Acknowledgement format for research work done on ARGO:

“These experiments were run on ARGO, a research computing cluster provided by the Office of Research Computing at George Mason University, VA. (URL:



Toor, A. S., & Wechsler, H. “Biometrics and forensics integration using deep multi-modal semantic alignment and joint embedding.”, Pattern Recognition Letters, February 2017. doi:10.1016/j.patrec.2017.02.012

Weisburd, D. Braga, A. A., Groff, E. R., and Wooditch, A. “Can Hot Spots Policing Reduce Crime in Urban Areas? An Agent-Based Simulation.”, Criminology, Volume 55, Number 1, pp. 137-173, 2017. doi:10.1111/1745-9125.12131


A. Naik and H. Rangwala. “Embedding Feature Selection for Large-scale Hierarchical Classification”, 2016 IEEE Big Data, Washington D.C., 5-8 December 2016.

A. Naik and H. Rangwala. “Inconsistent Node Flattening for Improving Top-down Hierarchical Classification”, 2016 IEEE International Conference on Data Science and Advanced Analytics, Montreal, Canada, October 2016.

A. Naik and H. Rangwala. “Large-scale Hierarchical Classification with Rare Categories and Inconsistencies”, AI Matters, Vol. 2(3), pp. 27-29, June 2016.

A. Mousavian, H. Pirsiavash, J. Kosecka. “Joint Semantic Segmentation and Depth Estimation with Deep Convolutional Networks”, International Conference on 3DVision, Stanford CA, USA, October 2016

Georgios Georgakis, Md Alimoor Reza, Arsalan Mousavian, Phi-Hung Le, Jana Kosecka. “Multiview RGB-D Dataset for Object Instance Detection.” International Conference on 3D Vision (3DV), Stanford CA, USA, October 2016

A. Harbir, E. Otarola, and A. J. Salgado. “A SPACE-TIME FRACTIONAL OPTIMAL CONTROL PROBLEM: ANALYSIS AND DISCRETIZATION” (2016). SIAM J. Control Optimization, Vol. 54, No. 3, pp. 1295-1328.

Lincoln Mullen. America’s Public Bible: Biblical Quotations in U.S. Newspapers, website, code, and datasets (2016).  Won First Prize from the National Endowment for the Humanities, see the announcement.

Maximova T, Carr D, Plaku E, Shehu A. “Sample-based Models of Protein Structural Transitions” Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, Seattle, WA, October 2016, pp. 128-137.

Maximova T, Plaku E, Shehu A. “Structure-guided Protein Transition Modeling with a Probabilistic Roadmap Algorithm” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2016, 13(4), doi:10.1109/TCBB.2016.2586044


A. Charuvaka and H. Rangwala. “HierCost: Improving Large Scale Hierarchical Classification with Cost Sensitive Learning.” In Proceedings of European Conference in Machine Learning and Knowledge Discovery in Databases, 2015

M. Drummond “Power and Performance Characterization of SPLASH2 Benchmarks on Heterogeneous Architecture.” Master of Science Thesis, Electrical and Computer Engineering, GMU, Summer 2015.

M. H. Hajkazemi, M. Chorney, R. J. Behrouz, M. K. Tavana, and H. Homayoun. “Adaptive Bandwidth Management for Performance-Temperature Trade-offs in Heterogeneous HMC+ DDRx Memory”, in Proceedings of the 25th edition on Great Lakes Symposium on VLSI, pp. 391-396. ACM, 2015.

M. H. Hajkazemi, M. K. Tavana, and H. Homayoun. “Wide I/O or LPDDR? Exploration and Analysis of Performance, Power and Temperature Trade-offs of Emerging DRAM Technologies in Embedded MPSoCs”, in Proceedings of the 33rd IEEE International Conference on Computer Design (ICCD), October 2015.

A. Naik and H. Rangwala. “A Ranking-based approach for Hierarchical Classification”, 2015 IEEE International Conference on Data Science and Advanced Analytics, Paris, France, October 2015 .

M. Bandari, R. Simon, and H. Aydin. Power Management in Cluster-Based Energy-Harvesting Sensor Networks through Dynamic Modulation Scaling. In Proceedings of the 12th IEEE International Conference on Embedded Software and Systems (ICESS’15), New York City, NY, August 2015. (Best Student Paper Award) 

R. Khade, J.Lin, and N.Patel “Frequent Set Mining for Streaming Mixed and Large Data.” Proceedings of International Conference of Machine Learning and Applications, December 9-11, 2015 at Miami, FL, USA.

A. Liakos and N. A. Malamataris  “Topological study of steady state, three dimensional flow over a backward facing step.” Computers & Fluids, Volume 118, September 2015, pages:1-18. doi:10.1016/j.compfluid.2015.05.019

Maximova T, Plaku E, Shehu A. “Computing transition paths in multiple-basin proteins with a probabilistic roadmap algorithm guided by structure data.” In Bioinformatics and Biomedicine (BIBM 2015) IEEE International Conference, pp. 35-42, 2015.

T. Saha, H. Rangwala and C. Domeniconi  “Predicting Preference Tags to Improve Item recommendation.” SIAM International Conference in Data Mining (SDM 2015), Vancouver, Canada. May 2015.

M. K. Tavana, M. H. Hajkazemi, D. Pathak, I. Savidis, and H. Homayoun. “ElasticCore: enabling dynamic heterogeneity with joint core and voltage/frequency scaling”, in Proceedings of the 52nd Annual Design Automation Conference, p. 151. ACM, 2015.


M. Bandari, R. Simon, and H. Aydin. Energy Management of Embedded Wireless Systems through Voltage and Modulation Scaling under Probabilistic Workloads. In Proceedings of the Fifth IEEE International Green Computing Conference (IGCC’14), Dallas, TX, November 2014.

A. Charuvaka and H. Rangwala. “Convex Multi-task Relationship Learning using Hinge Loss.”   In Proceedings of the IEEE Symposium Series on Computational Intelligence,  December 9-12, 2014, Orlando, FL.

A. Charuvaka and H. Rangwala. “Classifying Protein Sequences using Regularized Multi-Task Learning.”
Computational Biology and Bioinformatics (TCBB),  IEEE/ACM Transactions on, Volume:11, Issue: 6, pages 1087-1098.  DOI:10.1109/TCBB.2014.2338303

R. Clausen, B. Ma, R. Nussinov, and A. Shehu (2015) “Mapping the Conformation Space of Wildtype and Mutant H-Ras with a Memetic, Cellular, and Multiscale Evolutionary Algorithm.” PLoS Comput Biol 11(9): e1004470. doi:10.1371/journal.pcbi.1004470

M. A. Haque, H. Aydin and D. Zhu (2014) “Real-Time Scheduling under Fault Bursts with Multiple Recovery Strategy.” In Proceedings of the 20th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS’14), Berlin, Germany, April 2014.

I. Hashmi, D. Veltri, N. Kabbani and A. Shehu (2014) “Knowledge-based Search and Multiobjective Filters: Proposed Structural Models of GPCR Dimerization.”  In Proceedings of The 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), September 20-23, 2014, Newport Beach, CA.

K. Molloy, R. Clausen and A. Shehu (2014) “On the Stochastic Roadmap to Model Functionally-related Structural Transitions in Wildtype and Variant Proteins.” In Proceedings of the 2014 Robotics: Science and Systems Conference, July 12-16, 2014, Berkeley, CA.

Nils Ringe and Jennifer N. Victor with Christopher J. Carman.  Bridging the Information Gap Results produced on Argo cluster shown here.

T. Saha, H. Rangwala and C. Domeniconi (2014)  “FLIP: Active Learning for Relational Network Classification.”  In Proceedings of 7th European Conference on Machine Learning and Data Mining (ECML 2014), September 15-19, 2014 at Nancy, France.

Wright, M.  Thesis: “Evaluation of heterogeneity statistics for hydrological regional frequency analysis.” PhD Civil and Infrastructure Engineering, George Mason Univeristy (2014)

Wright, M., Ferreira, C. M. and Houck, M. “The relationship between Monte Carlo estimators of heterogeneity and error for daily to monthly time steps in a small Minnesota precipitation gauge network.” Submitted to Water Resources Research, 2014

Wright, M., Ferreira, C. M. and Houck, M. “Discriminatory power of heterogeneity statistics with respect to error of precipitation quantile estimation.” Journal of Hydrologic Engineering, Volume 20, Issue 10 (October 2015)

Wright, M., Ferreira, C. M. and Houck, M. (2014) “Evaluation of heterogeneity statistics as reasonable proxies of the error of precipitation quantile estimation in the Minneapolis-St. Paul region. ” Journal of Hydrology, (513) pages 457-466