🚀 StudyJam #DevFlow 2.0: Complete AI Research Cycle - Benchmarking FER Models & Writing IEEE-Style Paper

Ready to take your AI skills from the lab to the library? In this comprehensive session, we will explore the complete lifecycle of an AI research project, bridging the gap between technical experimentation and academic excellence. You will learn how to conduct a rigorous performance benchmark of three distinct Face Emotion Recognition (FER) approaches: models built from scratch, pretrained architectures, and cutting-edge Vision Language Models (VLM).

Beyond the code, we will demonstrate how to implement these models into a functional web application and, most importantly, how to document your findings. You will gain a clear roadmap for structuring your experimental results into a professional, IEEE-style scientific paper that is ready for publication. Whether you are aiming for a career in research or want to build more robust AI projects, this session provides the end-to-end guidance you need.

📅 Date: Wednesday, 16 February 2026

⏰ Time: 20:00 – 21:30 WIB

🌐 Online via Google Meet: meet.google.com/eqd-qzrp-qnj

🎤 Speaker: Fadhlan Nur Rachman - ex Indonesia AI Intern as Junior Web Developer

💡 What you’ll gain: 

• Master benchmarking techniques for Scratch, Pretrained, and VLM models

• Understand the fundamentals of Face Emotion Recognition (FER)

• Learn how to integrate AI models into simple web applications

• Gain insights into writing and structuring IEEE-standard scientific papers

👥 Who should join?

• Students interested in AI research and academic publication

• Developers curious about Face Emotion Recognition technology

• Aspiring researchers wanting to master the full project lifecycle

🎫 Seats are limited — secure your spot early!

#TechLearning #GDG #GDGoCBinusBandung #CampusTech #AIResearch #IEEE #FaceEmotionRecognition