Optimization Methods, Signal Processing, and Machine Learning
Ph.D., Hong Kong University of Science and Technology
B.Eng., Huazhong University of Science and Technology
Tianyu Qiu received a B.Eng. degree in electronic and information from Huazhong University of Science and Technology in 2013 and a Ph.D. degree in electronic and computer engineering from Hong Kong University of Science and Technology in 2018. He was an exchange student at RWTH Aachen University from September 2012 to June 2013 and was a visiting student at University of Minnesota from September 2016 to July 2017. He was recognized as Shenzhen Overseas High-Caliber Personnel (Level C) in June 2019. He joined Shenzhen Institute of Big Data as a research scientist in September 2022. His research interests include optimization methods, signal processing, and machine learning.
Tianyu Qiu, Xiao Fu, Nicholas D. Sidiropoulos, and Daniel P. Palomar, “MISO Channel Estimation and Tracking from Received Signal Strength Feedback,” IEEE Transactions on Signal Processing, vol. 66, no. 7, pp. 1691–1704, Apr 2018.
Tianyu Qiu and Daniel P. Palomar, “Undersampled Sparse Phase Retrieval via Majorization-Minimization,” IEEE Transactions on Signal Processing, vol. 65, no. 22, pp. 5957–5969, Aug 2017.
Tianyu Qiu, Prabu Babu, and Daniel P. Palomar, “PRIME: Phase Retrieval via Majorization-Minimization,” IEEE Transactions on Signal Processing, vol. 64, no. 19, pp. 5174–5186, Oct 2016.