AlephedgeEN / 中Our technology team combines mathematics, AI science, and systems engineering to build trusted, usable, and verifiable intelligent products.
The technology team is composed of mathematicians, AI scientists, and software engineers. Its members come from the Department of Mathematics at University College London, include doctoral research backgrounds, and bring hedge fund industry experience. The team spans algorithm research, model systems, data engineering, product engineering, and reliability, focused on turning complex technologies into stable, scalable, and deployable intelligent infrastructure capabilities.
Lead Mathematician
BSc, UCL; PhD student in Mathematics at Stanford, specializing in Number Theory. Combines mathematical research with experience in systems software and OS kernel development to build reliable and efficient quantitative algorithms and software systems.
Head of Quantitative Strategy
BSc graduate of the UCL Department of Mathematics with an MSc in Statistics from Columbia University. Former hedge fund quantitative researcher with extensive hands-on strategy experience in China A-share and commodity markets.
Algorithm Engineer / LLM Researcher
Core developer with a BSc from the UCL Department of Mathematics, currently pursuing graduate study in Computer Science at Waseda University and serving as a research assistant at Tsinghua University's Center for Brain-Inspired Computing Research. His research focuses on trustworthy AI and world models, covering generative models, multi-agent systems, and optimization theory. He previously worked as an LLM algorithm engineer.
Software Engineer / LLM Researcher
Core developer with BSc and MSc degrees from the UCL Department of Computer Science, focused on AI for Code and trusted intelligent systems.
Macro Analyst
Macro market analyst with a BSc from the UCL Department of Mathematics. Has years of market research experience and multi-year live trading experience across China A-shares, Hong Kong equities, and US equities.
Head of Market Department
BSc in Mathematics and Economics from UCL; currently pursuing a computer science-focused master's degree at the University of Warwick, with research interests spanning artificial intelligence and cybersecurity. Has experience in investment banking and private equity, with investment research experience across U.S. equities and derivatives markets.
Head of Risk Control
Graduated from the UCL Department of Mathematics and is pursuing a master’s degree in Financial Risk Management. His research focuses on reliability evaluation of large language models in financial risk, covering model accuracy, stability, and hallucination analysis. He has a background in mathematical modelling and quantitative analysis, with interests in applying AI to risk management and financial decision-making.
Quantitative Researcher
MSc student in Applied Computational Science at Imperial College London, where my work centres on machine learning and numerical methods for scientific computing. I earned my BSc in Mathematics at University College London (UCL), building a strong foundation in analysis, applied mathematics, and computation. I’m currently working on a joint research project with SLB (Schlumberger) and Imperial College London, bringing microscaling (MX) compression from machine learning into seismic wave simulation for subsurface exploration imaging — storing large wavefields in block-wise low precision and studying how stochastic rounding controls error over long simulations, to cut memory and bandwidth cost in reverse-time migration and full-waveform inversion. My interests span scientific machine learning, high-performance numerical methods, and inverse problems. You can reach me at shijun.huang.22@ucl.ac.uk.
