Ashiqur KhudaBukhsh

Hi everyone, I finished my PhD at the Computer Science Department, Carnegie Mellon University (CMU) advised by Prof. Jaime Carbonell. Right now, I am a Post doc at the same lab. My research interests include Machine Learning and Artificial Intelligence. You can find my resume here.

At UBC, I was a member of the Laboratory for Computational Intelligence, Beta Lab and Empirical Algorithmics Reading Group(EARG). My masters thesis was supervised by Kevin Leyton-Brown and Holger Hoos.

List of publications

  • Market-aware Proactive Skill Posting. A. R. KhudaBukhsh, Jong Woo Hong, Jaime G. Carbonell - Twenty-Fourth International Symposium on Methodologies for Intelligent Systems (ISMIS-18), 2018. [PDF CRC]
  • Robust learning in referral networks: a comparative analysis. A. R. KhudaBukhsh, Jaime G. Carbonell, Peter J. Jansen - Journal of Intelligent Information Systems (JIIS), June, 2018. [PDF CRC]
  • Expertise Drift in Referral Networks. A. R. KhudaBukhsh, Jaime G. Carbonell - International Conference on Autonomous Agents and Multiagent Systems (AAMAS-18), 2018. [PDF CRC]
  • Distributed Learning in Referral Networks . A. R. KhudaBukhsh - PhD thesis, 2017. [PDF]
  • Incentive Compatible Proactive Skill Posting in Referral Networks. A. R. KhudaBukhsh, Jaime G. Carbonell, Peter J. Jansen - Fifteenth European Conference on Multi-Agent Systems (EUMAS-17), 2017. [PDF CRC]
  • Robust Learning in Expert Networks: A Comparative Analysis. A. R. KhudaBukhsh, Jaime G. Carbonell, Peter J. Jansen - Twenty-Third International Symposium on Methodologies for Intelligent Systems (ISMIS-17), 2016. [PDF CRC]
  • Proactive-DIEL in Evolving Referral Networks. A. R. KhudaBukhsh, Jaime G. Carbonell, Peter J. Jansen - Fourteenth European Conference on Multi-Agent Systems (EUMAS-16), 2016. [PDF CRC]
  • Proactive Skill Posting in Referral Networks. A. R. KhudaBukhsh, Jaime G. Carbonell, Peter J. Jansen - Twenty-Ninth Australasian Joint Conference on Artificial Intelligence (AI-16), 2016. [PDF CRC]
  • Distributed Learning in Expert Referral Networks. A. R. KhudaBukhsh, Peter J. Jansen, Jaime G. Carbonell - Twenty-Second European Conference on Artificial Intelligence (ECAI-16), 2016. [PDF CRC]
  • Quantifying the Similarity of Algorithm Configurations. L. Xu*, A. R. KhudaBukhsh*, H. H. Hoos, K. Leyton-Brown - Learning and Intelligent Optimization Conference (LION10), 2016. [PDF CRC]
  • Building Effective Query Classifiers: A Case Study in Self-harm Intent Detection. A. R. KhudaBukhsh, Paul N. Bennett, Ryen W. White - Twenty-Fourth International Conference on Information and Knowledge Management (CIKM-15), 2015. [PDF CRC]
  • SATenstein: Automatically Building Local Search SAT Solvers From Components. A. R. KhudaBukhsh*, L. Xu*, H. H. Hoos, K. Leyton-Brown - Artificial Intelligence Journal (AIJ), volume 232, pp. 20-42, March 2016. [Preprint]
  • SATenstein: Automatically Building Local Search SAT Solvers From Components. A. R. KhudaBukhsh, L. Xu, H. H. Hoos, K. Leyton-Brown - Twenty-First International Joint Conference on Artificial Intelligence (IJCAI-09), 2009. [PDF CRC]
  • Detecting Non-adversarial Collusion in Crowdsourcing. A. R. KhudaBukhsh, Jaime G. Carbonell, Peter J. Jansen - Twenty-Fourth International Conference on Human Computation and Crowdsourcing (HCOMP), 2014. [PDF CRC]
  • SATenstein: Automatically Building Local Search SAT Solvers From Components . A. R. KhudaBukhsh - master thesis, 2009. [PDF]