The Voleon Group
Jack Wang is an accomplished researcher and educator with a strong background in computer science, specializing in computer animation, robotics, and machine learning. Currently serving as a Senior Member of Research Staff at The Voleon Group since October 2015, Jack previously held positions as an Assistant Professor at the University of Hong Kong, where teaching responsibilities included courses in machine learning and computer graphics, and as a Postdoctoral Researcher at Stanford University. Jack's early career includes internships and roles at prominent companies such as Microsoft Research, Alias Systems, Mitra Imaging, and Research In Motion. Jack earned a PhD and MSc in Computer Science from the University of Toronto and a BMath in Computer Science from the University of Waterloo.
The Voleon Group
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Founded in 2007 by two machine learning scientists, The Voleon Group is a quantitative hedge fund headquartered in Berkeley, CA. We are committed to solving large-scale financial prediction problems with statistical machine learning. The Voleon Group combines an academic research culture with an emphasis on scalable architectures to deliver technology at the forefront of investment management. Many of our employees hold doctorates in statistics, computer science, and mathematics, among other quantitative disciplines. Voleon's CEO holds a Ph.D. in Computer Science from Stanford and previously founded and led a successful technology startup. Our Chief Investment Officer and Head of Research is Statistics faculty at UC Berkeley, where he earned his Ph.D. Voleon prides itself on cultivating an office environment that fosters creativity, collaboration, and open thinking. We are committed to excellence in all aspects of our research and operations, while maintaining a culture of intellectual curiosity and flexibility. The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.