Statistics Ph.D. Student at Texas A&M University
I am a last year Ph.D. student at Texas A&M Univeristy, Department of Statistics. I am honored to be advised by Mingyan Zhou at the University of Texas at Austin, Debdeep Pati and Jianhua Huang at the Texas A&M University. I also had the opportunity to work at the DATA (Data Analytics at Texas A&M) Lab, supervised by Xia Hu during my second year. Before joining Texas A&M, I did my undergraduate studies in Electrical Engineering and Mathematics (double majors) at Sharif University of Technology, where I also did my Masters in Applied Mathematics with focus on False Discovery Rate, advised by Kasra Alishahi. I did my last summer internship as a machine learnig researcher at ELi Lilly and Company .
Convex Polytope Trees
Mohammadreza Armandpour, Mingyaun Zhou
Under Review, implemented in PyTorch, code .
Deep Personalized Glucose Level Forecasting Using Attention-based Recurrent
Mohammadreza Armandpour, Brian Kidd, Yu Du, Mingyaun Zhou
Under Review, implemented in PyTorch, the code will be released soon.
DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs
Ali Sadeghian*, Mohammadreza Armandpour (co-first author)*, Patrick Ding, Daisy Zhe Wang
Advances in Neural Information Processing Systems (NeurIPS 2019) acceptance rate: 21.1% (1,428 accepted out of 6,743 submissions), implemented in TensorFlow, code .
Robust Negative Sampling for Network Embedding
Mohammadreza Armandpour, Patrick Ding, Jianhua Huang, Xia Hu
Association for the Advancement of Artificial Intelligence (AAAI 2019), acceptance rate 16.2% (1,150/ 7,095 ).