fraudo Ex Co-lead : Bank Policy Institute (BPI) Explainability WGo Drove bank-wide AI innovation Strategy (focusing on AIOps, Ethics, Trust & Explainability) spanning industry, regulations and business stakeholders as part of the Chief Digital Officeo Worked on multiple projects viz. Explainable Loan Underwriting using AI, document extraction (contracts, statements), predictive services based on inferences from applying advanced NLP technologies on customer conversations/customer transactions and Enterprise Knowledge Graph (initial phases)

Part of core team - Participating in v2 discussions; AI Red Teaming; Tracking LLM/generative AI Security/Safety/Trust developments and publishing newsletter

Interesting collaborative work on "A Practitioners Guide To Explainability" viz.,Framework & Best Practices on Explainability, Bias & Disparate Action Mitigation et al, with detours into Use Cases and Definitions

Scoring data from multiple sources incl chain transactions

o Autonomous Mobile Fleet Management Stack : Building Self Orchestrating Distributed Decision-Making System for Autonomous Smart City Mobility (people, vehicles and services in a grid world) & Negotiating AI using Reinforcement Learning and Nash Equilibriumo Deep Learning/ML models & AI for Autonomous driving [ https://youtu.be/BRxewhfJH6g ], Lane Detection &, Object Detectiono Models : nVidia AI autonomous driving, SSD (Single Shot Multi Box) CNN Object Detection, Canny Edge/Hough Transformo (Exploring) Knowledge Graph, Conversation/Dialog for Contextual Semantic Intelligence for next generation autonomous carso (Exploring) Swarm Intelligence and Intelligent Infrastructure for smart cities w.r.t autonomous vehicles & Blockchain based fabric

Stealth Travel Startup : Building Recommendation of whom to meet, using social & interest graphs, time graph semantics for travel, NLP/DL & word2vec

Consulting : Data Science/Analytics Systems for Retail (Conn’s) – Credit Line Analysis, Next Purchase Prediction, Recommendation & Mailing List Analytics for Personalized consistent experience across channels w/ data driven automation

Increased the ability to sell more ads deterministically (forecasting, decision systems); nudged towards audience aware TV Ad Control Plane for I3 – Insights, Inference & Intelligenceo Decision Data Science: Analytics Dashboards for Platform Reach, Activity Inferences & Diagnostic Analytics, Ad Inventory Supply & Utilizationo Product Data Science: Tuneaway/Audience clustering for higher CPM addressability, Target audience forecastingo 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 generationo 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]

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 technologieso Founding Lead : AI & Robotics Group with Digital Enterprise Systems & Services Groupo Architecture Head for a team of ~20 Big Data Architects/Data Scientists (April-Nov 2013)o Incubated projects with a team of ~30, mostly offshoreo Increased awareness of company with students and conducted recruiting events at Stanford University for Recruiting & Academic Research Alliance

Genetics/BioInformatics based Scientific/Consumer feature set, using Python, MongoDB & Javao Architecture, Design & Coding of SaaS application incl REST API stack, DevOps & ScrumMaster for the teamo Developed Python based blackboard framework for Recommendation Engine (BioInformatics) & Risk Rankingo 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 2Factor authC & HIPAA compliance

Leading initial Engineering Team building a Big Data Platform for a combination of Scientific & Consumer feature sets in the genomic space

o Architecture, Implementation & Devops for Cloud Object Store layer - 10X scaling to 10Billion objects & 10 PBo 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

o Project Lead/Infrastructure optimization across compute-storage-network for Hadoop Cloudo 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 nodeso 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/rfc6208o Architecture & implementation of Precision Distributed Time Sync (IEEE1588) & GPS interface for financial customers/trading deskso Worked with customers to solve time sync requirements of the order of 50 μso Wrote code for implementing of IEEE1588v2 & completed interop-fest in Vienna Conference/Workshopo 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 CrossBowo Industry acceptance via collaboration with IBM on architecture specification (http://www.ibm.com/developerworks/autonomic/library/ac-summary/ac-cisco.html)

* 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!