Part-Time Lecturer, Khoury College of Computer Sciences
Biography
Dr. Smruthi Mukund joined the faculty at Northeastern University in Silicon Valley in 2020. With over 20 years of industry experience, she bridges academic rigor with real-world insight, specializing in Machine Learning, Natural Language Processing, Large-Scale Data Mining, Artificial Intelligence, and Information Retrieval. She is deeply passionate about designing and developing ML and big data solutions that positively impact millions of people while creating scalable solutions for complex business problems.
As the Head of AI/ML for Consumer Banking at JPMorgan Chase, Dr. Mukund is at the forefront of developing impactful and scalable machine learning solutions that directly benefit millions of customers and achieve key business objectives. Her distinguished career prior to JPMorgan Chase includes leadership roles in advanced research and development at prominent tech giants such as eBay, Amazon (including Amazon Alexa), and Twitter. Across these roles, her work encompassed diverse applications of natural language processing, from refining search capabilities and e-commerce ranking to enhancing fraud detection and query understanding.
Dr. Mukund is also actively engaged in the evolving landscape of AI, with a particular research focus on responsible AI and bias detection within machine learning systems, especially pertinent given the growth of generative AI in finance.
Education
- PhD in Computer Science, SUNY Buffaly
- MS in Computer Science and Engineering, SUNY Buffalo
- BE in Electrical and Electronics, BMS College of Engineering
Publications
Research Interests
Dr. Mukund’s research into fact-checking and hallucination detection is a critical area in the field of AI, particularly with the rise of Generative AI. This work involves developing and applying machine learning models to identify when an AI-generated text or image presents false or nonsensical information. This is a crucial guardrail that must be in place for successful AI integration at enterprise scale.
In addition, she works on agentic AI for data management with a focus on large, complex datasets. She focuses on the real-world constraints faced by the financial industry and other sectors where data must be handled at all times with high levels of automation, precision, compliance, and security.
Dr. Mukund’s research aims to make AI more trustworthy and robust by building systems that can verify information and autonomously manage the data they operate on.
