Publications


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2024 (4)

  • Resource Efficient Bayesian Optimization N. Juneja, P. Desai, O. Wodo, J. Zola and V. Chandola. In IEEE International Conference on Cloud Computing (IEEE Cloud).
  • COMODO: Configurable Morphology Distance Operator P. Desai, N. Juneja, V. Chandola, J. Zola and O. Wodo. Computational Materials Science
  • GreenABR+: Generalized Energy-Aware Adaptive Bitrate Streaming B.O. Turkkan, T. Dai, A. Raman, T. Kosar, C. Chen, M.F. Bulut, J. Zola and D. Sow. ACM Transactions on Multimedia Computing, Communications and Applications doi
  • End-to-End Bayesian Networks Exact Learning in Shared Memory S. Karan, Z. Sayed and J. Zola. IEEE Transactions on Parallel and Distributed Systems 35 (4) pp. 634-645. doi

2023 (2)

  • SCoOL – Programming Model and Parallel Runtime for Optimization Problems Z. Sayed and J. Zola. In IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC). doi
  • Coriolis: Enabling Metagenomic Classification on Lightweight Mobile Devices A. Mikalsen and J. Zola. Bioinformatics 39 (Proceedings of ISMB 2023) doi

2022 (3)

  • Counting Induced 6-Cycles in Bipartite Graphs J. Niu, J. Zola and A.E. Sariyuce. In International Conference on Parallel Processing (ICPP). doi
  • GreenABR: Energy‐Aware Adaptive Bitrate Streaming with Deep Reinforcement Learning B.O. Turkkan, T. Dai, A. Raman, T. Kosar, C. Chen, M.F. Bulut, J. Zola and D. Sow. In ACM Multimedia Systems Conference (MMSys). doi
  • Identifying Taxonomic Units in Metagenomic DNA Streams on Mobile Devices V. Zheng, A.E. Sariyuce and J. Zola. IEEE/ACM Transactions on Computational Biology and Bioinformatics doi

2021 (2)

  • Graph-based Strategy for Establishing Morphology Similarity N. Juneja, J. Zola, V. Chandola and O. Wodo. In International Conference on Scientific and Statistical Database Management (SSDBM). pp. 169–180. doi

2020 (3)

  • Identifying Taxonomic Units in Metagenomic DNA Streams V. Zheng, A.E. Sariyuce and J. Zola. In International Workshop on Data Mining in Bioinformatics (BioKDD). doi
  • Efficient Execution of Dynamic Programming Algorithms on Apache Spark M.M. Javanmard, Z. Ahmad, J. Zola, L.-N. Chowdhury R. Pouchet and R. Harrison. In IEEE Cluster. doi
  • Learning Manifolds from Dynamic Process Data F. Schoeneman, V. Chandola, N. Napp, O. Wodo and J. Zola. MDPI Algorithms 13 (30) doi

2019 (1)

  • Solving All-Pairs Shortest-Paths Problem in Large Graphs Using Apache Spark F. Schoeneman and J. Zola. In International Conference on Parallel Processing (ICPP). doi

2018 (7)

  • Bayesian Network Model of Multiple Myeloma Patients Based on Pharmaceutical Records J. Zola, N. Fillmore, R. Samudrala, N. Mushi, M. Brophy and N. Do. (Extended Abstract, 30th Anniversary AACR Conference on Convergence: Artificial Intelligence, Big Data, and Prediction in Cancer)
  • Microstructure Design Using Graphs P. Du, A. Zebrowski, J. Zola, B. Ganapathysubramanian and O. Wodo. Nature Computational Materials 4 (50) doi
  • Privacy Preserving Analytics on Distributed Medical Data M. Blanton, A.R. Kang, S. Karan and J. Zola.
  • Fast Counting in Machine Learning Applications S. Karan, M. Eichhorn, B. Hurlburt, G. Iraci and J. Zola. In Uncertainty in Artificial Intelligence (UAI).
  • Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes F. Schoeneman, V. Chandola, N. Napp, O. Wodo and J. Zola. In IEEE International Conference on Big Data (IEEE BigData). pp. 1655–1660. doi
  • Scalable Manifold Learning for Big Data with Apache Spark F. Schoeneman and J. Zola. In IEEE International Conference on Big Data (IEEE BigData). pp. 272-281. doi
  • Applications and Challenges of Real-time Mobile DNA Analysis S. Ko, L. Sassoubre and J. Zola. In International Workshop on Mobile Computing Systems and Applications (HotMobile). pp. 1-6. doi

2017 (2)

  • Scalable Exact Parent Sets Identification in Bayesian Networks Learning with Apache Spark S. Karan and J. Zola. In IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC). pp. 33-41. doi
  • Error Metrics for Learning Reliable Manifolds from Streaming Data F. Schoeneman, S. Mahapatra, V. Chandola, N. Napp and J. Zola. In SIAM International Conference on Data Mining (SDM). pp. 750-758. doi

2016 (1)

  • Exact Structure Learning of Bayesian Networks by Optimal Path Extension S. Karan and J. Zola. In IEEE International Conference on Big Data (IEEE BigData). pp. 48-55. doi

2015 (1)

  • Automated, High Throughput Exploration of Process-structure-property Relationships Using the MapReduce Paradigm O. Wodo, J. Zola, B.S.S. Pokuri, P. Du and B. Ganapathysubramanian. Materials Discovery 1 pp. 21–28. doi


Selected SCoRe Posters