Aman
About the Speaker
Aman Kumar Pandey is a Data Scientist specializing in NLP, Recommender Systems, and Applied AI, with 6+ years of experience across diverse industries.He has developed large-scale recommendation engines, fine-tuned LLMs, and worked on model monitoring, explainable AI, and multilingual NLP solutions.
Currently working at Pratilipi building Recommendation system at scale.
His work spans industry and conservation tech, using AI for wildlife monitoring via computer vision and deep learning. Passionate about open science and AI for social impact, he collaborates with researchers and NGOs to drive real-world innovation.
- Portfolio: https://aman5319.github.io/portfolio/
- Blogs: https://aman5319.github.io/portfolio/tech_blogs/
- LinkedIn: https://www.linkedin.com/in/aman5319/
- GitHub: https://github.com/aman5319
Session
Abstract
Recommendation systems are no longer just about suggesting the next movie, they now shape everything from what we eat and wear to who we date, what we watch, and even what we believe. In this hands-on workshop, we’ll explore the powerful systems behind these “invisible puppeteers” of modern digital life.
You’ll learn not just how recommendation systems work, but how they shape your choices, reinforce (or challenge) your biases, and how companies fine-tune them to maximize retention, revenue, and engagement. We’ll build and break down a recommendation pipeline from retrieval to ranking and dive into production challenges, optimization tricks, and the ethical trade-offs involved.
We’ll also discuss how users can hack these systems to personalize their feeds and how developers can design fairer, more diverse systems. Whether you're into dating apps, content feeds, or building ML pipelines, this workshop will help you understand the full spectrum of RecSys.