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Dr. Ahmed Elgammal

Dr. Ahmed Elgammal is a professor, researcher and entrepreneur whose pioneering work explores the question: can AI be creative?

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Intro:

Dr. Ahmed Elgammal is a professor at the Department of Computer Science, Rutgers University. He is the founder and director of the Art and Artificial Intelligence Laboratory at Rutgers. He is also an Executive Council Faculty at Rutgers University Center for Cognitive Science. Dr. Elgammal is the founder and CEO of Artrendex, a startup that builds innovative AI technology for the art market. 

Prof. Elgammal has published over 160 peer-reviewed papers, book chapters, and books in the fields of computer vision, machine learning and computational art history. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE). He received the National Science Foundation CAREER Award in 2006.  Dr. Elgammal research on Art&AI received wide international media attention, including many reports on the Washington Post, New York Times, NBC News, the Times, the Daily Telegraph, Science News, and many others. Dr. Elgammal received his M.Sc. and Ph.D. degrees in computer science from the University of Maryland, College Park, in 2000 and 2002, respectively

Selected AI projects:

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AICAN

AICAN is an Artificial Intelligence Artist and a Collaborative Creative Partner. Each artwork AICAN makes is an answer to the question "If we teach the machine about art and styles and push it to generate novel images that do not follow established styles, what would it generate?

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ArtPI - The Art API

ArtPI is an AI-system that provides insight into fine art collections and provides professionals valuable insights on the art market industry. You can use it to discover visual similarities within one's collection, engage visitors to browse and discover related content.

Elgammal on using artificial intelligence:

Why explore AI for its ability to understand and create art?

“I came to study computer science, and the most fascinating thing to me was how to increase a machine’s intelligence. I’m intrigued by the idea of how to make a computer understand the visual world around us the same way we do. I established a lab called ‘Artery’, an A.I. lab at Rutgers. I saw that a machine could not be called intelligent unless the machine could also understand and create cultural products; not just visual art but also music, literature, or jokes. There are layers of understanding and context there that humans go through, but machines cannot do anything like that.

When we started, we were trying to look at art at a macro level because humans are usually very good at looking at the details, but it's impossible for a person to look at all of art history at once. However, machines can do this well. A machine can look at someone's artwork and can figure out how the art evolved. We could give the machine images and the machine would start generating more of the same, but that isn’t art, because art is about creating something new, not emulating the past. That is my motivation: how can you give the machine art and have it create something new?

What are you trying to achieve with your work?

“We're trying to show the world two things: first, what the machine can create by itself. Second, that these are creative partners for artists in the future. I think this is analogous to the creation of photography in the 19th century, because when it was invented the definition of art back then was depicting the world on canvas, but then you have this device that can capture the world for you with the click of a button. So, what's your job as an artist? The definition of art changed as it was influenced by photography. Art focused more on the conceptualization and abstraction of the world rather than just depicting it. We now have a tool that can create things for you. It won’t take the jobs of artists away. It can explore a space of possibilities for you as an artist. You're framing it in terms of what details to feed to the machine, what you want to do with the data. Your job as an artist is the same — to control the process — but now you have a partner.”

How will AI impact human creativity?

“I think it is expanding human creativity to totally new levels. You have to have imagination to have creativity, but the human imagination is limited because we are constrained by our world. The machine is good at exploring possibilities, so if we can frame the machine to explore possibilities for you in the art space, then the machine can give you lots of new ideas.”

Current appointment:

  • Associate Professor, July 2008 – present (Assistant Professor, September 2002 – July 2008) at the Dept. of Computer Science, Rutgers, The state University of New Jersey.

  • Director of the Computer Science Master Program – 2014-present

  • Member of the Center for Computational Biomedicine Imagining & Modeling (CBIM)

  • Affiliated member with the Rutgers University Center Cognitive Science (RUCSS)

  • Director of the Art and Artificial Intelligence Laboratory – 2014-present

  • Director of the Human Motion Analysis Laboratory (HuMAn Lab)– 2002-present

Selected honors, awards and media:

  • IEEE senior member since 2013.

  • International Innovation North America Magazine has published a report about our NSF funded project on Generalized Separation of Style and Content for Human Motion Analysis, May 2013.

  • Editor Choice Paper: Image and Vision Computing Journal – April 2013 “Homeomorphic Manifold Analysis (HMA): Generalized Separation of Style and Content on Manifolds”.

  • Google Research Award 2011

  • Outstanding reviewer award, IEEE conference on Computer Vision and Pattern Recognition, June 2008.

    Rutgers Academic Excellence Award, Spring 2008.

  • National Science Foundation CAREER Award – January 2006.

  • Recipient of Honorary Mention for Best Paper Award. 4th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP'04), December 16-18, 2004, pages 656-662. Kolkata, India. With V. Shet, V. Shiv Naga Prasad, A. Elgammal, L. S. Davis, Y. Yacoob, paper title “Multi-Cue Exemplar-Based Nonparametric Model for Gesture Recognition”

The paper “Quantifying Creativity in Art Networks”:

  • Yang Wang “Why do we love Picasso? A ‘creativity algorithm’ explains” The Washington Post, July 31, 2015

  • Stephen Heyman “How Computing Can Help Art Historians” The New York Times, July 15, 2015

  • Dominic Basulto “Why it matters that computers are now able to judge human creativity” The Washington Post, June 18, 2015.

  • Devin Coldwewy “Computer Art Critic Picks Most Creative Paintings in History” NBC News, June 11, 2015.

  • Benjamin Sutton “Can an Algorithm Determine Art History’s Most Creative Paintings?” Hyperallergic, June 12, 2015.

  • Marissa Fessenden “History's Most Creative Paintings, As Picked by a Computer”, Smithsonian Magazine, June 18, 2015.

  • Richard Gray “Move over art critics! Computer algorithm reveals the most original masterpieces of all time” The Daily Mail, June 16, 2015.

  • Guelda Voien “Computer Program Ranks Relative ‘Creativity’ of Historical Paintings” Observer, June 23, 2015.

  • Rob Waugh “A Computer Has Ranked The Human Race’s ‘Best’ Art Works” Yahoo News, June 19, 2015.

  • Marc Bain “Picasso = Genius: This algorithm can judge “creativity” in art as well as the experts” Quartz, June 11, 2015.

  • Miguel Angel Criado “El Cristo de Goya, el cuadro más original para las máquinas” EL PAIS (Spain’s top national news paper, appeared also in the Brazilian edition) June 17, 2015.

  • “Los cuadros más creativos de la historia según la ciencia” ABC news paper (Spain third largest news paper)

  • Stefania Medetti “Arriva l’algoritmo che analizza e cataloga l’arte” Panorama, Italy, June 18, 2015.

  • Philip Ferrari “L'algoritmo che giudica le opere d'arte” Focus, Italy, June 15, 2015

  • “Machine Vision Algorithm Chooses the Most Creative Paintings in History” MIT Technology Review, June 10, 2015

The paper “Large-scale Classification of Fine-Art Paintings: Learning The Right Metric on The Right Feature”:

  • “The Machine Vision Algorithm Beating Art Historians at Their Own Game” MIT Technology Review, May 11, 2015.

  • Marissa Fessenden “Computers Are Learning About Art Faster than Art Historians” Smithsonian Magazine, May 13, 2015.

  • Tanya Lewis “Art-ificial Intelligence? Algorithm Sorts Paintings Like a Person” Live Science, June 19, 2015

The paper “Toward Automated Discovery of Artistic Influence”:

  • Haluka Maier-Borst “Looking for the art formula” PM Magazine, Germany, March 2015.

  • Mohana Ravindranath, “Computer Science Putting Art Analysis on Faster Track,” The Washington Post, Nov. 10, 2014.

  • Mohana Ravindranath, “Can an algorithm tell us who influenced an artist?” The Washington Post, Nov. 9, 2014.

  • Antonio Martínez Ron, “Este algoritmo quiere ser crítico de arte,” Vozpópuli, Oct. 16, 2014 (in Spanish).

  • Meghan Rosen, “Computer program reveals artists’ influences,” Science News, Oct. 13, 2014.

  • Rosalind Mckever "Can artificial intelligence really identify artistic influence?", Apollo- magazine, September 19, 2014.

  • Mostafa Heddaya, “Seeing Art History with Machine Eyes,” Hyperallergic, Aug. 26, 2014.

  • Zach Sokol, “An Intelligent Algorithm Made A Discovery That Slipped Past Art Historians For Years,” The Creators Project, Aug. 26, 2014.

  • Rafael Garcia "Scientists create computer program that analyzes painting and identifies influences between artists" article in portuguese, Folha De S. Paulo, August 24th, 2014

  • Matthew Sparkes, “Could Computers Put Art Historians Out of Work?” The Telegraph, Aug. 18, 2014. “When A Machine Learning Algorithm Studied Fine Art Paintings, It Saw Things Art Historians Had Never Noticed,” The Medium - The Physics arXiv Blog, Aug. 18, 2014.

Learn more about Dr. Ahmed Elgammal: