For Prospective Students

Basic Information
  • We always have openings for truly outstanding PhD students, starting at every year's spring and fall semesters (so no need to inquiry "whether you have PhD openings" by email). Our group is well funded, and research assistantships will be provided to PhD students by default.
  • Interested candidates for PhD opportunities are strongly encouraged to contact Dr. Wang by email. Please attach your CV, and clearly discuss your research interest and experiences. We are usually not very interested in your GPA and standard test scores.
  • Postdocs, and self-funded visitors are welcome to apply, and will be evaluated case by case. Due to the recent challenging situation of international travels, we are also open to remote collaborations, on certain basic research topics of common interest.
  • We are always open to working with UT undergraduates and master students for research projects. Please contact Dr. Wang by email and specify your interest (we prefer if you have more to share than pure "interest").
What we expect from good candidates?
  • Nothing is more important than a true enthusiasm and devotion to research. We do research only because we are really obsessed with and enjoy our research. Our research interests constantly evolve, and we always stay open to be intellectually excited and inspired by new things.
  • Two other important things that we look for: (1) a truly deep understanding of your problem of interest - don’t naively plug and play "hot" tools; (2) a solid background and a true passion for mathematics. Our research heavily leverages matrix analysis, optimization, and statistical learning.
What we provide to our students?
  • We have a very flat management structure with minimal communication overhead (“Talk is cheap. Show me the code/math”). Every student works directly and closely with Dr. Wang. The group also benefits a lot from its highly interactive, intimate, and helpful culture.
  • We provide extraordinarily strong support to students for internship, visiting, collaboration, networking, and scholarship opportunities. You can check from current group members' rich experiences.
  • Our students are highly popular among top employers, for both internship and full-time opportunities. During Ph.D. time, almost everyone spends considerable time researching with Google, Facebook, Microsoft, Amazon, Adobe, NVIDIA, and our many other industry partners, for every year.

About PI

Professor Zhangyang “Atlas” Wang [Google Scholar] is currently the Jack Kilby/Texas Instruments Endowed Assistant Professor in the Department of Electrical and Computer Engineering at The University of Texas at Austin. Meanwhile, in a part-time role, he serves as the Director of AI Research & Technology for Picsart, developing the next-generation AI-powered tools for visual creative editing. During 2021 - 2022, he held a visiting researcher position at Amazon Search. From 2017 to 2020, he was an Assistant Professor of Computer Science and Engineering, at the Texas A&M University. He received his Ph.D. degree in ECE from UIUC in 2016, advised by Professor Thomas S. Huang; and his B.E. degree in EEIS from USTC in 2012.

Prof. Wang has broad research interests spanning from the theory to the application aspects of machine learning (ML). Most recently, he studies efficient ML / learning with sparsity, robust & trustworthy ML, AutoML / learning to optimize (L2O), and graph ML, as well as their applications in computer vision and interdisciplinary science. His research is gratefully supported by NSF, DARPA, ARL, ARO, IARPA, DOE, as well as dozens of industry and university grants. He is/was an elected technical committee member of IEEE MLSP and IEEE CI; an associate editor of IEEE TCSVT (receiving the 2020 Best Associate Editor Award); and frequently serves as area chairs, guest editors, invited speakers, various panelist positions and reviewers. He has received many research awards and scholarships, including most recently an NSF CAREER award, an ARO Young Investigator Award, an INNS Aharon Katzir Young Investigator Award, an IBM Faculty Research Award, a J. P. Morgan Faculty Research Award, an Amazon Research Award, an Adobe Data Science Research Award, a Google TensorFlow Model Garden Award, a Young Faculty Fellow of TAMU, and five research competition prizes from CVPR/ICCV/ECCV.

About UT Austin

A Public Ivy (referred to a public university that can provide an Ivy League collegiate experience), UT Austin is one of the most prestigious universities in the US, and the flagship in the state of Texas. The university is a world-leading research institution in the engineering, computer science, and physical science fields. As of August 2021, 13 Nobel Prize winners, 4 Pulitzer Prize winners, 2 Turing Award winners, 2 Fields medalists, 2 Wolf Prize winners, and 2 Abel prize winners have been affiliated with the school as alumni, faculty members or researchers. The university has also been affiliated with 3 Primetime Emmy Award winners, and has produced a total of 155 Olympic medalists.

Internationally, UT Austin was ranked 34th in the 2020 "Best Global Universities" ranking by U.S. News & World Report, 45th in the world by Academic Ranking of World Universities (ARWU) in 2019, 39th worldwide by Times Higher Education World University Rankings in 2019, and 31st by the Center for World University Rankings (CWUR) in 2019. The Cockrell School of Engineering is consistently a top-10-ranked engineering school in the US.

AI/ML in UT Austin

UT Austin is among the world’s topmost universities for artificial intelligence (AI) and machine learning (ML) research. The U.S. News and World Report 2021 ranked UT Austin as No. 5 in the nation’s best AI programs. Recently, the National Science Foundation has selected UT Austin to lead the NSF AI Institute for Foundations of Machine Learning (IFML), bolstering the university’s existing strengths in this emerging field. UT Austin is poised to develop entirely new classes of algorithms that will lead to more sophisticated and beneficial AI technologies. Professor Wang is a member of the IFML team.

UT Austin has also established a campus-wide Machine Learning Laboratory, that will focus its initial research agenda on core algorithmic advances and a select set of applications that reflect the strengths and capabilities of UT Austin. The UT Machine Learning Laboratory brings together a community that includes linguists, ethicists, mathematicians, engineers, and computer scientists with plans to grow as machine learning takes on increasing importance across disciplines. Professor Wang is a core faculty member of the UT Machine Learning Laboratory.

UT Austin is home to the world-renowned Oden Institute for Computational Engineering and Sciences, an organized research unit created to foster the interdisciplinary development in computational sciences and mathematical modeling. The Oden Institute houses the interdisciplinary Ph.D/M.S program in Computational Science, Engineering & Mathematics (CSEM), which is ranked #1 in the world by CWUR in the discipline “Mathematics: Interdisciplinary Applications”. Professor Wang is an affiliated faculty member of the Oden Institute, and can solely advise graduate students from the CSEM program.

Besides, several exciting research initiatives currently being launched in UT Austin are relevant to the broader future of AI/ML, with which Professor Wang is also affiliated and involved. Examples include Texas Robotics, iMAGiNE consortium, and UT 6G.

About UT ECE

UT Austin Department of Electrical and Computer Engineering (UT ECE) has been ranked in the US top-10 over several decades. It is the largest department in the Cockrell School of Engineering with more than 2,500 students and 70 tenure/tenure-track faculty, and is housed by the fabulous EER Building. Based on U.S. News and World Report 2020, UT’s graduate programs in Electrical Engineering and Computer Engineering are ranked no. 9 and no. 6 in the U.S. respectively. UT ECE’s current faculty members include 1 Nobel Prize Winner, 1 Emmy Award winner, 4 National Academy of Engineering (NAE) Members, 9 National Academy of Inventors (NAI) Members, 5 ACM Fellows, 33 IEEE Fellows, 6 OSA Fellows, 4 SPIE Fellows, and 6 APS Fellows.

The City of Austin

Austin is the state capital of Texas, an inland city bordering the Hill Country region. Many people, including VITA members, consider Austin "the No. 1 Best Place to Live in the US". According to US News, the city of Austin has been voted the No. 1 place to live in America for three years in a row — based on affordability, job prospects and quality of life. Lately in 2021, Netflix endorses Austin as THE place in the 21st century, for young people with dreams; its 2021 TV shows in Austin are fun to watch: [Twentysomethings: Austin]

Austin is ranked No.1 fastest growing large city in the US, and No. 4 of the best large cities for startups. Recently called by Elon Musk "the biggest boomtown that America has seen in 50 years'", Austin has many other famous nicknames, including "Silicon Hills": a place that might potentially succeed Silicon Valley's leading role in the high-tech world. Many high-tech companies are headquartered at Austin nowadays, including three Fortune 500 companies (Tesla, Dell, and Oracle). It is also home to major regional offices of Apple, Facebook, IBM, Google, Amazon, AMD, Visa and more.

Austin is internationally known for its eclectic live-music scene centered around country, blues and rock. Its numerous parks and lakes are incredibly popular for hiking, biking, swimming and boating. Last but foremost, it is one of the greatest US cities for foodies and drinkers. Unsurprisingly, Austin also tops the list of best cities for young people dating ("scores high in everything") [BestPlaces]. You can check out more why living and studying in Austin is joyful, cool and promising: [Wall Street Journal] [New York Times] [Forbes] [Austin Local] [YouTube Channel].