UCL Mathematics and Statistical Sciences (IMSS) - In Conversation with UCL Alumnus Patrick Bangert

It’s never too early to start thinking about your future career and how you can prepare for it. Join UCL IMSS for an exclusive online conversation with UCL alumnus and Vice-President of Artificial Intelligence at Samsung, Patrick Bangert. An expert in artificial intelligence and machine learning, Patrick will share valuable first-hand experiences of his research with Samsung, insights and advice to help you find your way in the wider sector, and information on available internships.

For anyone interested in #energy, #datascience, #machinelearning, and #artificialintelligence, this is a unique opportunity to hear from one of our most engaging alumni speakers and discover internships available to you.

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Patrick Bangert - Vice President of Artificial Intelligence at Samsung SDS America

UCL MSci Physics 1999 | UCL MPhil Mathematics 2002

Dr. Patrick Bangert is the Vice President of Artificial Intelligence at Samsung SDS where he leads both the AI engineering software development and AI consulting groups, developing automated machine learning and providing expert consulting services. The teams supply the full spectrum of AI model development backed by state-of-the-art technology and human expertise.

 With a background in the process industry (chemical, power, oil and gas), Patrick has an eye on practical applications that deliver value in the real world. He is the founder and Board Chair of Algorithmica Technologies, providing real-time process modelling, optimisation, and predictive maintenance solutions to the process industry with a focus on chemistry and power generation. His doctorate from UCL specialised in applied mathematics and he holds academic positions at NASA’s Jet Propulsion Laboratory and Los Alamos National Laboratory. From optimising power plant efficiency, to enabling predictive maintenance in upstream and downstream plants, he has worked on practical AI projects on four continents and has published extensively across optimisation and machine learning.

 Location:             Online via Microsoft teams