astronomy

Manuela M. Veloso

Manuela M. Veloso is a astronomy 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 Manuela M. Veloso rather than just read about it. In short: Manuela Maria Veloso (born August 12, 1957) is the Head of J.P. Morgan AI Research & Herbert A.

Key takeaways

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

Reference excerpt

Manuela Maria Veloso (born August 12, 1957) is the Head of J.P. Morgan AI Research & Herbert A. Simon University Professor Emeritus in the School of Computer Science at Carnegie Mellon University, where she was previously Head of the Machine Learning Department. She served as president of Association for the Advancement of Artificial Intelligence (AAAI) until 2014, and the co-founder and a Past President of the RoboCup Federation. She is a fellow of AAAI, Institute of Electrical and Electronics Engineers (IEEE), American Association for the Advancement of Science (AAAS), and Association for Computing Machinery (ACM). She is an international expert in artificial intelligence and robotics.

Education Manuela Veloso received her Licenciatura and Master of Science degree in electrical engineering from Lisbon's Instituto Superior Técnico in 1980 and 1984 respectively. She then attended Boston University, and received a Master of Arts in computer science in 1986. She moved to Carnegie Mellon University and received her Ph.D. in computer science there in 1992. Her thesis Learning by Analogical Reasoning in General Purpose Problem Solving was supervised by Jaime Carbonell.

Career and research

Shortly after receiving her Ph.D., Manuela Veloso joined the faculty of the Carnegie Mellon School of Computer Science as an assistant professor. She was promoted to the rank of associate professor in 1997, and full professor in 2002. Veloso was a visiting professor at the Massachusetts Institute of Technology for the academic year 1999–2000, a Radcliffe Fellow of the Radcliffe Institute for Advanced Study, Harvard University for the academic year 2006–2007, and a visiting professor at Center for Urban Science and Progress (CUSP) at New York University (NYU) for the academic year 2013–2014. She is the winner of the 2009 ACM/SIGART Autonomous Agents Research Award. She was the Program Chair for IJCAI-07, held January 6–12, 2007, in Hyderabad, India and was program co-chair of AAAI-05, held July 9–13, 2005, in Pittsburgh. She was a member of the editorial board of CACM and the AAAI Magazine. She is the author of one book on Planning by Analogical Reasoning. As of 2015, Veloso has graduated 32 PhD students. She was appointed as the head of Carnegie Mellon's Machine Learning Department in 2016. Veloso describes her research goals as the "effective construction of autonomous agents where cognition, perception, and action are combined to address planning, execution, and learning tasks". Veloso and her students have researched and developed a variety of autonomous robots, including teams of soccer robots, and mobile service robots. Her robot soccer teams have been RoboCup world champions several times, and the CoBot mobile robots have autonomously navigated for more than 1,000 km in university buildings. In a November 2016 interview, Veloso discussed the ethical responsibility inherent in developing autonomous systems, and expressed her optimism that the technology would be put to use for the good of humankind.

Honors and awards National Science Foundation CAREER Award in 1995. Allen Newell Medal for Excellence in Research in 1997. 2003 AAAI Fellow 2006/2007 Radcliffe Fellow at the Radcliffe Institute for Advanced Study, Harvard University 2010 Institute of Electrical and Electronics Engineers (IEEE) Fellow 2010 American Association for the Advancement of Science (AAAS) Fellow 2009 ACM/SIGART Autonomous Agents Research Award 2012 Einstein Chair Professor, Chinese Academy of Sciences 2016 ACM Fellow, for "contributions to the field of artificial intelligence, in particular in planning, learning, multi-agent systems, and robotics." Veloso is featured in the Notable Women in Computing cards.

References

Illustrations

Worked examples

Example 1 — a first encounter with Manuela M. Veloso

Start with the simplest possible case. Write down what Manuela M. Veloso claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In astronomy, 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 Manuela M. Veloso 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 Manuela M. Veloso 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 Manuela M. Veloso

In research: Manuela M. Veloso appears in astronomy 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 Manuela M. Veloso 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: Manuela M. Veloso is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1957 births, 21st-century Portuguese women scientists, American people of Portuguese descent, so understanding it makes those chapters shorter.
In everyday life: Look for Manuela M. Veloso 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 Manuela M. Veloso in 20 minutes

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

Frequently asked questions

What is Manuela M. Veloso in simple terms?

Manuela Maria Veloso (born August 12, 1957) is the Head of J.P. Morgan AI Research & Herbert A.

Why does Manuela M. Veloso matter?

Because it connects several astronomy 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 Manuela M. Veloso?

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 Manuela M. Veloso.