Pedram Rooshenas
My official first name is Amirmohammad, but my friends, family, and my colleagues know me as Pedram, so if you are looking for Amirmohammad Rooshenas or Pedram Rooshenas you are looking at the right place :).

I am a post-doctoral researcher at the College of Information and Computer Sciences, University of Massachusetts, Amherst, and I am working with Prof. Andrew McCallum . I got my Ph.D. from the Department of Computer Science, University of Oregon, where I was working with Prof. Daniel Lowd.

I have completed my M.Sc under the supervision of Prof. Hamid R. Rabiee and Prof. Ali Movaghar at Sharif University of Technology in 2009.

I maintain Libra Toolkit , an open-source toolkit for learning and inference with discrete probabilistic models.

My Facebook address is Pedram Rooshenas

Please do not follow me on twitter because I only created the account but I have not used it yet, and I will not use it in the near future.

Click here to see my Curriculum Vitae but it is not up-to-date :(

My Google Scholar page.

You can contact me using :
email : pedram[at]cs[dot]umass[dot]edu


Research Interest

  • Energy-Based Models

  • Structured Prediction

  • Tractable Learning and Inference Algorithms

  • Probabilistic Graphical Models

  • Machine Learning



    • Publications

  • MA. Torkamani, S. Shankar, A. Rooshenas, and Phillip Wallis, Differential Equation Units: Learning Functional Forms of Activation Functions from Data, To be appeared in In Proc. of The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020.

  • A. Rooshenas, Dongxu Zhang, Gopal Sharma, and Andrew McCallum, Search-Guided, Lightly-Supervised Training of Structured Prediction Energy Networks, To be appeared in Advances in Neural Information Processing Systems 32 (NeurIPS), 2019.

  • A. Rooshenas, A. Kamath, and Andrew McCallum, Training Structured Prediction Energy Networks with Indirect Supervision, In Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics (HLT/NAACL), 2018. [ PDF ]

  • A. Rooshenas, Learning Tractable Graphical Models, Ph.D. Dissertation, 2017. [PDF]

  • A. Rooshenas and D. Lowd, Discriminative Structure Learning of Arithmetic Circuits, In Proc. of 19th International Conference on Artificial Intelligence and Statistics (AISTATS), 2016. [PDF]

  • D. Lowd and A. Rooshenas, The Libra Toolkit for Probabilistic Models, Journal of Machine Learning Research, 16:2459-2463, 2015. [PDF]

  • A. Rooshenas and D. Lowd, Learning Sum-Product Networks with Direct and Indirect Variable Interactions, In Proc. of the Thirty-First International Conference on Machine Learning (ICML 2014). [PDF [Learned models]

  • A. Rooshenas and D. Lowd, Learning Tractable Graphical Models Using Mixture of Arithmetic Circuits, Late-Breaking Developments in the Field of Artificial Intelligence, Presented at the Twenty-Seventh AAAI Conference on Artificial Intelligence, AAAI, 2013. [PDF]

  • D. Lowd and A. Rooshenas, Learning Markov Networks with Arithmetic Circuits, In Proc. of the 16th International Conference on Artificial Intelligence and Statistics (AISTATS), 2013.[PDF]

  • A. Rooshenas, H. R. Rabiee, A. Movaghar. M. Y. Naderi, Reducing Data Transmission in Wireless Sensor Networks Using Principal Component Analysis, In Proc. of The Sixth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP'10), Brisbane, Australia, 2010. [PDF][presentation file]

  • Z. Riazi, A. Rooshenas, A.Rahmani. Reducing Power Consumption Using Estimation for Scheduling in Wireless Sensor Network, CSICC 2009, Tehran, Iran, 2009 (in Farsi).

    My Google Scholar page.

    • Work Experiences

  • Apr. 2010 - Aug. 2011 Software Engineer, Maharan Engineering Group, Tehran, Iran
    Activities:   Developing a new Secure Industrial Network Protocol, Developing an OS Qualification plan for railway systems[read more]

  • Sep. 2005 - Sep. 2007 Project Manager, Sepidan System Idea Tehran, Iran
    Activities: Developing mobile social network application based on Flash and J2EE[read more]

  • Jun. 2004 - Apr. 2005 Software Developer, Eimaa Eimaa Inc. Tehran, Iran
    Activities: Working on Multimedia Message Service Enhancement Server, including System Design and Develop, Performance tuning, ,Server scaling and designing robustness into server [read more]

  • Jun. 2003 - May. 2004 Linux System Developer, Maharan Engineering Group. Tehran, Iran
    Activities: Tuning Linux kernel for embedded system, Installing remote booting for disk less systems, Developing driver for CAN-PCI cards [read more]

    • Teaching Experiences

  • Fall 2017 - Lecturer for AI/ML Seminar, University of Massachusetts Amherst.

  • Winter 2017 - Teaching assistant for Machine Learning, University of Oregon.

  • Fall 2016 - Teaching Assistant for Intro to Aritificial Intelligence, University of Oregon.

  • Spring 2016 - Guest lecturer for Probabilistic Graphical Models, University of Oregon.

  • Spring 2015 - Teaching Assistant for Probabilistic Graphical Models, University of Oregon.

  • Spring 2013 - Lab instructor for Fluency with Information Technology, University of Oregon.

  • Winter 2013 - Teaching Assistant for Intro to Algorithm, University of Oregon.

  • Fall 2012 - Teaching Assistant for Intro to Aritificial Intelligence, University of Oregon.

  • Spring 2012 - Lab instructor for Intro to Computer Networks, University of Oregon.

  • Winter 2012 - Lab instructor for Intro to Programming and Algorithms, University of Oregon.

  • Fall 2011 - Teaching Assistant for Intermediate Data Structure, University of Oregon.

  • Spring 2009 - Lecturer for Matlab Programming for Engineers course, Malek-Ashtar University of Technology

  • Spring 2009 - Teaching Assistant for Computer Networks, Sharif University of Technology.

    • Professional Service

  • Program Committee/Reviewer, AAAI’20 (4 papers), ICLR’20 (5 papers).

  • Program Committee/Reviewer, AAAI’19 (7 papers), ICLR’19 (4 papers), ICML’19 (4 papers), IJCAI’19 (5 papers), NeurIPS 2019 (5 papers).

  • Program Committee/Reviewer, IJCAI’18 (7 papers), TPM’18, LND4IR, NIPS’18 (4 papers).

  • Reviewer, International Journal of Approximate Reasoning

  • Program Committee, ICML 17 Workshop on Deep Structured Prediction, reviewed 3 papers.

  • Reviewer, ICML 17, reviewed 1 paper

  • Reviewer, Machine Learning Journal - Springer

  • Reviewer, NIPS 16, reviewed 3 papers

  • Reviewer, UAI 16, reviewed 1 paper

  • Reviewer, ICML 16, reviewed 2 papers

  • Student representative in Graduate Education Committee, CIS department, University of Oregon, Sep. 2013 - Jun. 2015

  • Program Committee, IJCAI'15, reviewed 6 papers.

  • Reviewer, AAAI'15, reviewed 2 papers

  • Reviewer, NIPS'14, reviewed 1 paper