Research Publications

Research Acknowledgement Guidance…

Nadine Kabbani and James L. Olds, Molecular Pharmacology May 1, 2020, 97 (5) 351-353; DOI: https://doi.org/10.1124/molpharm.120.000014

Olds, J.L. and Kabbani, N. (2020), Is nicotine exposure linked to cardiopulmonary vulnerability to COVID‐19 in the general population?. FEBS J, 287: 3651-3655. doi:10.1111/febs.15303

Brumfield KD, Huq A, Colwell RR, Olds JL, Leddy MB (2020) Microbial resolution of whole genome shotgun and 16S amplicon metagenomic sequencing using publicly available NEON data. PLoS ONE 15(2): e0228899.

Khan MS, Koizumi N, Olds JL. Biofixation of atmospheric nitrogen in the context of world staple crop production: Policy perspectives. Sci Total Environ. 2020 Jan 20;701:134945. doi: 10.1016/j.scitotenv.2019.134945. Epub 2019 Nov 2. PMID: 31734483.

Andrews, R. A. Handler, and E. Blaisten-Barojas, "Structure, energetics and thermodynamics of PLGA condensed phases from Molecular Dynamics,” Polymer 206, 122903 (2020); doi:https://doi.org/10.1016/j.polymer.2020.122903

Hopkins, G. Gogovi, E. Weisel, R. A. Handler, and E. Blaisten-Barojas, "Polyacrylamide in glycerol solutions from an atomistic perspective of the energetics, structure, and dynamics," AIP Advances 10, 085011 (2020); doi: 10.1063/5.0020850 (open access).

A. Handler, E. Blaisten-Barojas, P. M. Ligrani, P. Dong, M. Paige "Vortex Generation in a Finitely Extensible Nonlinear Elastic Peterlin Fluid Initially at Rest," Engineering Reports 2, e12135 (2020); don: 10.1002/eng2.12135 (open access).

"Workflow for investigating thermodynamic, structural and energy properties of condensed polymer systems," J. Andrews, E. Blaisten-Barojas, in Advances in Parallel & Distributed Processing, and Applications, Eds. H. R. Arabnia, et al., Springer Nature Collection, in press (expected publication Nov. 2020).

"The caloric curve of polymers from the Adaptive Tempering Monte Carlo method," G. Helmick, Y. Abere, and E. Blaisten-Barojas, in Advances in Parallel & Distributed Processing, and Applications, Eds. H. R. Arabnia, et al., Springer Nature Collection, in press (expected publication Nov. 2020).

Lev-Ari, H.; Ephraim, Y.; Mark, B.L., “Traffic Rate Network Tomography with Higher-Order Cumulants,” submitted to IEEE/ACM Transactions on Networking, August 2020.

Bijari, K., Akram, M.A. & Ascoli, G.A. An open-source framework for neuroscience metadata management applied to digital reconstructions of neuronal morphology. Brain Inf. 7, 2 (2020). https://doi.org/10.1186/s40708-020-00103-3

Santhalingam, Panneer Selvam, Yuanqi Du, Riley Wilkerson, Al Amin Hosain, Ding Zhang, Parth Pathak, Huzefa Rangwala, and Raja Kushalnagar. "Expressive ASL Recognition using Millimeter-wave Wireless Signals," 2020 17th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), Como, Italy, 2020, pp. 1-9, doi: 10.1109/SECON48991.2020.9158441.

Santhalingam, Panneer Selvam, Al Amin Hosain, Ding Zhang, Parth Pathak, Huzefa Rangwala, and Raja Kushalnagar. "mmASL: Environment-Independent ASL Gesture Recognition Using 60 GHz Millimeter-wave Signals." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4, no. 1 (2020): 1-30.

Andrews and E. Blaisten-Barojas, "Exploring with Molecular Dynamics the Structural Fate of PLGA Oligomers in Various Solvents," J. Phys. Chem B 123, 10233-10244 (2019).

Gogovi, F. Almsned, N. Bracci, K. Kehn-Hall, A. Shehu and E. Blaisten-Barojas, "Modeling the Tertiary Structure of the Rift Valley Fever Virus L protein," Molecules 24, 1768 (2019); doi:10.3390/molecules24091768 (open access)

Reitz and E. Blaisten-Barojas, "Simulating the NaK eutectic alloy with Monte Carlo and Machine Learning," Scientific Reports 9, Article number: 704 (2019) | doi:10.1038/s41598-018-36574-y (open access)

Kulkarni, Rajendra and Schintler, Laurie and Koizumi, Naoru and Olds, James and Stough, Roger R., Cryptocurrency, Stablecoins and Blockchain: Exploring Digital Money Solutions for Remittances and Inclusive Economies (December 29, 2019). 66th Annual North American Meetings of the Regional Science Association International

JL Olds, MS Khan, M Nayebpour, N Koizumi. Explainable AI: A Neurally-Inspired Decision Stack Framework. arXiv preprint arXiv:1908.103002019

Krichmar JL, Severa W, Khan MS and Olds JL (2019) Making BREAD: Biomimetic Strategies for Artificial Intelligence Now and in the Future. Front. Neurosci. 13:666. doi: 10.3389/fnins.2019.00666

Automating Knowledge Transfer with Multi-Task Optimization. Eric O. Scott and Kenneth A. De Jong. IEEE Congress on Evolutionary Computation, 2253–2260, Wellington, New Zealand. 2019

Xue, Y., Houser, P. R., Maggioni, V., Mei, Y., Kumar, S. V., & Yoon, Y. (2019) Assimilation of Satellite-based Snow Cover and Freeze/Thaw Observations into Noah-MP Land Surface Model in High Mountain Asia. Front. Earth Sci. 7, 115. https://www.frontiersin.org/articles/10.3389/feart.2019.00115/full

Xue, Yuan, P. R. Houser, Viviana Maggioni, Yiwen Mei, S. Vignesh Kumar and Yeosang Yoon. “Assimilation of Satellite-Based Snow Cover and Freeze/Thaw Observations Over High Mountain Asia.” Front. Earth Sci. (2019).

Ahmed Bin Zaman, Prasanna Parthasarathy, and Amarda Shehu. Using Sequence-Predicted Contacts to Guide Template-free Protein Structure Prediction. ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), Niagara falls, NY, 2019 (Accepted)

Ahmed Bin Zaman, Parastoo Kamranfar, Carlotta Domeniconi, and Amarda Shehu. Decoy Ensemble Reduction in Template-free Protein Structure Prediction. Computational Structural Bioinformatics Workshop (CSBW), Computational Structural Bioinformatics Workshop (CSBW), Niagara falls, NY, 2019 (Accepted).

Ahmed Bin Zaman and Amarda Shehu. Building Maps of Protein Structure Spaces in Template-free Protein Structure Prediction. Journal of Bioinformatics and Computational Biology (JBCB), 2019 (Under review).

Ahmed Bin Zaman, Kenneth A De Jong, and Amarda Shehu. Using Subpopulation EAs to Map Molecular Structure Landscapes. Genetic and Evolutionary Computation Conference (GECCO), Prague, Czech Republic, 2019.

Ahmed Bin Zaman and Amarda Shehu. Balancing Multiple Objectives in Conformation Sampling to Control Decoy Diversity in Template-free Protein Structure Prediction. BMC Bioinformatics, vol. 20, issue 1, pg. 211, 2019.

Ahmed Bin Zaman and Amarda Shehu. Equipping Decoy Generation Algorithms for Template-free Protein Structure Prediction with Maps of the Protein Conformation Space. Intl Conf on Bioinf and Comp Biol (BiCoB), Honolulu, HI, 2019.

Ahmed Bin Zaman and Amarda Shehu. A Multi-Objective Stochastic Optimization Approach for Decoy Generation in Template-free Protein Structure Prediction. Biophysical Journal, vol. 116, issue 3, Suppl. 1, 2019.

Diao, G., Zeng, D., Hu, K., Ibrahim, J. G. (2019) “Semiparametric frailty models for zeroinflated event count data in the presence of informative dropout". Biometrics, accepted.

Diao, G., Ibrahim, J. G. (2019) “Quantifying time-varying cause-specific hazards and subdistribution hazards ratios with competing risks data". Clinical Trials, 16, 363–374.

Diao, G., Ma, H., Zeng, D., Ke, C., Ibrahim, J. G. (2019) “Synthesizing studies for comparing treatment sequences in clinical trials". Biometrika, submitted.

Makrani, Hosein Mohammadi, Farnoud Farahmand, Hossein Sayadi, Sara Bondi, Sai Manoj Pudukotai Dinakarrao, Liang Zhao, Avesta Sasan, Houman Homayoun, and Setareh Rafatirad. "Pyramid: Machine Learning Framework to Estimate the Optimal Timing and Resource Usage of a High-Level Synthesis Design." arXiv preprint arXiv:1907.12952(2019).

Qiao, W. and Polonik, W. (2019). Nonparametric confidence regions for level sets: statistical properties and geometry. Electronic Journal of Statistics, 13(1), 985-1030.

Toward Learning Neural Network Encodings for Continuous Optimization Problems. Eric O. Scott and Kenneth A. De Jong. Companion Proceedings of the Genetic and Evolutionary Computation Conference, 123–124, Kyoto, Japan. 2018.

Makrani, Hosein Mohammadi, Hossein Sayadi, Devang Motwani, Han Wang, Setareh Rafatirad, and Houman Homayoun. "Energy-aware and Machine Learning-based Resource Provisioning of In-Memory Analytics on Cloud." In SoCC, p. 517. 2018.

Makrani, Hosein Mohammadi, Hossein Sayadi, Sai Manoj Pudukotai Dinakarra, Setareh Rafatirad, and Houman Homayoun. "A comprehensive memory analysis of data intensive workloads on server class architecture." In Proceedings of the International Symposium on Memory Systems, pp. 19-30. ACM, 2018.

Azad Naik and H. Rangwala, “HierFlat: Flattened Hierarchies for Improving Top-Down Hierarchical Classification”, International Journal of Data Science and Analytics (JDSA), September 2017, issn:2364-4168, doi: 10.1007/s41060-017-0070-1

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

Multitask Evolution with Cartesian Genetic Programming. Eric O. Scott and Kenneth A. De Jong. Companion Proceedings of the Genetic and Evolutionary Computation Conference, 255–256, Berlin, Germany. 2017.

"Compressed Least Squares revisited" published in the proceedings of AISTATS 2017.

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

Garzon. J.L.and Ferreira, C. M. (2016) “Storm surge modeling in large estuaries: sensitivity analyses to parameters and physical processes in the Chesapeake Bay ” Journal of Marine Sciences and Engineering 4(3):45

Garzon. J.L.and Ferreira, C. M. (2016)  “Evaluation of weather forecast systems for storm surge modeling in the Chesapeake Bay.”,  Ocean Modeling (submitted)

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