Siddharth Paliwal

Research Assistant at Nanyang Technical University - NIE Singapore (2026-02 – Present)

Conducted affective research to develop Open Emotional Learner Models and engineered privacy-centric deep learning pipelines.

• Conducted affective research to develop "Open Emotional Learner Models" that map facial dynamics to student learning states for improving student learning.
• Engineered a privacy-centric deep learning pipeline using the DAiSEE dataset, extracting facial blendshapes to train accurate models without storing raw video.

Product Analyst at Powerup Money (2025-09 – 2025-12)

Formulated and tested data-driven hypotheses on user behavior and product engagement.

• Formulated and tested data-driven hypotheses on user behavior, evaluating how product changes influenced user engagement and progression through key interaction stages.

Product Analyst at PocketFM (2025-09 – Present)

Developed pLTV models, conducted behavioral analysis of high-value users, and managed production-scale data pipelines.

• Developed and deployed a pLTV model to forecast Day-30 user revenue, and built the end-to-end data pipeline supporting the prediction workflow.
• Conducted in-depth behavioral analysis of high-value ("Whale") users to uncover early predictive signals, modeling temporal user interaction patterns and translating them into features for monetization and retention prediction tasks.
• Managed and maintained production-scale user data pipelines and fact tables, ensuring data quality and consistency to support accurate, data-driven decisions by business stakeholders.

Analyst Intern at PocketFM (2024-01 – 2024-06)

Contributed to data infrastructure migration from Amazon Redshift to Databricks.

• Contributed to the migration of data infrastructure from Amazon Redshift to Databricks, improving processing efficiency, scalability, and reliability of analytics workflows.

Research and Algorithm Developer at Happy Reliable Surgeries (2023-06 – 2023-07)

Registered MRI scans and experimented with AI-based medical image segmentation methods.

• Registered MRI scans of the spine and brain with 3D camera data using the Iterative Closest Point (ICP) algorithm, improving spatial alignment for medical imaging analysis.
• Utilized segmentation tools such as 3D Slicer and ImFusion to preprocess MRI images and experimented with AI-based methods for automating medical image segmentation.

M.Sc. in Artificial Intelligence – Nanyang Technological University (2026)

B.E. in Electrical and Electronics Engineering – Birla Institute of Technology and Science Pilani (2020 – 2024)

Minor in Data Science – Birla Institute of Technology and Science Pilani (2020 – 2024)