Smruthi Mukund

(she/her/hers)

Part-Time Lecturer

Smruthi Mukund
  • Data science 
  • Machine learning 
  • Natural language processing
  • Language modeling

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. In the context of finance, where accuracy is paramount, this research is crucial for building reliable AI systems that can’t “hallucinate” or invent data.

Her work on agents for data management focuses on creating intelligent, automated systems that can handle large, complex datasets efficiently and securely. These “agents” are essentially AI models designed to perform specific tasks, such as cleaning, organizing, and preparing data for analysis or for use by other AI systems. This is especially relevant in fields like finance, where managing massive amounts of customer data requires high levels of automation, precision, and security.

Essentially, 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. This focus on responsible AI and bias detection ensures that AI systems are not only effective but also fair and reliable for end-users.

  • PhD in Computer Science, SUNY Buffalo 
  • MS in Computer Science and Engineering, SUNY Buffalo 
  • BE in Electrical and Electronics, BMS College of Engineering

Smruthi Mukund is a part-time lecturer at the Khoury College of Computer Sciences at Northeastern University, based in Silicon Valley, where she shares her expertise in algorithms and machine learning. 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.

As the head of AI/ML for consumer banking at JPMorgan Chase, 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. 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.