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Arup Das

  • Specialist Professor

Department: Computer Science and Software Engineering

Office: James and Marlene Howard Hall 235

Phone: 732-571-3596

Email: adas@monmouth.edu


Joining Monmouth University as a full-time faculty member in 2024, Arup Das is an expert in Artificial Intelligence and Machine Learning, with extensive experience in applied AI and the generative AI industry. As the Head of AI & Gen AI Industry Specialists at UiPath, he advised and lead initiatives to advance AI and generative AI-driven document and communication automation across diverse sectors such as financial services, healthcare, manufacturing, and the public sector. Along with building high-performing AI/ML teams, his professional journey includes Avenue One, Compass, and Machine Analytics, where he developed low-code AI platforms and advanced natural language processing (NLP) solutions. Arup’s experience extends to digital strategy, product management, process engineering, and the development of modern data infrastructures

Education

MBA, Cornell University

MS, Analytics, Data Mining & Machine Learning, Villanova University

MS, Computer Engineering, Stony Brook University

Research Interests

Federal Reserve meeting minutes analysis using NLP, Twitterverse – NLP Analytics

Books

The Generative AI Practitioner’s Guide: How to Apply LLM Patterns for Enterprise Applications, Arup Das and David Sweenor, Tiny Tech Books, 2024

Popular Articles

Creating a Culture of Innovation, ALA Legal Management, Mar 8, 2019

How to Approach Legal Innovation: Options for Every Firm, Law Technology Today, Jan 17, 2019

There’s a Bot for That, Law Practice Today, Dec 18, 2018

2019 Budget Planning: Tips to Increase IT Department ROI, Legal Tech News, Nov 15, 2018

Leadership and a Strategy: Your Keys to Creating an Innovation Program, ILTA’s Peer to Peer Magazine, Nov 8, 2018

Staying Strategic in a Sea of IT Distractions, Legal IT Insider, Jul 13, 2018

Block Chain 101 – What Lawyers Need to Know Now: Attorney at Work, May 21, 2018

Tech Tips for Mid-size Firms, ABA Law Technology Today, Mar 28, 2018

Key Considerations When Starting an AI Program, Legal Ink, Mar 2, 2018

The Changing Landscape of Legal IT, ABA Law Practice Today, Feb 15, 2018

Is your IT Department Innovative Enough?, ILTA’s Peer to Peer Magazine, Feb 13, 2018

2018 trends to watch: Smart-sourcing Legal IT, ALM’s Legaltech News, Dec 18, 2017

Artificial Intelligence – Knowing when it’s Right for Your Firm, ALM’s Cyber Security Law and Strategy, Dec 1, 2017

Digital Transformation – How Innovation is Becoming as Important as Good Lawyering, ABA Law Technology Today, Nov 22, 2017

Artificial Intelligence 101 – What Lawyers Need to Know, Legal Ink, Sep 18, 2017

Artificial Intelligence 101: What Lawyers Need to Know, Legal Ink Magazine, Oct 1, 2016

Professional Associations

Advisory Council Member, Villanova School of Business 2017-2019

Advisory Council Member, Cornell University 2016-2018

Member, 101 Blockchains

Advisor, Center of Business Analytics, Villanova University

Awards

Thought Leader of the Year, ILTA, August 2018

Additional Information

Patent: Business Workflow Map: US 62101284 · Filed Jan 1, 2015

Courses

Recently Taught Classes

2025 Spring

  • Applications for Data Science – DS 650
  • Computer Programming Essentials – CS 501A
  • Introduction to Computer Programming for Data Science I – DS 502
  • Introduction to Computer Science I – CS 175
  • Spectp: Natural Language Proces in Ds – DS 598

2024 Fall

  • Advanced Data Science Techniques – DS 655
  • Applied Machine Learning – CS 620
  • Data Analytics: Concepts and Techniques – DS 520
  • Ethics and Bias in Ai – DS 517

2024 Spring

  • Applications for Data Science – DS 650
  • Practicum in Data Science II – DS 695B

2023 Fall

  • Legal, Ethical and Privacy Issues in Data Science – DS 515
  • Practicum in Data Science – DS 695A

2023 Spring

  • Practicum in Data Science II – DS 695B
  • Spectp: Natural Language Proces in Ds – DS 598

2022 Fall

  • Legal, Ethical and Privacy Issues in Data Science – DS 515
  • Practicum in Data Science – DS 695A

Frequently Taught Classes

  • Advanced Data Science Techniques (DS 655)
  • Applications for Data Science (DS 650)
  • Applied Machine Learning (CS 620)
  • Data Analytics: Concepts and Techniques (DS 520)
  • Ethics and Bias in Ai (DS 517)
  • Legal, Ethical and Privacy Issues in Data Science (DS 515)
  • Practicum in Data Science (DS 695A)
  • Practicum in Data Science II (DS 695B)
  • Spectp: Natural Language Proces in Ds (DS 598)