Balaji Lakshminarayanan

Hello! I am an MPhil/PhD student at Gatsby Computational Neuroscience Unit, University College London, working with Yee Whye Teh. I am interested in Machine Learning and its various applications.

Education

• M.S., Oregon State University (OSU), Corvallis, USA

  • Major: School of Electrical Engineering & Computer Science (EECS), Minor: Statistics
    

  • I worked with Prof. Raviv Raich and was part of the Bioacoustics research group.
    

• B.Eng, College of Engineering, Guindy, Anna University, Chennai, India

  • I was part of the Integrated Systems laboratory, where I was involved in the development of communication subsystems for the Anna University Microsatellite (ANUSAT) project.

Industry Experience

• Jan - Sep 2011: Yandex Labs, Palo Alto, USA. I worked with Dmitry Pavlov and the MLR team.
  

• Summer 2010: Machine Learning for Optimisation and Services group, Xerox Research Centre Europe, Grenoble, France. I worked with Cedric Archambeau and Guillaume Bouchard.
  

• Summer 2009: Center for Advanced Research, PricewaterhouseCoopers, San Jose, USA.

Publications

• Cedric Archambeau, Balaji Lakshminarayanan, and Guillaume Bouchard, “Latent IBP compound Dirichlet Allocation”, in NIPS workshop on “Bayesian Nonparametrics: Hope or Hype?”, Sierra Nevada, Spain, 2011 (pdf)

• Balaji Lakshminarayanan and Raviv Raich, “Inference in Supervised Latent Dirichlet Allocation”, in Proc. IEEE International Workshop on Machine Learning for Signal Processing, Beijing, China, 2011 (pdf)

• Balaji Lakshminarayanan, Guillaume Bouchard, and Cedric Archambeau, “Robust Bayesian matrix factorization”, in Proc. Intl. Conf. on Artificial Intelligence and Statistics (AISTATS), Ft. Lauderdale, USA, 2011 (revised pdf)

  • Note: the updates for were wrong in the original version of the pdf. The increments ought to be and respectively instead of 1.

• Balaji Lakshminarayanan and Raviv Raich, “Non-negative matrix factorization for parameter estimation in Hidden Markov models”, in Proc. IEEE International Workshop on Machine Learning for Signal Processing, Kittila, Finland, 2010 (pdf)

• Balaji Lakshminarayanan, Raviv Raich and Xiaoli Fern, “A syllable-level probabilistic framework for bird species identification”, in Proc. IEEE International Conference on Machine Learning and Applications, Miami, USA, 2009 (pdf)

Oregon State University

MS Thesis

• “Probabilistic models for classification of bioacoustic data” (pdf)

Course Projects

• Balaji Lakshminarayanan, Christian Baumberger and Junyuan Lin, “Supervised LDA for Transboundary Freshwater Dispute Database”, Bayesian networks course project

• Balaji Lakshminarayanan and Behrouz Behmardi, “Dimensionality reduction methods for text classification and visualization”, Machine Learning course project

• Balaji Lakshminarayanan and Paul Lewis, “A Survey of Machine Learning methods applied to Computer Architecture”, High performance computer architecture course project

• Balaji Lakshminarayanan and Jonathan Wong, “Parameter estimation for mixture of multinomial distributions”, Estimation & Detection course project

Graduate Coursework

• Fall 2008: Theory of Statistics-1, Estimation & Detection, Artificial Intelligence (sit-in)

• Winter 2009: Theory of Statistics-2, Bayesian Statistics, High performance computer architecture

• Spring 2009: Machine Learning, Stochastic signals and systems, Introduction to Financial mathematics (audited)

• Fall 2009: Non-linear Optimization, Linear Systems

• Winter 2010: Introduction to Bayesian networks, Methods of data analysis-1

• Spring 2010: Methods of data analysis-2