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Vivian Chu

Vivian Chu is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Vivian Chu rather than just read about it. In short: Vivian Chu (born c. 1987) is an American roboticist and entrepreneur, specializing in the field of human-robot interaction. She is Chief Technology Officer at Diligent Robotics, a company she co-founded in 2017 for creating autonomous, mobile, socially intelligent robots.

Key takeaways

  • Vivian Chu belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Vivian Chu to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Vivian Chu from memory before moving on to harder problems.

Reference excerpt

Vivian Chu (born c. 1987) is an American roboticist and entrepreneur, specializing in the field of human-robot interaction. She is Chief Technology Officer at Diligent Robotics, a company she co-founded in 2017 for creating autonomous, mobile, socially intelligent robots.

Early life and education Chu was born in San Jose, California. Growing up, she lived with her parents, who were both software engineers, and her grandparents. She received her bachelor's degree in electrical engineering and computer science from the University of California, Berkeley in 2009. During her time at Berkeley, she worked as a research assistant in the lab of Dennis K. Lieu, where she worked on integrated flywheels in triple hybrid drive trains. Upon graduation, she worked for IBM Almaden Research, an innovation lab for disruptive technology, where her research centered on natural language processing and intelligent information integration. In 2011, Chu left IBM Almaden to pursue a master's degree at the University of Pennsylvania. At Penn, she worked under the mentorship of Katherine Kuchenbecker in the Haptics Research Group as a part of the GRASP Lab. She focused on haptic technology to enable robots to both interact with their environment and understand the abstract terms that humans would use to describe the feeling of that interaction. For example, a human may say a carpet is fuzzy, but Chu's algorithms would enable a robot to sense the rug, perform a computation, and also associate that “feeling” with the adjective or descriptor of fuzzy. Chu and her colleagues were able to train PR2 robots equipped with haptic sensors to touch objects and relate the information from the sensor with the human-provided adjective for the haptic quality of the object. The robot was able to learn these associations and then later generalize its learning to objects it had not yet touched and provide an adjective descriptor similar to one a human might use. This work were reported in Chu's first author paper in 2013, which was awarded Best Paper in Cognitive Robotics at the IEEE International Conference on Robotics. After completing her Master's in 2013, Chu had a summer internship at Honda Research Institute and continued graduate training at Georgia Tech. She worked towards a PhD in Robotics under the mentorship of Andrea L. Thomaz in the Socially Intelligent Machines Lab and under the mentorship of Sonia Chernova in the Robot Autonomy and Interactive Learning Lab. Her work focused on building algorithms that enable robots to reason about action effects and interact with their environments in an adaptable way. Chu was inspired by a talk in developmental psychology discussing how children learn to interact with their environments. She figured that she could approach robot learning in this way as well, giving robots the basic building blocks of cognition so that they could play with objects in the environment and learn the appropriate ways to interact with them. Chu based her design on applying human-guided robot self-exploration to learn affordances. She built algorithms that enabled robots with both self guided and supervised learning of the affordances of objects in the environment, and showed that the combination of both self and supervised learning allows for the best robot performance. Chu and Thomaz filed a patent in 2017 for this technology, which is also when she completed her PhD.

Career and research In 2015, Chu spent a summer as an intern at Google[x] under the mentorship of Leila Takayama. She then began working alongside Andrea Thomaz to create a company to build socially intelligent robots that can assist people with chores at work and home. In 2017, they co-founded Diligent Robotics. After graduating from her PhD in 2018, she became the full-time Chief Technology Officer at the firm. She leads a diverse team of roboticists who build robots that feature autonomous mobile manipulation, social intelligence, and human-guided learning abilities, inspired by Chu's graduate discoveries.

Diligent Robotics Diligent Robotics' first clinical assistant was Poli, a one-arm robot that was able to pre-fetch supply kits to allow nursing staff to spend more time with patients. Poli was piloted at Seton Medical Center at the University of Texas in Austin. The firm's second healthcare support robot, Moxi, is a refurbished and updated version of Poli. It possesses more human-like features including a face that can visually communicate social cues and a head and torso. In 2020, Diligent Robotics raised a $10 million Series A. In 2022, the company raised more than $30 million for their Series B, led by Tiger Global, for a total of nearly $50 million since founding. It has won accolades including being named as Time's 100 Best Inventions (2019), World Economic Forum Technology Pioneer (2021), and Newsweek America's Greatest Disruptors (2021).

Awards and honors 2013 Best paper in cognitive robotics IEEE International Conference on Robotics 2014 Google Anita Borg Memorial Scholarship 2016 Paper on Human-Guided Robot Self-Exploration nominated for Best Technical Advance in Human-Robot Interaction 2019 MIT Technology Review 35 Innovators Under 35 2021 Fast Company Queer 50 2022 Fast Company Queer 50 2022 Fortune Magazine 40 under 40

Depiction in media 2020: The Future of Science is Female by Zara Stone

Appearances In November 2020, Chu keynoted at ROS World on "Accelerating Innovation with ROS: Lessons in Healthcare" In October 2022, Chu keynoted at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) in Kyoto on “Launching Socially-Aware Mobile Manipulation Robots in Hospitals.” In July 2023, Chu presented at Fortune Brainstorm Tech in Utah on "Robotic Revolution."

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Vivian Chu

Start with the simplest possible case. Write down what Vivian Chu claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Vivian Chu before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Vivian Chu ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Vivian Chu

In research
Vivian Chu appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Vivian Chu in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Vivian Chu is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1987 births, 21st-century American scientists, 21st-century American women scientists, so understanding it makes those chapters shorter.
In everyday life
Look for Vivian Chu outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Vivian Chu in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Vivian Chu means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Vivian Chu out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Vivian Chu in simple terms?

Vivian Chu (born c. 1987) is an American roboticist and entrepreneur, specializing in the field of human-robot interaction. She is Chief Technology Officer at Diligent Robotics, a company she co-founded in 2017 for creating autonomous, mobile, socially intelligent robots.

Why does Vivian Chu matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Vivian Chu?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Vivian Chu.

Tags

  • 1987 births
  • 21st-century American scientists
  • 21st-century American women scientists
  • American chief technology officers
  • American company founders
  • American roboticists
  • American women company founders
  • American women computer scientists
  • Georgia Tech alumni
  • IBM employees
  • Living people
  • People from San Jose, California

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