Hi, this is Mitul Tiwari, I am a Director of AI and Machine Learning Engineering at ServiceNow. Previously, I was the CTO and Cofounder of Passage AI, a conversational AI company. Earlier I was part of Search, Network, and Analytics Group at LinkedIn as Head of People You May Know and Growth Relevance. Previously, I worked at Kosmix as a Member of Technical Staff. I completed my PhD in Computer Science from University of Texas at Austin in 2007. Earlier I received my under graduation as a Bachelor of Technology in Computer Science and Engineering from Indian Institute of Technology, Bombay in Summer 2001. I joined UTCS in Fall 2001, and earned my Master of Science in Computer Science in 2003.

At ServiceNow, I lead development of natural language processing driven production features including Conversational AI, Incident Auto Resolution, Question-Answering for Search, and Text2Code for Workflows. We are building next generation of Natural Language Processing technologies using some of the latest Language Models and Deep Learning techniques and scaling to hundreds/thousands of large enterprise customers to improve work experience of 70M+ enterprise users.

At Passage AI, I built a conversational AI platform using the latest Deep Learning and Natural Language Processing technologies. Passage.AI's natural language understanding and processing platform can be used to create a intelligent conversational interface for any website or business.

At LinkedIn, I worked on data driven products such as "People You May Know" (PYMK). PYMK is a large-scale social recommendation system that analyzes billions of edges to predict social connections. Using Hadoop, PIG, Clojure, Machine Learning algorithms.

At Kosmix, I worked on document/tweet/query categorization, concept mining, query parsing, query expansion, and relevance of search results to improve the quality of pages generated for any given topic. I also worked on building high performance, scalable systems for data fetching, data storage, and distributed processing.

At UT Austin, I worked on algorithms for emerging network applications. In particular, my research focused on designing self-tuning algorithms for distributed resource allocation, especially for caching, monitoring, and scheduling problems. My advisor at UT Austin was Greg Plaxton. I also interacted with Harrick Vin and Mike Dahlin.

In the past I have worked with Soumen Chakrabarty and Inderjit Dhillon on web mining, clustering, and other data mining problems.

My interests include machine learning, AI, search, distributed systems, and network algorithms.