About Me
Here is Liao Honglin (Honglin Liao,廖泓霖).
Welcome to my academic homepage! I am a fourth-year undergraduate student pursuing a degree in Robotics and Intelligent Devices at National University of Ireland Maynooth. Currently, I hold the position of Research Assistant in the Financial Technology Laboratory. In this role, I have had the privilege of receiving meticulous guidance from Professor Yong Tang, who leads the Data Mining (DM) group within the National Social Science Foundation.
I am actively preparing for and seeking opportunities to pursue a master's degree, with the aim of further advancing my academic journey. Should you have any interest in or inquiries regarding my academic background, research experience, or future plans, I cordially invite you to contact me via email at onglinguge@gmail.com. I would be profoundly grateful for the opportunity to engage in further dialogue with you, sharing insights into my educational experiences and professional aspirations.
I am actively preparing for and seeking opportunities to pursue a master's degree, with the aim of further advancing my academic journey. Should you have any interest in or inquiries regarding my academic background, research experience, or future plans, I cordially invite you to contact me via email at onglinguge@gmail.com. I would be profoundly grateful for the opportunity to engage in further dialogue with you, sharing insights into my educational experiences and professional aspirations.
Research Interests and Motivation
- Applied Machine Learning
- Risk Management
- Financial Engineering
- Engineering Management
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My research centers on the application of artificial intelligence (AI) to economics，finincial engineering, risk management as well as engineering management. I aim to embed macroeconomic structure and managerial constraints directly into the architectures and training objectives of AI models. By leveraging AI’s strengths in ingesting multi-source, heterogeneous data, detecting latent patterns, and enabling real-time decision making, my goal is to design management systems that are more resilient, efficient, and secure.
This interdisciplinary integration promises both methodological and societal value. Methodologically, aligning economic theory and engineering management principles with modern machine learning can enhance model robustness, interpretability, and generalization in complex system settings. Societally, better system-level performance in areas such as risk monitoring, resource allocation, and operational coordination supports a more efficient, stable, and orderly functioning of markets and institutions. By synthesizing the strengths of these domains, I seek to develop solutions that address multifaceted, real-world challenges, advance management science and technology, and ultimately improve human well-being.
A core motivation of my work is to narrow the gap between theory and practice. I am particularly interested in building adaptive, intelligent systems that: (i) navigate the complexity of global markets, (ii) optimize resource deployment under uncertainty, and (iii) support high-stakes decision making across sectors. To this end, I plan to explore approaches that integrate domain knowledge as inductive biases or soft constraints in model design; quantify and propagate uncertainty for risk-aware decisions; and couple time-series models with unstructured-information pipelines to enrich signal detection. Beyond pushing the frontier of AI applications, I aspire to help shape a rigorous, collaborative paradigm for interdisciplinary research—one that brings economists, engineers, and computer scientists together to deliver measurable impact.
News and Updates
- Sep 2024: (award) Received the Fuzhou University Comprehensive Scholarship of 5000 yuan.
- Aug 2024: (paper) Our paper has been accepted by KDD 2024 (CCF-A). See you in Spain!
- Aug 2024: (certificate) Successfully passed the Financial Risk Manager (FRM) certification Level I issued by the Global Association of Risk Professionals (GARP)!
- Apr 2024: (paper) Our paper LEET accepted by PeerJ Computer Science 2024 (SCI JCR QI, IF=3.5).
- Feb 2024: (award) Received the "H Award" in the MCM competition.
- Nov 2023: (paper) Our paper on Automatic Pricing accepted by IEECT 2023.
- Nov 2023: (activity) Became a research assistant in the Financial Technology Laboratory under the guidance of Prof. Yong Tang.
Lastest Update: 9th Sep 2024