Interdisciplinary Studies

We apply machine learning on interesting interdisciplinary problems, such as molecule generation, inverse design, ocean soundscape analysis, biomedical hypothesis generation, and bioinformatics.

  • Waqas W. Ahmed, Mohamed Farhat, Kestutis Staliunas, Xiangliang Zhang, Ying Wu. Machine learning for knowledge acquisition and accelerated inverse-design for non-Hermitian systems. Nature Communications Physics. Volume 6, Article number: 2 (2023)
  • Waqas Ahmed, Mohamed Farhat, Pai-Yen Chen, Xiangliang Zhang, and Ying Wu. A Generative Deep Learning Approach for Shape Recognition of Arbitrary Objects from Phaseless Acoustic. To appear in Advanced Intelligent Systems. 20 January 2023
  • Rongyu Lin, Zhiyuan Liu, Peng Han, Ronghui Lin, Yi Lu, Haicheng Cao, Xiao Tang, Chuanju Wang, Vishal Khandelwal, Xiangliang Zhang and Xiaohang Li. A machine learning study on superlattice electron blocking layer design for AlGaN deep ultraviolet light-emitting diodes using the stacked XGBoost/LightGBM algorithm. Journal of Materials Chemistry C. 2022,10, 17602-17610
  • Changsheng Ma, Qiang Yang, Xin Gao, Xiangliang Zhang. DEMO: Disentangled Molecular Graph Generation via an Invertible Flow Model. Accepted as a full paper by CIKM 2022.
  • Chongsheng Zhang, Bin Wang, Ke Chen, Ruixing Zong, Bofeng Mo, Yi Men, George Almpanidis, Shanxiong Chen, Xiangliang Zhang. Data-Driven Oracle Bone Rejoining: A Dataset and Practical Self-Supervised Learning Scheme. Accepted at KDD 2022 Applied Data Science Track. August 14-18, 2022, in Washington, DC. (Acceptance Rate: 195/753 = 26%)
  • Adnan Qamar, Sarah Kerdi, Najat Amin, Xiangliang Zhang, Johannes Vrouwenvelder, Noreddine Ghaffour. A deep neural networks framework for in-situ biofilm thickness detection and hydrodynamics tracing for filtration systems. Separation and Purification Technology. Volume 301, 15 November 2022.
  • Changsheng Ma, Xiangliang Zhang. GF-VAE: A Flow-based Variational Autoencoder for Molecule Generation. Accepted as a full paper at the CIKM 2021 conference (Acceptance rate = 271/1251 = 21.7%).
  • Rongyu Lin, Peng Han, Yue Wang, Ronghui Lin, Yi Lu, Zhiyuan Liu, Xiangliang Zhang, Xiaohang Li. Low resistance asymmetric III-nitride tunnel junctions designed by machine learning. Nanomaterial. 2021, 11(10), 2466
  • Duarte, Carlos M.; Chapuis, Lucille; Collin, Shaun P.; Costa, Daniel P.; Devassy, Reny P.; Eguiluz, Victor M.; Erbe, Christine; Gordon, Timothy A. C.; Halpern, Benjamin S.; Harding, Harry R.; Havlik, Michelle N.; Meekan, Mark; Merchant, Nathan D.; Miksis-Olds, Jennifer L.; Parsons, Miles; Predragovic, Milica; Radford, Andrew N.; Radford, Craig A.; Simpson, Stephen D.; Slabbekoorn, Hans; Staaterman, Erica; Van Opzeeland, Ilse C.; Winderen, Jana; Zhang, Xiangliang; Juanes, Francis. The soundscape of the Anthropocene oceanScience. Vol 371, Issue 6529. 05 February 2021​. 

Underwater Noise Pollution is Disrupting Ocean Life – But We Can Fix It.
In the Media [Time Magazine] [Reuters] [Yahoo! News] [Gulf News] [BBC News​]

  • Waqas W. Ahmed, Mohamed Farhat, Xiangliang Zhang, Ying Wu. Deterministic and probabilistic deep learning models for inverse design of broadband acoustic cloak. Regular Article in Physical Review Research. 3 (1), 013142. 2021
  • Uchenna Akujuobi, Jun Chen, Mohamed Elhoseiny, Michael Spranger, and Xiangliang Zhang. Temporal Positive-unlabeled Learning for Biomedical Hypothesis Generation via Risk Estimation.  Neural Information Processing Systems (NeurIPS 2020). Virtual-only Conference. (Acceptance rate = 1900 /9454 = 20%).
  • Cecilia Martin, Stephen Parkes, Qiannan Zhang, Xiangliang Zhang, Matthew McCabe, Carlos M. Duarte: Use of Unmanned Aerial Vehicles for Efficient Beach Litter Monitoring. Marine Pollution Bulletin. Jun;131(Pt A):662-673, 2018