Check out research updates and our news coverage below.  

Physics students meet Nobel Laureate

On September 8, Nobel laureate Dr. Arthur B. McDonald met with NYUAD Physics students ahead of his Research Institute Lecture titled Understanding Our Universe From 2 KM Underground.

Light-1 launch

UAE-Bahraini nanosatellite Light-1 launched successfully into Orbit from the International Space Station. Read about how NYU Abu Dhabi was involved in the historic launch. Read about it here in Italian or here in English. 

First PhD Fellow in Physics defends thesis

Last week, Samuele Crespi became NYUAD’s first ever PhD Fellow in Physics to defend his thesis. Titled, ‘The Problem of Including Collisions in Simulations of Rocky Planet Formation’, the talk was attended by members of our Physics program, the Division of Science. 

Research Associate, Moe Abbas discusses Space Junk on a New Morning program on August 26, 2022. 

What is space junk and how dangerous are they? How did we pollute space and how can we clean it up? 

A cosmic romance written in the stars

An international team of astronomers, including CAP3 Fellow, Research Associate, Benjamin Davis has made a rare finding of what could be one of the largely missing population of “intermediate-mass” black holes. Read about the Arabic News on Al Khaleej here

Mohamad Ali-Dib wins in the 5th Annual NYUAD Graduate & Postdoctoral Research Showcase

Mohamad Ali-Dib works as a Research Scientist at CAP3. An abstract of his winning presentation on Craters Identification with Artificial Intelligence is below.

Impact craters are the dominant morphological structures on most solar system planets and moons. Their numbers can be used as a diagnostic tool to estimate the surface age of objects, while their shapes and sizes encode valuable information on the impactors that created these craters. Finding new craters and retrieving their sizes has, however, generally been a manual process, and as such is rather extremely time-consuming. Mohamad's research focuses on using modern Artificial Intelligence techniques to detect craters in space probes imagery data. The algorithms he developed are currently being deployed to help plan the upcoming Emirates Lunar Rover's path on the Moon.

Image: Lunar surface (left) and the craters detected by the machine learning algorithm Mohamad developed (right)

NYUAD student team wins an Award of Excellence from the Worldwide Logo Design competition for visual identity of new Center for Astro, Particle, and Planetary Physics (CAP3)

An NYUAD student group was awarded an Award of Excellence from the Worldwide Logo Design Award (WOLDA) for exemplary design and concept in the New Logo, Asia category. Over 223 logos and identities from 30 countries participated in the eleventh WOLDA awards.

The WOLDA is a worldwide competition for logos and corporate identity, honoring the world’s best work. It was founded in 2006 in Milan, Italy and is now organized by the International Editorial-Design and Research Forum in Meerbusch, Germany.

The NYUAD student group was composed of Manesha Ramesh, Ilya Akimov, and Jude Al Qubaisi. In fall 2019, the group took the Foundations of Graphic Design class with Assistant Professor of Practice of Visual Arts, Goffredo Puccetti. As part of the course, the whole class brainstormed, drafted and pitched new center visual identities for the Center for Astro, Particle, and Planetary Physics (CAP3). And mentored by Professor Puccetti, the winning team did a fantastic job!


  • Professor: Goffredo Puccetti
  • Logo concept: Manesha Ramesh
  • Visual Identity: Manesha Ramesh, Ilya Akimov, Jude Al Qubaisi
  • Masters: Humus Design

Writing in the stars

Using an AI technique (a neural network architecture called cycleGAN) Mario Pasquato turned simulated star clusters into the Center for Astro, Particle, and Planetary Physic's abbreviation CAP3. The neural net learns to translate images from one class (e.g. pictures taken in winter) to another (e.g. pictures taken in summer) by being shown examples. The result is very general and can be applied to translating a distribution of black points on a white background, as would be obtained by a dynamical simulation of a star cluster, into APOD-like pictures (on which the net was actually trained). Effectively, Mario generated these images that appear as if he is "writing with stars”.

The images points_X.png are semi-random distributions of points in the shapes of letters, and the resulting output is in the pictures named X.png. 

Mind Over Dark Matter

Professor Andrea Macciò has been searching his entire life for something that science knows is there but has never seen.