Previous Members

  • Zhiling Long, Post-doc

  • Yazeed Alaudah, Ph. D. (Summer 2019) - Machine Learning Engineer at Airbus Aerial. [LinkedIn]

  • Yuting Hu, Ph. D. (Summer 2019) - Senior Engineer at Qualcomm. [LinkedIn]

  • Tariq Alshawi, Ph. D. (Spring 2018) - Assistant Processor at King Saud University, Riyadh, Saudi Arabia. [LinkedIn]

  • Muhammad Amir Shafiq, Ph. D. (Spring 2018). [LinkedIn]

  • Haibin Di, Post-doc – Data Scientist at Schlumberger [Website]

  • Mohammed Aabed, Ph.D. (Fall 2016) – Camera & Vision Systems Engineer at Amazon Lab126 [LinkedIn]

  • Hasan Al-Marzouqi, Ph. D. (Fall 2014) – Assistant Professor at The Petroleum Institute, AbuDhabi, UAE [LinkedIn]

  • Mingyu Chen, Ph. D. (Fall 2013) – Computer Vision Engineer at Magic Leap, Inc. [LinkedIn]

  • Ayntac Azgin, Ph. D. (Spring 2013) – Research Engineer at FutureWei Technologies [LinkedIn]

  • Michael Santoro, Ph. D. (Fall 2012) – Senior Software Engineer at Google [LinkedIn]

  • Mashhour Solh, Ph. D. (Fall 2011) – Algorithm Development Lead, Sr. Applied Scientist at Amazon Lab126 [LinkedIn]

  • Junlin Li, Ph. D. (Fall 2008) – Sr. Principal Scientist/Video Architect at Broadcome [LinkedIn]

  • Dihong Tian, Ph. D. (Fall 2006) – Co-Founder & CTO at Intellifusion [LinkedIn]

  • Julie Petta, M. S. (Spring 2016) – Implementation Engineer at ASTEK [LinkedIn]

  • Sanjay Kariyappa, M. S. (Spring 2015) – Hardware Engineer at Oracle [LinkedIn]

  • Keerthi S. Arumugam, M. S. (Spring 2014) – Ph.D. student at Georgia Tech [LinkedIn]

  • Wenhui Xu, M. S. (Spring 2010) – Software Engineer at Apple [LinkedIn]

  • Gerardo Orozco, M. S. (2005) – Principal RF Software Engineer at National Instruments [LinkedIn]

  • Fred Stakem, M. S. (Spring 2004) – Software Engineer at Tripwire [LinkedIn]

  • Nejat Kamaci, M. S. – Principal IC Design Engineer at Broadcom [LinkedIn]

  • Tamir Hegazy, Research Scientist – Senior Scientist at Philips Research [LinkedIn]

  • Wang Youngqiang, Post-doc

  • Adnan Chaudhry, M. S. Student (Fall 2016, Spring 2017)

  • Niranjan Kumar, M. S. Student (Fall 2016)

  • Haider Khan, Ph.D. Student (Spring 2016)

  • Taruj Goyal, Undergraduate Student

  • Varol Burak Aydemir, Undergraduate Student

  • Huijie Pan, Undergraduate Student

  • Ziran Ling, Undergraduate Student

  • Paloma Casteleiro, Undergraduate Student

  • Hai Nguyen, Undergraduate Student

  • Olusegun Adeyemo, Undergraduate Student

  • Steven Vaughn, Undergraduate Student

  • David Whitney, Undergraduate Student

  • Derek Jin, Undergraduate Student

  • Chuyao (Daniel) Feng, Undergraduate Student

  • Adhithya Rajasekaran, Undergraduate Student

  • Ke (Olivia) Tang, Undergraduate Student

  • Chenyu Li, Undergraduate Student

Prospective Students

Students with interest in digital signal processing, image and video processing,  machine learning, and computer vision and are interested in working towards their PhD. degree with me are encouraged to read through this web page and follow the below steps.

  • First, interested students must read the OLIVES research section in the Home page and visit the Publications page.

  • Second, send me the following materials:

  1. your detailed CV,

  2. a statement of purpose that illustrates in detail the value you will add to my group, your unique aspects compared to average top graduate students, and the reasons you think you are among the top 1% applicants to graduate school, and

  3. a comprehensive list of the topics that you may work on within the group and you think they will change the world and have a positive impact on humanity; for each topic state the reasons that make you a good fit to such topics.

  • Third step is for me to review all materials with the help of, at least, one Postdoctoral Fellow, and two senior Graduate students. If we decide an applicant as competitive, then I will ask the student to register a special problem course for one or two semesters, at most. Upon the conclusion of the special problem course, we decide and commit to each other for both thesis and GRA.

Why join this group?

The group runs by participation from every member. Each team consists for the most part of one Postdoc, at least one senior PhD student, at least one junior Ph.D. student, and a few undergraduate students. Students receive training on conducting literature review, reviewing publications, writing grants and funding proposals, writing papers, presenting high-quality presentations, and communication skills. The students within a group define their research topics within certain guidelines and they work together to publish and submit funding grants. Collaboration is important to the success of the group.

The technical work in the group covers a broad spectrum of visual data ranging from natural images and videos to computed subsurface images/volumes and many other types of data. This is the strength of our group where the core of processing the data based on neural networks and perceptional models drive the innovation into many applications ranging from autonomous vehicles to planets exploration and oil extraction.

Although students are encouraged to publish journal papers and write patents, we also focus on problems that may result in start ups.

New students start by reading two self development books :)

The major philosophy is that grit is key to success; Ph.D. is no different.

Examples of Alumni:

Are you interested in enjoying life and changing the world? If yes, you are at the right place! Please check out the stories of some of our alumni