Gowtham Bellala

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Research Scientist
Palo Alto

Biography



Gowtham Bellala is a member of the Analytics lab within HP labs. He is currently conducting inter-disciplinary research on the applications of machine learning and data mining techniques to optimize resource consumption and enhance operational efficiency of cyber-physical systems.


He received his PhD in Electrical Engineering and Computer Science from University of Michigan, Ann Arbor in 2011. His PhD thesis focused on developing an Information theoretic framework for problems in Active Diagnosis. He has also worked on several inter-disciplinary projects involving applications of machine learning to problems in Bioinformatics, in collaboration with researchers from UTMB, University of Houston and the University of Pittsburgh.


Gowtham received an M.S in Electrical Engineering and Computer Science from the University of Michigan, Ann Arbor in 2008, and a B.Tech in Electrical Engineering from the Indian Institute of Technology, Madras in 2006.

 

Research interests

Machine Learning, Data Mining, Pattern Recognition, Statistical Signal Processing, and their applications.

Awards

  •  Distinguished Paper Award, American Medical Informatics Association, 2013.
  • .Distinguished Paper Award, American Medical Informatics Association, 2012. 

Publications

  • Z. Qazi, JK Lee, T. Jin, G. Bellala, M. Arndt, G. Noubir, "Application-awareness in SDN," ACM SigComm, 2013.
  • S. K. Bhavnani, J. A. Drake, G. Bellala, B. Dang, B. Peng, J. A. Oteo, P. Santibañez-Saenz, S. Visweswaran, J. P. Olano, "How Cytokines Co-occur across Rickettsioses Patients: From Bipartite Visual Analytics to Mechanistic Inferences of a Cytokine Storm," Proceedings of AMIA Summit on Translational Bioinformatics, 2013.  (Distinguished Paper Award)    
  • G. Bellala, J. Stanley, S. K. Bhavnani, and C. Scott, "A Rank-based Approach to Active Diagnosis," to appear in IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013. 
  • G. Bellala, M. Marwah, A. Shah, M. Arlitt, and C. E. Bash, "A Finite State Machine-based Characterization of Building Entities for Monitoring and Control," ACM BuildSys, 2012.   
  • G. Bellala, M. Marwah, M. Arlitt, G. Lyon and C. E. Bash, "Following the Electrons: Methods for Power Management in Commercial Buildings," KDD, 2012.  
  • S. K. Bhavnani, G. Bellala, S. Victor, K. E. Bassler and S. Visweswaran, "The Role of Complimentary Bipartite Visual Analytic Representations in the Analysis of SNPs: A Case Study in Ancestral Informative Markers," JAMIA, 2012.   
  • G. Bellala, S. K. Bhavnani and C. Scott, "Group-based Active Query Selection for rapid diagnosis in time-critical applications," IEEE Transactions on Information Theory, 459-478, 2012.
  • S. K. Bhavnani, G. Bellala, S. Victor, M. Abbas, V. McMicken, J. Tupa, and S. Visweswaran, "The Role of Complimentary Bipartite Visual Analytic Representations in the Analysis of SNPs: A Case Study in Ancestral Informative Markers," AMIA, 2012.  (Distinguished Paper Award) [News:.http://www.sciencedaily.com/releases/2012/06/120612115944.htm]
  • G. Bellala, M. Marwah, M. Arlitt, G. Lyon and C. E. Bash, "Towards an understanding of campus-scale power consumption." In ACM BuildSys, 2011.
  • G. Bellala, J. Stanley, C. Scott and S. K. Bhavnani, "Active Diagnosis via AUC Maximization: An Efficient Approach for Multiple-Fault Identification in Large Scale, Noisy Networks, " Proceedings of Uncertainty in Artificial Intelligence (UAI 2011). 
  • G. Bellala, S. K. Bhavnani and C. Scott, "Active Diagnosis under Persistent Noise with Unknown Noise Distribution: A Rank-based Approach," Proceedings of Artificial Intelligence and Statistics (AISTATS 2011).  
  • S. K. Bhavnani, S. Victor, W. J. Calhoun, W. W. Busse, E. Bleecker, M. Castro, H. Ju, R. Pillai, N. Oezguen, G. Bellala, A. R. Brasier, "How Cytokines co-occur across Asthma Patients: From Bipartite Network Analysis to a Molecular-based Classification," Journal of Biomedical Informatics, 44, S24-S30, 2011.  
  • G. Bellala, S. K. Bhavnani and C. Scott, "Extensions of Generalized Binary Search to Group Identification and Exponential costs," Advances in Neural Information Processing Systems 23 (NIPS 2010).  
  • S. K. Bhavnani, G. Arunkumaar, T. Hall, E. Maslowski, F. Eichinger, S. Martini, P. Saxman, G. Bellala, and M. Kretzler, " Discovering Hidden Relationships between Renal Diseases and Regulated Genes through 3D Network Visualizations," BMC Research Notes, 3:296, 2010.  
  • S. K. Bhavnani, G. Bellala, A. Ganesan, R. Krishnan, P. Saxman, C. Scott, M. Silveira and C. Given, "The Nested Structure of Cancer Symptoms: Implications for Analyzing Co-occurrence and Managing Symptoms," Methods of Information in Medicine, 49(6), 581 ‐ 591, 2010.  
  • C. Scott, G. Bellala and R. Willett, "The false discovery rate for statistical pattern recognition," Electronic Journal of Statistics, Vol. 3, 651 ‐ 677, 2009.  
  • S. K. Bhavnani, G. Bellala, A. Ganesan, R. Krishnan, P. Saxman, C. Scott, M. Silveira and C. Given, "Network Analysis of Cancer Patients and Symptoms: Implications for Symptom Management and Treatment," Proceedings of American Medical Informatics Association (AMIA), 2009.   
  • C. Scott, G. Bellala and R. Willett, "Generalization error analysis for FDR controlled classification," IEEE Workshop on Statistical Signal Processing(SSP), 792 ‐ 796, Madison, WI, August 2007.