Our research and innovation teams are multi-disciplinary, and our researchers actively collaborate with numerous universities around the globe.
Jean Bolot, VP of Research & Innovation
He leads the Technicolor Artificial Intelligence Lab (AI Lab) in Silicon Valley focusing on AI technologies for entertainment. Before Technicolor he led the research lab of Sprint, pioneering large scale cell phone data mining. Prior to that he was a founding team member of Ensim, a Silicon Valley startup (acquired by Ingram Micro), a visiting professor in Computer Science at UC Berkeley and a researcher at Inria. He holds a MS and PhD degree in Computer Science from the University of Maryland at College Park.
Jaideep Chandrashekar, Principal Scientist
His research interests are broadly in computer networks and systems. Research projects are around the areas of network monitoring and troubleshooting and online privacy. He has worked on problems related to network measurements and analysis (both home and cellular networks) applying methods from data science towards troubleshooting home networks. Led a project exploring how to reduce NSP operational costs by continuous monitoring feeding into a data analytics backend. The initial research idea (use spare cycles on gateways to push monitoring state) went into trial in a large European ISP and has subsequently found traction inside a business group.Prior to Technicolor, he was an Intel Labs researcher.
Naveen Goela, Researcher
He is the lead researcher on the topic of DNA storage, working in collaboration with biologists at Harvard University. He received undergraduate degrees in computer science and mathematics, and a M. Eng. degree in computer science from the Massachusetts Institute of Technology (MIT). His research at MIT focused on multi-camera visual hull reconstruction, and motion graphs. He received his Ph.D. in electrical engineering and computer science from UC, Berkeley.
Shahab Hamidi-Rad, Software Architect
His areas of work and interest include big data analytics, machine learning, and deep learning as well as software backend design and implementation. Before Technicolor, he worked at Harmonic developing a statistical multiplexing system for video broadcast transport streams. At Animatics Corporation he worked on smart stepper/servo motors in real-time designing a G-Code based Servo Motion Control System.
Yingbo Hu, Engineer
He is exploring research interests in Machine Learning/Deep Learning and their applications with real world data. Before joining the AI Lab, he had been a chip designer at Intel and other companies. He holds a MS degree in ECE from University of Minnesota-Twin Cities and a MS degree in EE from Tsinghua University.
Swayambhoo Jain, Researcher
His current research is in machine learning, signal processing and communications. His focus is on deep learning and deep neural networks – how to set up, train and run deep networks on resource-constrained devices such as TVs, set-top boxes or media sticks or even directly on home devices such as security cameras or smart speakers. He developed an analytics platform using machine learning to accelerate the creation of complex visual and special effects for Hollywood blockbusters and reducing the production costs. He completed his PhD in Electrical Engineering, University of Minnesota – Twin Cities.
Ajith Pudhiyaveetil, Engineer
After starting off as an intern at Technicolor in 2010, he then joined as an Engineer in 2013. His focus is on building data collection applications for the Android OTT set top boxes that Technicolor sells to various customers around the globe. The collected data can provide useful insights for the customers to understand their users. One exploratory projects was prototyping a robotic repeater for gateways to handle common WIFI problems faced by users at their home which was successfully demo’ed to positive feedback. He completed his master’s degree in Computer and Information Sciences at the University of Arkansas.
Akshay Pushparaja, Engineer
He works with the MPC team to build their analytics and prediction pipeline. He is actively researching applications of Reinforcement Learning in the media domain. He received his master’s degree from Carnegie Mellon University, Pittsburgh. Before moving to United States, he worked in the Investment Banking domain and co-founded a startup while in India. He actively participates in Silicon Valley hackathons. He has won hackathons organized by Twitter and AT&T and has also presented at the Techcrunch Disrupt hackathon. His current area of interest is application of machine learning in real world applications.