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Vishal Ahuja
Machine Learning Engineer at JPMC
About
Vishal Ahuja is a highly skilled Deep Learning Engineer with over a decade of experience in the tech industry. Currently, he is working at Okkular.io, where he is responsible for developing and implementing deep learning algorithms to improve the platform's functionality. Prior to his current role, Vishal worked as a Senior Developer at Koinearth and as a Principal Data Engineer at Target. During his tenure at these companies, he gained extensive experience in developing and deploying large-scale data-driven solutions. Vishal's education background is impressive, having earned a Doctor of Philosophy (PhD) in Computer Science from the University of California, Davis, and a Bachelor of Science (BSc) in Computer Science from the University of Auckland. His PhD research focused on developing efficient algorithms for data mining, which laid the foundation for his expertise in data engineering and deep learning. In addition to his educational background and work experience, Vishal is proficient in various technologies, including deep learning, web3, blockchain, and data engineering. His expertise in these areas has helped him stay ahead of the curve in the rapidly evolving tech industry. Overall, Vishal Ahuja is a highly accomplished Deep Learning Engineer with a proven track record of delivering innovative solutions. His expertise in data engineering and deep learning, combined with his educational background and proficiency in various technologies, make him a valuable asset to any organization.
Education
• university of california davis
Companies
• jp morgan
• okkular.io
• koinearth
• target
• kvantum
• uc davis
Experience
11.8 Years
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Experience
Skills
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Algorithms
Blockchain
C
C++
Computer Science
Golang
Linux
Machine Learning (ML)
OpenCL
OpenMP
Programming
Pthreads
Python (Programming Language)
Research
Software Engineering
ZeroMQ
Contact Details
Email (Verified)
vahXXXXXXXXXXXXomMobile Number
+91XXXXXXXXXXEducation
university of california davis
Doctor of Philosophy - PhD
2008 - 2013
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