Sep 2023 – Nov 2023 · 2 mos · Remote

• CRM team

Jul 2020 – Jul 2023 · 3 yrs · San Diego, California, United States

• Software Content Compliance Engineering team.
• Primary contributor to a new Workflow Orchestration service, that automates open-source scanning and compliance activities. The service worked with multiple internal and external applications to facilitate end-to-end automated compliance scan and annotation pipelines, which helped to reduce incidence of code liability at Qualcomm.
• o Architected workflows using Django and Apache Airflow that would fulfill compliance requirements across several teams at Qualcomm.
• o Simplified the process of requesting ad-hoc compliance checks by developing an API front-end using Django Rest Framework. Users would create JIRA tickets as requests which would be automatically picked up by the Django front end and processed by Apache Airflow.
• o Contributed to the project from the early stage and was responsible for ensuring successful deployment. I also collaborated with the project’s stakeholders across teams, gathered requirements for enhancement and developed solutions for them.
• Provided development and research support to the internal source code scanning system that detects potential open source and licensing markers.
• o Improved scanning system using an open-source toolkit, NexB’s Scancode-Toolkit, that would provide better contextual clues around what was being flagged, making it easier to remedy issues.
• o Added ~50 bots to automate manual decision-making rules that a human would have to execute, significantly reducing processing time by making it 10 times faster to add annotations post scan.
• o Conducted independent analysis and provided metrics to stakeholders to understand further optimization opportunities and enhancement efforts to streamline and improve automation. These optimizations led to a further 55% decrease in manual annotations.

Jun 2019 – Aug 2019 · 2 mos · San Diego, California

• Search Engine Optimization team
• Used Latent Semantic Analysis and NLTK in python to summarize and extract important topics in queries received from partner companies. This data was used to help internal teams identify gaps in product documentation.
• Built a web app using ReactJS and Flask that exposed this data and deployed it to an in-house server to make it easy for internal teams to use.

Jan 2019 – Jul 2020 · 1 yr 6 mos · New York, New York, United States

Jan 2018 – Jun 2018 · 5 mos · Singapore

• Research intern under Dr Chng Eng Siong
• The central goal of the research project was to detect and classify human emotions using ML.
• Physiological signals such as ECG, EMG and EDA were collected and analyzed to find changes/patterns to lead up to emotion detection using Peak Detection Algorithm, Anomaly Detection and LSTM.