Milanova named NVIDIA Deep Learning Institute University Ambassador

Ajani Oyindamola — Tue, 11 Jun 2019 13:11:58 +0000

A University of Arkansas at Little Rock professor has been selected as a teaching ambassador and has been granted essential resources and tools to teach deep learning skills to students, researchers, and professors in Arkansas. Dr. Mariofana Milanova, professor of computer science, has joined NVIDIA’s Deep Learning Institute (DLI) University Ambassador Program. Ambassadors are a select group of DLI-certified instructors committed to teach free instructor-led workshops at universities, academic conferences, and events exclusively for academic students, staff, and researchers. Deep learning is a branch of artificial intelligence covering a spectrum of machine learning research and industrial innovation that provides more efficient algorithms to deal with large-scale data over a broad range of fields, including neurosciences, computer vision, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, healthcare, robotics, cybersecurity, and games. As an ambassador, Milanova will receive free cloud-based training platform and lecture materials for workshops and events, reimbursement for travel and catering expenses, and early access to new training materials. Ambassadors are required to hold two workshops per year, but Milanova plans to hold at least six trainings or more per year based on demand. Since becoming an ambassador in April, she had already held a training on April 26 and May 14. Milanova thinks the high demand for the workshops is due to the fact that potential employers are looking to hire students who have these skills. “We had 40 participants for each workshop, and there is still a waiting list,” Milanova said. “This is one way students can be prepared for future jobs. Hiring companies constantly ask if students have skills in Python and deep learning. Many companies require these skills from our computer science, information science, and engineering students. Students need to know what industry employers want and how to use those skills with real-world applications.” The experience has also been beneficial to her teaching assistants for workshops, Suzan Anwar, Lamarcus Coleman, Kyle Hooks, and Esther Mead, who are graduate students in the Department of Computer Science. “The benefits are tremendous because the students can learn the advanced techniques in deep learning,” Milanova said. “I would like to say thanks to all my TAs for their wonderful support. They are all applying to become university ambassadors as well.” Anyone who completes the workshop will earn a certificate in deep learning from NVIDIA.

Doctoral student creates software that can detect emotions

Ajani Oyindamola — Wed, 22 May 2019 12:47:32 +0000

A University of Arkansas at Little Rock graduate has created a computer program that can identify emotions on a person’s face in real time. Suzan Anwar, of Little Rock, graduated May 11 from ��Vlog��ý Little Rock with a Ph.D. in computer and information science. In August, she will begin a new position as an assistant professor of computer science at Philander Smith College, where she has taught robotics courses for the past year. Anwar and her dissertation advisor, Dr. Mariofanna Milanova, professor of computer science, created a face analysis package that uses face and eye detection and eye tracking software to recognize emotions like happiness, sadness, anger, disgust, fear, and surprise. The second part of the system can track the position of a person’s head and what their eyes are looking at when they feel a specific emotion. The software has the potential for a variety of real-world applications. “I’d like for it to be used in the medical field to help kids with special needs,” Anwar said. “It can be used in marketing to see what products are grabbing people’s attention. In education, you can use it for non-native speakers to see what emotions they experience while learning a new language.” The software has already been used to ensure that weary truck drivers do not fall asleep at the wheel. “A trucking company uses it to give alerts to truck drivers who are falling asleep while driving,” Anwar said. “An alarm will go off on the driver’s phone, and the trucking company will receive a call to say they have a driver asleep.” Anwar also sees a future for the application in security to identify people who are about to commit a criminal act. “We’ve previously worked on a project for airport security,” she said. “We can link facial and emotion recognition with behaviors to learn if a person is acting suspiciously. When we see images or videos of attacks in the news, the people responsible are often acting suspiciously. If someone had noticed, I think eventually we could avoid a lot of these attacks.” Anwar earned her bachelor’s and master’s degrees in computer science in Iraq, where she worked as a lecturer in the Department of Computer Science at Salahaddin University for 12 years. “My husband (Jarjees Khaidir) started here in 2009 while I was back in Iraq completing my master’s degree,” she said. “He encouraged me to apply to ��Vlog��ý Little Rock after he saw how good the Department of Computer Science is.”

Suzan Anwar is a graduate student researching real-time facial recognition and eye-gaze estimation. Photo by Ben Krain.

Now that her studies are completed, Anwar, her husband, and three children are going on a trip to visit her family in Iraq before she begins her faculty position at Philander Smith in August. The couple has two daughters, 14 and 17, as well as a 4-year-old son, whom Anwar calls her “Ph.D. baby,” since she had him during her first year of doctoral studies. As an instructor and research assistant at ��Vlog��ý Little Rock, Anwar’s research all began with a memorable trip to Arkansas Children’s Hospital. “I had a course with Dr. Milanova, and you have to submit a project at the end of the semester,” she said. “We took a trip to Arkansas Children’s Hospital, where the researchers showed us a computer with a special camera. Children with autism would sit in front of the computer, and it would do emotion detection and eye gaze analysis. The problem is that kids don’t want to sit still for the research. The researchers asked if we could develop software that can detect emotions and gaze estimation on a tablet.” After a year, Anwar and Milanova completed a program that can track the children’s emotion and eye gaze all while they are playing games on a tablet. “The kids don’t even know the system is working while they are playing on the tablet,” Anwar said. “Children with autism don’t often look people in the eye. Sometimes, they only communicate through games. We saw that children show emotion while they are playing on the tablet, and the researchers are hoping to learn how this can help children with autism communicate better.” At ��Vlog��ý Little Rock, Anwar has won several awards, including the Outstanding First Year Ph.D. Student Award and the Top Ph.D. Student Award from the Department of Computer Science. Additionally, she has won the Applied Innovation Award and Outstanding Publication Award at the College of Engineering and Information Technology Open House.

- University News Archive - ����Vlog��ý Little Rock

Milanova named NVIDIA Deep Learning Institute University Ambassador

Doctoral student creates software that can detect emotions

- University News Archive - ��Vlog��ý Little Rock