[in-person] Abu Dhabi Machine Learning Meetup Season 6 Episode 1

**🚀 Abu Dhabi Machine Learning Meetup – Season Kickoff @ Colnago Caffè** We’re excited to restart the **Abu Dhabi Machine Learning Meetup** with a new season of talks and community gatherings. This time, we’re meeting at the **Colnago Caffè in Al Hudayriat Island**—a spacious and welcoming venue perfect for technical talks, networking, and refreshments. This event brings together researchers, practitioners, and enthusiasts in **machine learning, AI, and data science** from academia, industry, and government-backed research labs. Whether you’re a student, engineer, researcher, or just curious about AI, you’ll find something to learn and someone to connect with. ## 📅 Event Details * **Date:** Thursday, 25 September 2025 * **Time:** 6:00 PM – 9:00 PM * **Location:** Colnago Caffè, Al Hudayriat Island, Abu Dhabi * **Registration:** Free (RSVP required) (max. 50 pax) ## 📌 Agenda * **6:00 – 6:30 PM** → Arrival, check-in & networking * **6:30 – 8:00 PM** → Technical talks (3 speakers) * **8:00 – 9:00 PM** → Q&A, open discussion & informal networking **🎤 Programme** ### Talk 1: *2nd Place Solution for Kaggle Competition: Jane Street Real-Time Market Data Forecasting* **Speaker:** Patrick Yam (Quant Researcher) **Abstract** This talk presents the end-to-end approach behind my 2nd place solution in the Kaggle competition Jane Street Real-Time Market Data Forecasting. The dataset and setting closely reflected the realities of building models for modern financial markets. I will share the full pipeline and highlight interesting findings from developing models under these conditions. **Short Bio** Patrick Yam is a Quantitative Researcher and a Kaggle Competitions Grandmaster. He holds master’s degrees in Data Science and Analytics (Cardiff University, UK) and Transportation Engineering (University of Hong Kong). Patrick specializes in machine learning for financial forecasting, with expertise in time-series modeling, deep learning, and real-time prediction systems. He has earned multiple gold and silver medals in Kaggle competitions. ### Talk 2: *From Lab to Road: Challenges in Autonomous Driving Perception* **Speaker:** Murad Smreteab (Research Engineer, Autonomous Vehicles Lab – Khalifa University) **Abstract** Machine learning has driven significant progress in autonomous driving perception, from object detection and tracking to sensor fusion and prediction. Yet, models that excel on benchmarks often fall short in real-world conditions. This talk explores the research-to-product gap in autonomous driving perception. We’ll cover the perception pipeline (sensors, detection, tracking, fusion) and highlight challenges including domain shift, calibration, simulation-to-reality gaps, and the trade-offs between accuracy and real-time performance. The session is designed to give attendees both a high-level understanding of autonomous perception and practical insights into why the “last 10%” of the problem is often the hardest. **Short Bio** Murad Smreteab is a Research Engineer at Khalifa University’s Autonomous Vehicles Lab (AVLab). He holds a B.Sc. in Computer Engineering (2021) and an M.Sc. in Computer Science (2023), both from Khalifa University. His research focuses on perception and prediction for autonomous driving, with hands-on experience in LiDAR–camera fusion, 3D detection, multi-object tracking, and trajectory prediction. 👉 Additional talks and speakers will be announced soon! ## ℹ️ What to Expect * **Talks:** Technical yet accessible talks on cutting-edge ML/AI topics * **Community:** A chance to meet peers across academia, industry, and government R&D * **Refreshments:** Provided by Colnago Caffè (thanks to our sponsors) * **Bring:** Curiosity, questions, and your business cards (if you’d like to network) ## 🎯 Who Should Join? * ML/AI researchers and engineers * Data scientists and software developers * Students and early-career professionals curious about applied AI * Industry professionals exploring ML applications