Our team of top minds range in qualifications from PHD and masters in engineering to neuroscience and physics.

Shamik Raja

Whitebeard is the brainchild of Shamik Raja, a developer and computer engineer with expertise in digital signal processing, programming, commodities, and quantitative science. He holds a degree in Electrical & Computer Engineering from the University of British Columbia, Canada. His career is defined by pioneering digital signal processing applications in financial markets, developing advanced trading systems that integrate AI, advanced mathematics, and data science. At Whitebeard, Raja combines eight years in blockchain with over two decades of experience in quantitative finance and engineering, driving innovation at the intersection of technology and decentralized finance.

Yadav Jani

Yadav, an entrepreneurial force with a Master's in Finance and Marketing, has been shaping the financial sector since 2006 as a financial advisor. His insights and strategic guidance in wealth management have earned him a reputation for excellence in financial circles. In 2013, his innovative spirit led him to establish a prime property company in Central London, quickly making waves and earning industry accolades for record-setting achievements. This venture solidified his status as a real estate virtuoso. Expanding his horizon further, in 2018, Yadav delved into the blockchain and cryptocurrency space, where he has already made significant impacts across over 15 international projects. Yadav's career is a testament to his ability to navigate and excel in diverse financial landscapes.

Sina Tootoonian

Sina Tootoonian started as an electrical engineer with a degree from University of British Columbia. Sina later pivoted his focus into computational neuroscience studying sensory systems in the brain using techniques from applied mathematics, statistics and machine learning to analyze neural data and develop theories for how brains organize the flood of noisy sensory inputs into rich representations of the external world. Earlier, Sina was a research associate for both UCL and Cambridge University where he gained experience in analyzing simple models of artificial neural networks to better understand their performance in an analytically tractable setting. Sina has a PHD in neuroscience and vast experience.