Amita M.

Applied Science, AGI, MultiModal, IR, Knowledge Graph

San Francisco Bay Area

About

Innovative leader in applied science and AI, specializing in developing scalable machine learning solutions. I have led cross-functional teams to drive advancements in Generative AI, Multilingual, and MultiModal Search capabilities. Passionate about leveraging cutting-edge technology to solve complex problems.

Experience

  • Adjunct Professor at University of California, Santa Cruz
    Sep 2022 - Present · 3 yrs 10 mos

    I teach Generative AI at UCSC NLP Program. The course explors the practical applications of deep generative models across diverse domains, including natural language processing, computer vision, reinforcement learning, and retrieval augmented generation for information retrieval.

  • Applied Science Head (Generative AI and MultiModal Search) at Amazon
    Jul 2021 - Present · 5 yrs

    Managing a cross-functional team of Applied Scientists, Engineers, and Managers, to deliver transformative innovation through Generative AI at Amazon's AGI. I lead the development of scalable machine learning systems that power multilingual Question-Answering systems, Knowledge Graph & Reasoning and MultiModal Search capabilities across the Amazon AGI

  • NLP Lead Scientist at IBM watson
    Jun 2018 - Jul 2021 · 3 yrs 2 mos

    • Led the development and productization of novel NLP algorithms for IBM Watson's Natural Language Understanding (NLU) cloud service for advanced text analytics. • Designed proof-of-concept and prototypes for a novel explainable framework to improve customer retention. • Developed various compression techniques to improve inference time of machine learning models leading to cost savings for production systems. • Collaborated with research and product teams across multiple geographies to introduce new and improve existing NLP algorithms for IBM's NLU cloud.

  • Graduate Research Scholar at UC Santa Cruz
    Sep 2012 - Jun 2018 · 5 yrs 10 mos

    - Developed techniques to recognize the specific arguments and counter arguments people tend to advance and group them across discussions as Facets in Social media conversations. - Developed a systematic approach to leverage pyramid based summarization framework to identify central arguments in social media dialogue. ( NAACL 2015) - Developed a novel method for ranking arguments in conversational data. ( Semdial 2017) - Introduced a new task of Argument Facet Similarity (AFS), and created a novel corpus of dialogic arguments aimed at identifying various facets across opinionated dialogue. (SIGDIAL 2016) - Developed topic-independent features for classifying (dis)agreement in online dialogue. ( SIGDIAL 2013)

  • Research Intern at IBM Almaden Research Center
    Jun 2017 - Sep 2017 · 4 mos

    Developed a novel antonym dictionary based method for sentiment analysis in customer service data.