Ravdeep Pasricha

Ravdeep Pasricha

Data Mining Researcher

About Me

I am a Final Year Ph.D. Student in Computer Science and Engineering Department at University of California Riverside, where I am advised by Professor Vagelis Papalexakis. My primary research interest is in Multi-Aspect Data Mining specifically around streaming tensor decomposition algorithms and time-evolving graphs.

Prior to this, I worked in industry and have a work experience of close to three years, where I mainly worked as a DevOps engineer and spent the majority of my time involved in writing Infrastructure as a code, automation for deployments, creating/evaluating new tools which provide visibility into the system.

Apart from work, I enjoy cooking, reading, and traveling. I also ride motorcycles and have done (almost) two cross-country trips (from California to East Tennessee and back). Follow me on Instagram for my riding adventures.

Publications

Conference Papers

  • Ravdeep Pasricha, Pravallika Devineni, Evangelos E. Papalexakis, and Ramakrishnan Kannan​. Tensorized Feature Spaces for Feature Explosion​. Accepted at ICPR 2020, Milan, Italy. [Paper] [Code]

  • Ekta Gujral, Ravdeep Pasricha, and Evangelos E. Papalexakis. Beyond Rank-1: Discovering Rich Community Structure in Multi-Aspect Graphs. The Web Conference 2020, Taipei, Taiwan. [Paper]

  • Ekta Gujral, Ravdeep Pasricha, Tianxiong Yang, and Evangelos E. Papalexakis. OCTen: Online Compression-based Tensor Decomposition. IEEE CAMSAP 2019, Guadeloupe, West Indies. [Paper]

  • Ravdeep Pasricha, Ekta Gujral, and Evangelos E. Papalexakis. Identifying and Alleviating Concept Drift in Streaming Tensor Decomposition. ECML PKDD 2018, Dublin, Ireland. [Paper] [Code]

  • Ekta Gujral, Ravdeep Pasricha, and Evangelos E. Papalexakis. SamBaTen: Sampling-based Batch Incremental Tensor Decomposition. SIAM SDM 2018, San Diego, CA. [Paper]

Workshop Papers

  • Ravdeep Pasricha, Ekta Gujral, and Evangelos E. Papalexakis. Adaptive Granularity in Time Evolving Graphs as Tensors. KDD 2020 Workshop on Mining and Learning with Graphs (MLG). [Paper] [Video]

Pre-Prints

  • Ravdeep Pasricha, Ekta Gujral and Evangelos E. Papalexakis. Adaptive Granularity in Tensors: A Quest for Interpretable Structure. [Paper]