Optimization for Data-Driven Science (ODDS) Research Group

Graduate Students

  • Maher Nouiehed
    Maher Nouiehed
    Maher Nouiehed is a Ph.D. candidate in Industrial and Systems Engineering at the University of Southern California (USC). He received a Master’s in Operations Research Engineering from USC in 2016 and his B.Sc. in Electrical and Computer Engineering from American University of Beirut in 2012. His research interests lie in establishing theoretical understanding and developing efficient algorithms for solving challenging large-scale optimization problems arising in various fields of data science and engineering.

 

  • Babak Barazandeh 
    Babak Barazandeh
    Babak Barazandeh is currently a second year PhD student at the University of Southen California (USC) . Before joining USC, he obtained his MS from Virginia Tech in 2017 and BS from Sharif University of Technology in 2014 in Statistics and Electrical Engineering, respectively. Babak has been awarded DIA (Diversity, Inclusion and Access) Fellowship from USC, Fellowship from Virginia Tech and Fellowship from National Elites Foundation. He also has been awarded as outstanding teaching assistant and “John Grado” graduate teaching assistant from Virginia Tech in 2016. His research interests lie in developing algorithms for non-convex learning problems such as mixture models or Generative Adversarial Networks (GANs).

 

  • Sina Baharlouei

Sina BaharloueiSina Baharlouei is a second year Ph.D student at the University of Southern California (USC), studying Industrial and Systems Engineering. He received his bachelor degree in Computer Engineering at Amirkabir University of Technology. His research interests encompass large-scale optimization theory and its applications in general machine learning models and in particular  machine learning for Bioinformatics.

 

  • Tianjian Huang
    Tianjian HuangTianjian Huang is a first-year student in Industrial and Systems Engineering at the University of Southern California. He obtained his B.Sc. in Electrical Engineering and Mathematics at Rensselaer Polytechnic Institute. His research interest lies in developing large-scale optimization algorithms, especially for training machine learning models with binary weights.

 

  • Ali Ghafelebashi
    Ali GhafelebashiAli is currently a first year Ph.D. student at the University of Southern California. He obtained his B.Sc. in Industrial Engineering from Amirkabir University of Technology in 2018 (overall GPA: 4.0/4.0). He was granted FOE (Faculty of Engineering) prize for the 1st GPA at the Department of Industrial Engineering for three-year sequence at Amirkabir University of Technology. He was awarded the membership of National Elites Foundation in 2017.

 

 

Undergraduate Students