Abu Dhabi Machine Learning Season 5 Episode 1
16.09.2024 - Abu Dhabi Machine Learning - ~4 Minutes
When?
- Monday, September 16, 2024 from 3:00 PM to 5:00 PM (Abu Dhabi Time)
Where?
- ADGM Academy, 20F, Al Maqam Tower, Al Maryah Island, Abu Dhabi
The ADGM Academy page of the event:
The Meetup page of the event:
Abu Dhabi Machine Learning Meetup Season 5 Episode 1
Programme:
Talk 1: Mapping Hong Kong’s Financial Ecosystem: With Networks and LLMs
Abstract: We present the first study of the Public Register of Licensed Persons and Registered Institutions maintained by the Hong Kong Securities and Futures Commission (SFC) through the lens of complex network analysis. This dataset, spanning 21 years with daily granularity, provides a unique view of the evolving social network between licensed professionals and their affiliated firms in Hong Kong’s financial sector. Leveraging large language models, we classify firms (e.g., asset managers, banks) and infer the likely nationality and gender of employees based on their names. This application enhances the dataset by adding rich demographic and organizational context, enabling more precise network analysis. Our preliminary findings reveal key structural features, offering new insights into the dynamics of Hong Kong’s financial landscape. We release the structured dataset to enable further research, establishing a foundation for future studies that may inform recruitment strategies, policy-making, and risk management in the financial industry.
Speaker: Abdulla AlKetbi is a research specialist in finance, with over 10 years of experience. He is currently pursuing a PhD at Khalifa University, focusing on explainable AI in complex networks. Abdulla is also a CFA charterholder and holds a master’s degree in Computational Data Science from Khalifa University. Abdulla also serves as the Chairman of the Operations Board at ADIA Lab.
Talk 2: Unveiling the Black Box: A Guide to Explainable and Interpretable ML
Abstract: As machine learning models become more integral to decision-making processes, understanding their inner workings is crucial. This presentation delves into the concepts of explainable and interpretable ML, providing an overview of how complex “black box” models can be made more transparent. Drawing from model-agnostic techniques we explore approaches to ensure that ML systems are not only powerful but also understandable. We’ll highlight methods like Partial Dependence Plots, Marginal Plots, ALE and SHAP values, all aimed at balancing model performance with clarity. The goal is to equip participants with practical tools and insights for applying interpretable machine learning in real-world contexts without sacrificing predictive accuracy. Based on Christoph Molnar’s comprehensive work on interpretable machine learning, this session provides both a theoretical foundation and practical examples for enhancing ML transparency.
Speaker: Kristof Juhasz is Quantitative Researcher in Abu Dhabi, specializing in signal extraction and predictive modeling for long-short trading strategies in equities. Previously fulfilling similar roles at Goldman Sachs and G-Research in London. With a Mathematics degree from the University of Cambridge, Kristof has expertise in machine learning, data science, and financial modelling.
Talk 3: TelecomGPT: Revolutionizing Telecommunications with Large Language Models
Abstract: TelecomGPT has recently made the headlines (see UAE’s TelecomGPT: The AI Breakthrough Set to Transform Telecoms) as the first general-purpose Large Language Models (LLMs) for specialized applications within the telecommunications domain. The work was jointly performed by Khalifa University’s (KU) 6G Center and Abu Dhabi’s Technology Innovation Institute (TII). Leveraging customized pre-training, instruction tuning, and alignment techniques, TelecomGPT addresses unique challenges in telecom, including domain-specific language understanding, code generation, and real-time network optimization. In this talk, we will delve into the framework’s architecture, key benchmarks, and its potential to enhance network management, reduce operational costs, and drive new AI-driven innovations in telecom. The discussion will highlight TelecomGPT’s role in transforming the telecommunications landscape, offering unprecedented opportunities for industry advancement and efficiency.
Speaker: Mérouane Debbah is a researcher, educator and technology entrepreneur. He has founded several public and industrial research centers, start-ups and held executive positions in ICT companies. He is professor at Khalifa University in Abu Dhabi, United Arab Emirates and founding director of the Khalifa University 6G Research Center.
Learn more about Mérouane Debbah on Wikipedia: https://en.wikipedia.org/wiki/Mérouane_Debbah