computer science

Nina Amenta

Nina Amenta 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 Nina Amenta rather than just read about it. In short: Annamaria Beatrice "Nina" Amenta (born 1958 or 1959) is an American computer scientist and professor emeritus of computer science at the University of California, Davis. Her research is in computational geometry, computer graphics, and visualization, especially algorithms for collecting, processing, reconstructing, and visualizing three-dimensional shapes.

Key takeaways

Nina Amenta 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 Nina Amenta to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Nina Amenta from memory before moving on to harder problems.

Reference excerpt

Annamaria Beatrice "Nina" Amenta (born 1958 or 1959) is an American computer scientist and professor emeritus of computer science at the University of California, Davis. Her research is in computational geometry, computer graphics, and visualization, especially algorithms for collecting, processing, reconstructing, and visualizing three-dimensional shapes.

Education and career Amenta grew up in Pittsburgh, where as a high-school student in the 1970s she explored mathematical patterns inspired by M. C. Escher and used Carnegie Mellon University library books to learn about repeating patterns. She studied classical civilization at Yale University, graduating in 1979. After working for more than ten years as a computer programmer, including five years writing firmware for medical ultrasound machines, she returned to graduate study through the University of California, Berkeley Reentry Program. She received her Ph.D. from the University of California, Berkeley in 1994. Her dissertation, Helly Theorems and Generalized Linear Programming, was supervised by Raimund Seidel. After postdoctoral work at The Geometry Center and Xerox PARC, Amenta joined the faculty of the University of Texas at Austin. She moved to the University of California, Davis in 2002. In late 2011, Amenta became director of CITRIS at UC Davis, where she worked to connect information technology researchers with interdisciplinary projects in climate, health, visualization, and public-interest technology. At UC Davis, she served as vice-chair of the Department of Computer Science from 2007 to 2012 and chair from 2013 to 2017. She was later named professor emeritus. During graduate school at Berkeley, Amenta wrote Kali, a program for creating tessellations in the 17 wallpaper groups; it was later modified and developed by topologist Jeff Weeks. Amenta co-chaired the 2006 Symposium on Computational Geometry with Otfried Cheong.

Research Amenta is known for her work on surface reconstruction from scattered data points. Tamal K. Dey's book Curve and Surface Reconstruction describes work by Amenta and Marshall Bern as the first surface reconstruction algorithm with proved guarantees. Her later work has included point-set surfaces, geometric algorithms for three-dimensional modeling, forest LiDAR visualization, biological shape analysis, applications in graphics and visualization, and GPU-based algorithms for geometric computation. Amenta has collaborated with physical anthropologist Eric Delson on modeling gradual evolutionary change in primate skull morphology, using laser-scanned skulls and evolutionary trees based on genomic data. In 2020, Amenta, Sunghee Choi, and Ravi Kolluri received a Test of Time Award from the journal Computational Geometry: Theory and Applications for their 2001 paper "The power crust, unions of balls, and the medial axis transform". UC Davis described the paper as having provided a conceptual framework that researchers in computational geometry continued to use nearly two decades later.

Awards and honors Alfred P. Sloan Foundation Research Fellowship UC Davis Chancellor's Fellowship Computational Geometry: Theory and Applications Test of Time Award, 2020 UC Davis College of Engineering Outstanding Faculty Award for Excellence in Teaching, 2021

Selected publications Amenta, Nina (1994). "Helly theorems and generalized linear programming". Discrete & Computational Geometry. 12 (3): 241–261. Amenta, Nina; Bern, Marshall; Eppstein, David (1998). "The crust and the beta-skeleton: combinatorial curve reconstruction". Graphical Models and Image Processing. 60 (2): 125–135. Amenta, Nina; Bern, Marshall (1999). "Surface reconstruction by Voronoi filtering". Discrete & Computational Geometry. 22: 481–504. Amenta, Nina; Choi, Sunghee; Kolluri, Ravi (2001). "The power crust, unions of balls, and the medial axis transform". Computational Geometry: Theory and Applications. 19 (2–3): 127–153. Amenta, Nina; Choi, Sunghee; Dey, Tamal K.; Leekha, Naveen (2000). "A simple algorithm for homeomorphic surface reconstruction". Proceedings of the Sixteenth Annual Symposium on Computational Geometry. Association for Computing Machinery. pp. 213–222. Amenta, Nina; Attali, Dominique; Devillers, Olivier (2012). "A tight bound for the Delaunay triangulation of points on a polyhedron". Discrete & Computational Geometry. 48 (1): 19–38. Tsui, Alex; Fenton, Devin; Vuong, Phong; Hass, Joel; Koehl, Patrice; Amenta, Nina; Coeurjolly, David; DeCarli, Charles; Carmichael, Owen (2013). "Globally optimal cortical surface matching with exact landmark correspondence". Information Processing in Medical Imaging: 487–498.

References

External links Official website Annamaria Beatrice Amenta at the Mathematics Genealogy Project Google Scholar profile

Worked examples

Example 1 — a first encounter with Nina Amenta

Start with the simplest possible case. Write down what Nina Amenta 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 Nina Amenta 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 Nina Amenta 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 Nina Amenta

In research: Nina Amenta 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 Nina Amenta 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: Nina Amenta is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1950s births, 21st-century American scientists, 21st-century American women scientists, so understanding it makes those chapters shorter.
In everyday life: Look for Nina Amenta 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 Nina Amenta in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Nina Amenta 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 Nina Amenta out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Nina Amenta in simple terms?

Why does Nina Amenta 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 Nina Amenta?

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 Nina Amenta.