Farhad Pourkamali Anaraki, PhD

Assistant Professor, Computer Science Department, University of Massachusetts Lowell

Email: farhad_pourkamali [at] uml [dot] edu

Office: Dandeneau Hall 330, 1 University Ave, Lowell, MA 01854

Fall 2019 Office Hours: Tuesdays 12:30 to 2 PM, Thursdays 4 to 5:30 PM

Overview

Farhad Pourkamali is an assistant professor in the Department of Computer Science at the University of Massachusetts Lowell since fall 2018. He is also the director of Computational and Statistical Data Science (CSDS) Lab. Before joining UMass Lowell, Prof. Pourkamali spent one year as a postdoctoral research associate in the Department of Applied Mathematics at the University of Colorado Boulder, and he received his PhD in Electrical Engineering from the same institution under the supervision of Stephen Becker.

Prof. Pourkamali's research areas are machine learning, data science, and optimization. His research group focuses on the foundational and statistical aspects of machine learning as well as a diverse range of practical applications. Notably, his research team works on developing scalable and principled techniques to analyze complex high-dimensional data in unsupervised scenarios (clustering), and when labeled data is limited (active learning). Moreover, Prof. Pourkamali conducts interdisciplinary research in various areas, such as structural engineering and materials science.

Focus Areas

  • Theoretical and statistical aspects of machine learning algorithms with focus on data summarization and active learning
  • Development of scalable and robust data analytic tools and optimization methods
  • Various aspects of deep learning including generalization, regularization, and generative models
  • Applications of machine learning in structural engineering and materials science
  • Representation learning and dimensionality reduction

What's New

  • Prof. Pourkamali is organizing a seminar on Machine Learning in fall 2019, every Wednesday 4:30 to 5:30 PM in DAN 321. We have an outstanding list of speakers from top universities. This is a great opportunity for interested students and faculty members at UMass Lowell. For more information, you can see this page.
  • Prof. Pourkamali will serve as a session chair at the IEEE Machine Learning for Signal Processing Workshop (MLSP). The session is Poster Session 2, Signal Detection, Pattern Recognition, Semi/Un-supervised Learning, at 16:00-18:30pm on Monday, October 14, 2019.
  • Prof. Pourkamali is a program committee member for the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS).
  • New paper accepted to Neurocomputing: "Improved fixed-rank Nystrom approximation via QR decomposition: Practical and theoretical aspects." The paper is available online here, July 2019.
  • New paper accepted to IEEE Machine Learning for Signal Processing (MLSP): "Large-scale sparse subspace clustering using landmarks." The paper is available on arxiv here, August 2019.
  • New grant with Min Hyung Cho: "A Next Generation Electromagnetic Solver for Multilayered Media and its Applications in Photonic Passive Cooling Devices." This proposal is funded by UMass Lowell Kennedy College of Sciences Seed Grant.
  • Received travel award to attend the National Science Foundation (NSF) Grants Conference, 2019.