DML
DML Sharif University of Technology

Mehrdad Farajtabar

Group Data Science and Machine Learning
Entrance 2009

I am a senior research scientist at Google DeepMind. My research interests are deep learning, machine learning, and artificial intelligence, in general. As a research scientist, I work on continual and lifelong learning, multitask and transfer learning, understanding the training dynamics of deep neural networks and reinforcement learning. These research are inline with DeepMind's mission towards Aritifical General Intelligence. As an applied scientist and engineer, I work on applications of machine learning, specifically using recommendation and predictive models, meta learning, causal inference and reinforcement learning to improve Google's products in areas such as YouTube, Cloud and Sales. I received my Ph.D. in 2018 in Computational Science and Engineering from Georgia Institute of Technology, under the supervision of Hongyuan Zha and Le Song. I used to work on modeling and optimization of events data, stochastic point processes, and dynamics of and on the networks. Prior to that, I received my M.Sc. in Artificial Intelligence from the Computer Engineering Department at Sharif University of Technology and my B.Sc. from the same university in Software Engineering. Amid the coronavirus outbreak, I'm currenly living in and working from the greater Seattle area.

Efficient Iterative Semi-Supervised Classification on Manifold
M. Farajtabar , H.R. Rabiee , A. Shaban and A. Soltani-Farani

2011

IEEE

Mobility Aware Distributed Topology Control in Mobile Ad-Hoc Networks with Model Based Adaptive Mobility Prediction
S.A. Hosseini , K. Alizadeh , A. Khodadadi , A. Arabzadeh , M. Farajtabar , H. Zha and H.R. Rabiee

2018

IEEE

Manifold Coarse Graining for Online Semi-Supervised Learning
M. Farajtabar , A. Shaban , H.R. Rabiee and M.H. Rohban

2011

Springer Link

Recurrent Poisson Factorization for Temporal Recommendation
S.A. Hosseini , A. Khodadadi , K. Alizadeh , A. Arabzadeh , M. Farajtabar , H. Zha and H.R. Rabiee

2020

IEEE

Correlated Cascades: Compete or Cooperate
A. Zarezade , A. Khodadadi , M. Farajtabar , H.R. Rabiee , L. Song and H. Zha

2017

AAAI Press

From Local Similarity to Global Coding: An Application to Image Classification
A. Shaban , H.R. Rabiee , M. Farajtabar and M. Ghazvininejad

2013

IEEE

Online object representation learning and its application to object tracking
A. Shaban , H.R. Rabiee , M. Farajtabar and M. Fadaee

2013

AAAI Press