Kartik Singh Email and Phone Number

1. Digital AI Assistant: Created a conversational AI which can engage in contextual conversations with users around recent news, mood, and jokes etc. The AI assistant can interact with other lab demos and give clients a walkthrough of the I&D's departments capabilities. 2. Document Clustering: Implemented text mining and clustering techniques on the descriptions, tags, metadata etc to group similar documents (search results of a huge knowledge base repository platform) by grouping the search results into meaningful labelled clusters and presented via an interesting and navigable Voronoi visualization3. Semantic Search and Graph Databases: Represented the documents in the form of a semantic ontology to build a semantic relationship between the documents. Utilised graph database to store the ontologies developed and created a Rshiny application to view the documents and their associations as a D3 network visualisation.4. Natural Language Query: Used state of the art transformers (BERT based SQLova) to perform natural language queries and wrote utilities for it5. Whitepaper on multi-agent Robotic Systems: Explored technologies and frameworks for designing an autonomous software robotic system for a conversational assistant. The goal was to design a multi-agent robotic system for a conversational assistant

1. Worked on Agent-Based Modeling to Understand Consumer Behavior. Captured consumer behaviour captured using bayesian causal networks and enabled Client to devise an effective marketing strategy in the wake of a new product launch.2. Implemented Algorithmic Trading using Reinforcement Learning where an autonomous pair-trader based on SARSA Reinforcement Learning model is used to decide the optimal action (Enter/Exit trade or Do nothing) at any given time and state of the trade3. Built a Face Recognition System using FaceNet and ReactJS which is an end-end prototype of a facial recognition system to identify employees for secured access to Mu Sigma's Innovation and development lab.4. Developed multiple components in R, Python and Javascript (UI) for a unified ML model deployment and management platform and enabled enterprises to deploy intelligence and manage algorithms in production.

Lead the Battery Recycler in setting up of their Technology Stack and Data Science capabilities. Built Real-Time monitoring platform for the deployed batteries along with ML models to predict the state of Health of Lithium-Ion Batteries

Contributed with multiple blogs on technical and non-technical topics related to Data Science

Contributed with blogs on Web Scraping ranging from async web scraping to scraping for competitor analysis and affiliate marketing