Founder and Chief Executive Officer, Aigen Investment Management, LP
Juhua Zhu is the founder and Chief Executive Officer of Aigen Investment Management, LP, a New York-based investment management firm specializing in diversified systematic investment strategies. Founded in 2018, Aigen applies a rigorous, data-driven investment process that combines quantitative modeling, machine learning, large-scale data analysis, and high-performance computing to develop and implement systematic strategies across global equity markets.
Juhua has spent her career at the intersection of technology, quantitative research, and financial markets. Before founding Aigen, she spent more than twelve years at Morgan Stanley, where she was a Managing Director in the Institutional Equity Division in New York. Her work focused on the research and development of systematic and multi-factor statistical arbitrage strategies across global equity markets, including North America, Europe, and Asia. Over the course of her career at Morgan Stanley, she developed extensive expertise in quantitative alpha generation, portfolio construction and optimization, market impact modeling, data analytics, and performance attribution.
At Aigen, Juhua oversees the firm’s investment process and technology platform, spanning quantitative research, data processing, portfolio construction, risk management, and trading execution. Her work explores how advances in machine learning and computing can expand the scale and sophistication of systematic investment research while maintaining rigorous standards for statistical validity, risk control, and generalization. She is particularly interested in the practical challenges of applying artificial intelligence to financial markets, where signal-to-noise ratios are extremely low, market behavior is adaptive, and models must continually evolve.
Juhua’s path into quantitative finance began in engineering and computer science. She received a Ph.D. in Electrical Engineering from Princeton University in 2005, with a minor in Operations Research and Financial Engineering. Her doctoral research focused on pattern recognition, computer vision, and multimedia processing, including algorithms for object detection, tracking, image analysis, and video understanding. Her doctoral work resulted in publications at conferences including CVPR and ICASSP, as well as a U.S. patent for a transform-domain method for foreground segmentation in video sequences.
Prior to Princeton, Juhua received both a master’s and bachelor’s degree in Electrical Engineering from Shanghai Jiao Tong University, along with a bachelor’s degree in International Trade. Her undergraduate and graduate education gave her an interdisciplinary foundation spanning engineering, computer science, quantitative analysis, and economics.
Juhua’s transition from machine learning research to quantitative finance reflects a broader evolution in the application of computational methods to financial markets. Her experience spans both the development of machine-learning and computer-vision algorithms and their application to real-world, highly competitive financial systems. During her years at Morgan Stanley, she became one of the practitioners working at the forefront of the growing use of quantitative and computational methods in equity trading. Her work and perspectives on the transformation of Wall Street and the increasing role of technically trained researchers have also been featured publicly, including in IEEE Spectrum.
Beyond her professional work, Juhua is actively involved in initiatives supporting Asian American leadership and the next generation of professionals in technology and finance. She is a founding member of the Asian American Leadership in Financial Services Alliance, an organization dedicated to elevating Asian American leaders in financial services and investing in the next generation of financial professionals. She has also contributed to the Asian American Scholar Forum’s initiatives at the intersection of technology, finance, and the Asian American community, including serving on the program committee for the 2026 AIX Summit and moderating a session on AI and investing in finance.
Juhua’s career reflects a continuing interest in translating advances in science and engineering into practical systems. From early work in computer vision and pattern recognition, through quantitative research at a major global financial institution, to building an independent investment firm around systematic strategies and machine learning, her work has remained centered on using data, mathematics, and computation to solve complex real-world problems.
