Hooshmand Shokri Razaghi

hooshmand shokri columbia

Columbia University
PhD Candidate (2018)

E-mail: hooshmand@cs.columbia.edu

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I am a Ph.D. candidate in Computer Science at Columbia University. My research advisor is Liam Paninski. I work on machine learning and statistical methods for neuroscience problems.

Before, I used to work at CCLS on smart cities projects including forecast and optimization of energy consumption in smart buildings.

My research interests include Bayesian probabilistic models, time-series analysis, reinforcement learning, and optimization.

My resume and CV (as of October 2016).


education

  • PhD in Computer Science, Columbia University, 2014-Present
  • M.S. in Computer Science, Columbia University, 2012-2013
  • B.S. in Computer Engineering-Software Engineering, Sharif University of Technology, 2007-2012

projects

Smart Cities

  • Di-BOSS - comprehensive building operating system that aims to optimize energy consumption and increase security using real-time data streams to make predictions and provide recommendations for future operation.
  • NYC public transport - Feasibility study for wireless charging technology. The goal of the study was to discover the optimal locations of charging stations for buses powered by electricity using probabilistic modeling and heuristic search.

Natural Language Processing (NLP)

  • Omnimixture: Enhancing topic models with graph based representation of textual data that leads to new features that are lowly correlated with topic model features.

Neural Data Analysis

  • Processing dense multi-electrode array recording of neural activity. We are developing a method and a software to efficiently and accurately carry out spike sorting.

teaching

  • Head Teaching Assistant, Discrete Math, Columbia University, September-December 2015
  • Instructor, Introduction to Calculus, Barnard College, Columbia University, June-August 2015

papers & presentations

  • On Reliability and Scalability of Spike Sorting in Dense Multi-Electrode Arrays
  • Jin Hyung Lee, David Carlson, Espen Hagen, Gaute Einevoll, Liam Paninski, Hooshmand Shokri Razaghi, To be submitted.
  • Omnimixture: Enriched Topic Modeling
  • Lauren A. Hannah, Rebecca J. Passonneau, Hooshmand Shokri Razaghi, Ruilin Zhong, submitted to NIPS 2016.
  • Adaptive Stochastic Controller for Smart Buildings
  • Roger N. Anderson, Albert Boulanger, Promiti Dutta, and Ashish Gagneja, Hooshmand Shokri Razaghi, New York Academy of Sciences ML Conference, 2014.
  • Di-BOSS: Digital Building Operating System Solution
  • Roger N. Anderson, Albert Boulanger, Vaibhav Bhandari, Jessica Forde, Ashwath Rajan, Vivek Rathod, Hooshmand Shokri Razaghi, NIPS, 2013.
  • An Efficient Simulated Annealing Approach to Traveling Tournament Problem
  • Sevnaz Nourollahi, Kourosh Eshghi, Hooshmand Shokri Razaghi, American Journal of Operations Research (AJOR), Vol.2 No.3, September 2012.
Last Update: October 2016