People to Watch 2016

Hartmut Neven
Director of Engineering
Google

Hartmut Neven is a scientist working in quantum computing, computer vision, robotics and computational neuroscience. He is best known for his work in face and object recognition and his contributions to quantum machine learning. He is currently Director of Engineering at Google where he is leading the Quantum Artificial Intelligence Laboratory.

Hartmut Neven studied Physics and Economics in Köln, Paris, Tübingen, Aachen, Jerusalem and Brazil. He wrote his Master thesis on a neuronal model of object recognition at the Max Planck Institute for Biological Cybernetics under Valentino Braitenberg. In 1996 he received his Ph.D. from the Institute for Neuroinformatics at the Ruhr University in Bochum, Germany, for a thesis on “Dynamics for vision-guided autonomous mobile robots” written under the tutelage of Christoph von der Malsburg.

HPCwire: Hi Hartmut. Congratulations on being named an HPCwire Person to Watch in 2016! Quantum computing represents what could be the next leap forward in computing technology, but many still see its promise as being too far off to merit much attention. What milestones do you hope to meet in 2016 that should bring quantum computing into the limelight?

Hartmut Neven: In the next years we hope to fabricate processors with about 100 highly coherent qubits. With such devices we hope to demonstrate what is known as “quantum supremacy”. This means to perform a computation that no classical computing system will ever be able to complete.

HPCwire: One key distinction about the D-Wave system that Google and NASA are operating in your lab is that it’s not designed for all computing tasks. What are some exciting applications we could potentially see fleshed out in the coming year?

The D-Wave processors are quantum annealers. Quantum annealing is well suited to perform optimization and sampling tasks. Those in turn have applications in many fields. We are particularly interested in applications to machine intelligence. For example, we developed machine learning algorithms capable of learning from very noisy data sets. This can help to overcome a bottleneck in today’s machine learning systems which have a need for clean training data sets.

HPCwire: What trends in high performance computing do you see as particularly relevant as you look forward to the year ahead?

Besides watching new milestones in quantum computing being accomplished I am curious to follow the efforts in designing neuromorphic computing architectures.

HPCwire: Outside of the professional sphere, what can you tell us about yourself – personal life, family, background, hobbies, etc.?

I have a wife who is from Korea. We have two boys and are living in Malibu in Southern California. We love to travel. In particular I find it fascinating to visit and study the culture of indigenous tribes in the Amazon rainforest.

I am in the fortunate position that my passions and my work coincide. I love fundamental physics, quantum computing, artificial intelligence and neurobiology. I am also fascinated by the phenomenon of consciousness but I am not very optimistic that it is accessible to study with the methods of experimental science.

HPCwire: Final question: What can you share about yourself that you think your colleagues would be surprised to learn?

rather keep such surprises for folks who are getting to know me better.

 

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