One Year Full Time MBA (PGPX)




Prerna Luthra

Prerna Luthra

Software Engineer with 6.9 years of experience in Data & AI in USA, leading high-impact projects, optimizing backend systems, and driving AI tool development like chatbots. Strong AI innovation background recently led medical imaging research at New York University with results presented in top forums.

Work Experience

Live Project - Gen-AI powered Knowledge Management System for IIMA | BCG X

  • Developed a Knowledge Management System platform as a part of 3 member team using Large Language Models (LLMs) to assist students and administration at IIMA
  • Analyzed Llama models and leveraged their APIs to develop a working prototype, including setting up a data ingestion pipeline and a vector database

 

Independent Research Project - Digital Healthcare Records, Interoperability and AI Analytics | CIIE

  • Landscaped the HealthTech space to identify key business opportunities in implementation of Digital Healthcare Records, Interoperability, and AI Analytics, needed to drive digital healthcare transformation in India
  • Developed a business model that incentivizes the adoption of digital health records among Indian users and ensures the system's long-term sustainability

 

Advisory Software Engineer | IBM Watson | New York City, NY, USA

  • Spearheaded the development of a high-performance event streaming consumer microservice using Apache Kafka for real-time data ingestion from third-party services. This solution improved data flow and boosted user engagement with the Watson Assistant platform by 10%
  • Spearheaded the development of a web application integrating Watson Assistant with Salesforce and played a key role in developing integrations for other platforms like Slack, Facebook, and Zendesk as well. This initiative played a crucial role in acquiring about 2x new customers
  • Proposed and implemented advanced authentication mechanisms, including OAuth 2.0, for integrating third-party services with Watson Assistant, by drawing on industry best practices from HubSpot, Zoho, and Slack. Also optimized UI/UX design to incorporate these changes
  • Conceptualized and implemented a new routing framework that efficiently directed Watson Assistant users to the appropriate human agents, involving modifications to the UI/UX design to significantly enhance user navigation and support
  • Led the development of a tool that improved intent (or topic) classification accuracy within Watson Assistant by 12% through the incorporation of human-annotated data, significantly improving the mapping of user utterances to relevant topics
  • Engineered and optimized algorithms for extracting system entities (e.g., currency, dates) from user utterances, achieving about 10% boost in System Entity Recognition accuracy
  • Actively contributed to Watson’s open-source community by developing a tool that enabled users to customize their data models for the Speech to Text Service, which increased developer engagement and expanded the service's user base by 2x
  • Engaged directly with clients to identify and resolve pain points, utilizing Agile methodologies and tools like Jira and Asana to track and manage production issues. Authored technical blogs on newly released features to enhance community knowledge
  • Worked with different languages and technologies including Java, Node.js, Typescript, Python, Docker, Apache Kafka, Nginx, Akamai, IBM Cloud, Redis, SQL
     

Software Engineer | IBM Watson | New York, NY, USA

  • Led the development of algorithms for extracting data from various documents, including PDFs, scanned PDFs, images, and MS Word files, by leveraging advanced image processing techniques and data extraction libraries such as OpenCV. This new feature helped in acquiring about 3x new customers
     

Research Assistant | New York University (NYU)| New York City, NY, USA

  • Conducted research under the guidance of Prof. Yao Wang and Prof. Li Feng in medical image processing and deep learning. The goal was to detect long COVID patients using dynamic lung MRIs. Additionally, developed automated histogram analysis using self-supervised learning for organ segmentation, demonstrated through liver T1 mapping in quantitative MRI. These projects were presented at ISMRM Annual Meeting 2024, Singapore and i2i Workshop 2023, CAI2R, NYU Grossman School of Medicine, New York, NY
  • Conducted research under Prof. Grace Lindsay in neuroscience and machine learning, utilizing deep learning models like VGGish to investigate auditory attention, drawing inspiration from previous studies that used vision models such as VGG16 to explore visual attention
     
Accomplishments
  • IIM A PGPX Entry Scholarship holder
  • Member of Winning Team, Hackathon Watson Assistant Fall 2022: Proposed an enhancement to “Extensions” (a feature of Watson Assistant) inspired by the Netflix series Better Call Saul
  • Manager’s Choice Award: Awarded for showing personal interest in various projects during my first year at IBM
  • Membership of Eta Kappa Nu (HKN), Beta Nu Chapter at RPI: Membership is awarded to top 1/4 of juniors and top 1/3 of seniors in ECSE Department at RPI
  • Magna Cum Laude: This special recognition is given for securing a GPA between 3.7 and 3.89
  • Boeing Scholarship: Awarded to female engineering students with outstanding academic record
  • Rensselaer Leadership Award: Awarded in recognition of an outstanding record of academic and personal achievements
  • Dean’s List of Distinguished Students: The Dean's Honor List is compiled at the end of each semester to recognize undergraduate students who have completed 12 or more credit hours at Rensselaer with a 3.5 grade point average or better for that term. Received the honor from Fall 2011 to Fall 2015
  • D. Srinivasan Running Trophy: Awarded for achieving the highest score in Computer Science among my batchmates at Springdales School, Pusa Road, Delhi, in the A.I.S.S.C. Examination 2011 of Std. XII
  • Posters & Publications: 
  1. Luthra, P., Pei, H., Mikheev, A., Rusinek, H., Bruno, M., Sood, T., Wang, Y., Chandrana, H., & Feng, L. Automated Respiratory Pattern Analysis for Dynamic MRI of the Lung with Post  COVID-19 at 0.55 T.  October 2023. [Poster Presentation]. i2i Workshop, CAI2R, NYU Grossman School of Medicine
  2. Luthra, P., Pei, H., Mikheev, A., Rusinek, H., Bruno, M., Sood, T., Wang, Y., Chandrana, H., & Feng, L. Automated Respiratory Pattern Analysis for Dynamic MRI of the Lung with Post COVID-19 at 0.55 T. May 2024. [Digital Poster]. ISMRM 2024
  3. Umapathy, L., Luthra, P., Chen, J., Sodickson, D., & Feng, L. Quantitative MRI with Automated Histogram Analysis Based on Self-Supervised Learning of Organ Segmentation: Demonstration for Liver T1 Mapping. May 2024. [Digital Poster]. ISMRM 2024
Education

MS, Computer Science, Rensselaer Polytechnic Institute (RPI), NY, USA            
BS (Dual Major), Electrical & Computer and Systems Engineering, Rensselaer Polytechnic Institute (RPI), NY, USA
 

Certificates

Machine Learning, New York University
Deep Learning, New York University

Co/Extra-curricular
  • Member of Speaker Series Committee and Women’s Leadership Club
  • Student at New York City Guitar School (NYCGS), New York, NY
  • Learned guitar and participated in open mics
  • Student at New York Academy of Art, New York, NY. Participated in an ‘Intro to Sketching and Oil Painting’ course led by Adam Cross
  • Treasurer of Women’s Mentor Program, RPI, Troy, NY. Responsible for handling/tracking budgets for various events organized by Women’ Member of Aryasamaj Mandir, Delhi, India
  • Continue to participate in havans and actively promote knowledge of Vedic texts and scriptures.      
     

Quick Look

  • Work Experience: 6.9 Years
  • Previous Roles

    Advisory Software Engineer, IBM Watson

    Software Engineer, IBM Watson

    Research Assistant, New York University

  • Function : Engineering & Maintainence
    Product Management/Development
    Research & Development
  • Industry/Sector: Technology
Work Experience

Live Project - Gen-AI powered Knowledge Management System for IIMA | BCG X

  • Developed a Knowledge Management System platform as a part of 3 member team using Large Language Models (LLMs) to assist students and administration at IIMA
  • Analyzed Llama models and leveraged their APIs to develop a working prototype, including setting up a data ingestion pipeline and a vector database

 

Independent Research Project - Digital Healthcare Records, Interoperability and AI Analytics | CIIE

  • Landscaped the HealthTech space to identify key business opportunities in implementation of Digital Healthcare Records, Interoperability, and AI Analytics, needed to drive digital healthcare transformation in India
  • Developed a business model that incentivizes the adoption of digital health records among Indian users and ensures the system's long-term sustainability

 

Advisory Software Engineer | IBM Watson | New York City, NY, USA

  • Spearheaded the development of a high-performance event streaming consumer microservice using Apache Kafka for real-time data ingestion from third-party services. This solution improved data flow and boosted user engagement with the Watson Assistant platform by 10%
  • Spearheaded the development of a web application integrating Watson Assistant with Salesforce and played a key role in developing integrations for other platforms like Slack, Facebook, and Zendesk as well. This initiative played a crucial role in acquiring about 2x new customers
  • Proposed and implemented advanced authentication mechanisms, including OAuth 2.0, for integrating third-party services with Watson Assistant, by drawing on industry best practices from HubSpot, Zoho, and Slack. Also optimized UI/UX design to incorporate these changes
  • Conceptualized and implemented a new routing framework that efficiently directed Watson Assistant users to the appropriate human agents, involving modifications to the UI/UX design to significantly enhance user navigation and support
  • Led the development of a tool that improved intent (or topic) classification accuracy within Watson Assistant by 12% through the incorporation of human-annotated data, significantly improving the mapping of user utterances to relevant topics
  • Engineered and optimized algorithms for extracting system entities (e.g., currency, dates) from user utterances, achieving about 10% boost in System Entity Recognition accuracy
  • Actively contributed to Watson’s open-source community by developing a tool that enabled users to customize their data models for the Speech to Text Service, which increased developer engagement and expanded the service's user base by 2x
  • Engaged directly with clients to identify and resolve pain points, utilizing Agile methodologies and tools like Jira and Asana to track and manage production issues. Authored technical blogs on newly released features to enhance community knowledge
  • Worked with different languages and technologies including Java, Node.js, Typescript, Python, Docker, Apache Kafka, Nginx, Akamai, IBM Cloud, Redis, SQL
     

Software Engineer | IBM Watson | New York, NY, USA

  • Led the development of algorithms for extracting data from various documents, including PDFs, scanned PDFs, images, and MS Word files, by leveraging advanced image processing techniques and data extraction libraries such as OpenCV. This new feature helped in acquiring about 3x new customers
     

Research Assistant | New York University (NYU)| New York City, NY, USA

  • Conducted research under the guidance of Prof. Yao Wang and Prof. Li Feng in medical image processing and deep learning. The goal was to detect long COVID patients using dynamic lung MRIs. Additionally, developed automated histogram analysis using self-supervised learning for organ segmentation, demonstrated through liver T1 mapping in quantitative MRI. These projects were presented at ISMRM Annual Meeting 2024, Singapore and i2i Workshop 2023, CAI2R, NYU Grossman School of Medicine, New York, NY
  • Conducted research under Prof. Grace Lindsay in neuroscience and machine learning, utilizing deep learning models like VGGish to investigate auditory attention, drawing inspiration from previous studies that used vision models such as VGG16 to explore visual attention
     
Accomplishments
  • IIM A PGPX Entry Scholarship holder
  • Member of Winning Team, Hackathon Watson Assistant Fall 2022: Proposed an enhancement to “Extensions” (a feature of Watson Assistant) inspired by the Netflix series Better Call Saul
  • Manager’s Choice Award: Awarded for showing personal interest in various projects during my first year at IBM
  • Membership of Eta Kappa Nu (HKN), Beta Nu Chapter at RPI: Membership is awarded to top 1/4 of juniors and top 1/3 of seniors in ECSE Department at RPI
  • Magna Cum Laude: This special recognition is given for securing a GPA between 3.7 and 3.89
  • Boeing Scholarship: Awarded to female engineering students with outstanding academic record
  • Rensselaer Leadership Award: Awarded in recognition of an outstanding record of academic and personal achievements
  • Dean’s List of Distinguished Students: The Dean's Honor List is compiled at the end of each semester to recognize undergraduate students who have completed 12 or more credit hours at Rensselaer with a 3.5 grade point average or better for that term. Received the honor from Fall 2011 to Fall 2015
  • D. Srinivasan Running Trophy: Awarded for achieving the highest score in Computer Science among my batchmates at Springdales School, Pusa Road, Delhi, in the A.I.S.S.C. Examination 2011 of Std. XII
  • Posters & Publications: 
  1. Luthra, P., Pei, H., Mikheev, A., Rusinek, H., Bruno, M., Sood, T., Wang, Y., Chandrana, H., & Feng, L. Automated Respiratory Pattern Analysis for Dynamic MRI of the Lung with Post  COVID-19 at 0.55 T.  October 2023. [Poster Presentation]. i2i Workshop, CAI2R, NYU Grossman School of Medicine
  2. Luthra, P., Pei, H., Mikheev, A., Rusinek, H., Bruno, M., Sood, T., Wang, Y., Chandrana, H., & Feng, L. Automated Respiratory Pattern Analysis for Dynamic MRI of the Lung with Post COVID-19 at 0.55 T. May 2024. [Digital Poster]. ISMRM 2024
  3. Umapathy, L., Luthra, P., Chen, J., Sodickson, D., & Feng, L. Quantitative MRI with Automated Histogram Analysis Based on Self-Supervised Learning of Organ Segmentation: Demonstration for Liver T1 Mapping. May 2024. [Digital Poster]. ISMRM 2024
Education

MS, Computer Science, Rensselaer Polytechnic Institute (RPI), NY, USA            
BS (Dual Major), Electrical & Computer and Systems Engineering, Rensselaer Polytechnic Institute (RPI), NY, USA
 

Certificates

Machine Learning, New York University
Deep Learning, New York University

Co/Extra-curricular
  • Member of Speaker Series Committee and Women’s Leadership Club
  • Student at New York City Guitar School (NYCGS), New York, NY
  • Learned guitar and participated in open mics
  • Student at New York Academy of Art, New York, NY. Participated in an ‘Intro to Sketching and Oil Painting’ course led by Adam Cross
  • Treasurer of Women’s Mentor Program, RPI, Troy, NY. Responsible for handling/tracking budgets for various events organized by Women’ Member of Aryasamaj Mandir, Delhi, India
  • Continue to participate in havans and actively promote knowledge of Vedic texts and scriptures.