Gen Li, M.Sc.

Doctoral Researcher

E-Mail: gen.li@tum.de
Office: 2539 (Building 5, 2nd floor)

 

About Me

I am a Doctoral Researcher affiliated with both the Technical University of Munich's Center for Energy Markets (CEM) and the Institute for Ethics in Artificial Intelligence (IEAI). My work is driven by a passion for applying mathematical and computational techniques to tackle real-world challenges in the extractive industries and energy markets. With a robust background in Mathematics and Operations Research, my current research focuses on exploring the potential of Artificial Intelligence (AI) in promoting multi-objective optimization within the complex ecosystem of the extractive (mining) industries, ensuring that technological advancements are aligned with ethical standards and societal well-being.

Outside my academic and research interests, I'm passionate about cycling, hiking, and badminton for staying active, and enjoy playing guitar for creative expression. My reading tastes are eclectic, with a preference for the imaginative worlds of Cixin Liu, and the profound narratives of Hermann Hesse and Haruki Murakami.

Research Interests

My primary research interest lies in Operations Research and the application of mathematical modeling, optimization, machine learning, and statistics to solve real-world problems.

I am particularly fascinated by Resource and Energy Economics, especially regarding the energy transition, extractive mining and EV charging industries. My Ph.D. research is dedicated to exploring AI's potential in the extractive industries to achieve multi-objective optimization, acknowledging the sector's inherent complexities involving various stakeholders with often conflicting objectives.

Current Work

The essence of my doctoral research revolves around the premise that the mining industry, characterized by its substantial capital expenditure and significant societal and environmental impacts, requires a sophisticated and multi-faceted approach to policy-making and operational efficiency. This industry's complexity is further amplified by the multitude of stakeholders, including mining companies, governments, and local communities, each with their distinct objectives and expectations.

In addition to my focus on the extractive industry, I am also fascinated by the rapidly evolving sector of e-mobility, particularly in the realm of infrastructure network optimization and pricing for electric vehicle charging to boost operational efficiency and profit margins. My interest in this area was sparked by my collaborative master's thesis with the Siemens Infrastructure Design research group. In this project, I applied stochastic optimization to strategic allocation of charging stations, taking into account the uncertainty of the electrical grid network.

Furthermore, the prospect of applying machine learning and large language models across diverse sectors deeply fascinates me. I am exploring the potentials of utilizing these cutting-edge technologies to model decision-making processes and consumer patterns, in order to improve strategic initiatives and operational effectiveness.

Education

Since 04/23

Doctoral Researcher at Center for Energy Markets, Technical University of Munich, Germany

10/19 – 02/23

M.Sc. in Mathematics in Operations Research, Technical University of Munich, Germany

09/14 – 06/18

B.Sc. in Mathematics, Jilin University, China

 

Publication

On the way! This guy is not that fast, let's give him some patience.