CS663

Dr. Lynne L. Grewe
lynne.grewe@csueastbay.edu

phone: 510-885-4167, Room SF 551

Dr. Grewe has her PhD from the Electrical and Computer Engineering Department of Purdue University. She has a number of years industrial experience and academic experience. Her research interests include Computer Vision, Media Processing and AI. She has recently served while on sabbatical at Google as a Faculty in Residence.

Tell about your foray into tech world?

I began my career as an Undergraduate student as an intern at Intel Corporation. It was exciting to come to Silicon Valley, the heart of much tech invention and becoming part of a major leading tech company. I learned a lot including what I didnt like to do. I strongly encourage students to look for any opportunity to work/participate in the tech industry before they graduate.
I subsequently worked at HP and Hughes Research Labs. I learned working at a research lab how much I liked the independence and autonomy of doing research
I worked full time at IBM corporation who also sponsored me for my PhD. I was a Vision specialist and worked with research and an International team on unique vision based systems. I enjoyed working on an international team but, working across time zones is a challenge.
I most recently while on sabbatical served at Google as a Faculty in Residence

What is the most exciting thing about Computer Vision today?

What isnt exciting. Computer Vision is what is leading the explosuion of what I call the "Uber Automation Revolution". Think about self-driving cars and assistive drones. The main technology involved is computer vision - understanding (or people today call it Machine Learning). Yes ofcourse Machine Learning can be applied to many concepts. A lot of the progress is about having a lot of data and having the capabilities (machines/cloud) to process them.

What advice do you give to students interested in computer vision?

Did you know that having a background in computer vision and ML can lead to jobs in everything from advertising recommendations to stock predicitons. Why? Because the basics of doing image understanding is challenging and complex and "mastering" this means you can apply understanding techniques to other (potentially simpler) kinds of data.
Enjoy it! I found my way into computer vision as a graduate student partially because I was bored with the mundane (my opinion) of chip design and hardware and partly because I was a photographer (for University) and partly because the creativity that can be expressed in this field attracted me.
Really work. Computer Science in general and I believe computer vision specifically is a field that requires practice and experience....this means working and failing. Failing is not failing --- you have learned something --it may be what not to do, or it may lead you to another way of doing it, it could lead you to use the failed idea in another way / application that is successful.

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