Mr.

I. Delivered the AI-enabled Natural Language Assistant for business applications to various businesses and customers during my tenure at TCS. Successfully onboarded a few customers who used the product in their production environment.

II. Lead Business Analyst at Carefirst BCBS with 17 years of experience in business analysis and IT, managing business needs and technological adaptability.
What I do: Lead Business Analyst with a proven track record of delivering innovative AI and IT solutions, with a focus on streamlining processes and enabling business agility.

Proficiency

● AI and Machine Learning

● Natural Language Processing (NLP) Applications

● Business Process Automation

● Software Development and Engineering

● System Architecture and Algorithm Design

● Research and Development

● Project Management

● Technical Leadership

● Continuous Learning and Adaptability

● Emerging Technologies (AI, Blockchain)

Academic Excellence

Developed Educational iOS Applications: As a Graduate Assistant at Hofstra University, I developed two iOS applications—Circuit Math and TOPS. These applications enabled young children to learn mathematics in a game-based, interactive manner, fostering interest and engagement in learning. My work was featured in Hofstra Horizons magazine in Spring 2013. ● Hofstra Horizons Spring 2013 (Title Page, and Pages 18–21)


Published Research Papers 1. An Architecture for Intelligent Email-Based Workflow Interface to Business Applications 2. Enabling Email-Based Conversational Interface to Business Applications 3. Framework for Text-Based Conversational User-Interface for Business Applications


Judging/Reviewing Opportunities Served

● Peer Review of Research Papers at TCS: During my tenure at TCS, I had the opportunity to peer review research papers authored by my team. As a core developer of the product that these papers were based on, I provided valuable technical feedback and insights to ensure the quality and accuracy of the work. The reviewed papers include: 1. Method and System for Obtaining Semantically Valid Chunks for Natural Language Applications 2. Ontology-Driven Approach to Obtain Semantically Valid Chunks for NL-Enabled Business Applications 3. Finding Semantic Correlation in Structured Data from Unstructured Notes