Division Director
Division Director


Robert Rallo is a chemist and computer scientist who serves as the director for the Advanced Computing, Mathematics, and Data Division (ACMDD) at PNNL. He is also an affiliate professor in the Chemical Engineering Department at the University of Washington.

From 2017 until 2019, Robert led the Data Sciences Group in ACMDD. Before joining PNNL, he was an associate professor (2007–2016) in computer science and AI and the director of the Advanced Technology Innovation Center (2012–2016) at the Universitat Rovira i Virgili in Catalonia.

His research interests focus on the development and application of AI to support scientific discovery. Dr. Rallo serves regularly as reviewer for several national and international research organizations, including the U.S. Department of Energy, the National Science Foundation (NSF), the European Research Council, the EU Horizon2020 Program, the EU COST Program, and the NWO Research Council for Earth and Life Sciences (ALW).

Disciplines and Skills

  • Bio-inspired AI/ML. Use of scalable reservoir computing to develop surrogates of complex dynamical systems.
  • Urban data science. Development of ontologies and knowledge models for smart cities and regions, and sustainable and energy-efficient transportation in large-scale mobility networks.
  • Data-driven characterization of nano–bio interactions. Analysis and modeling of interactions at the nano–bio interface using data mining techniques and ML to understand the role of the structure and properties of nanoparticles in biological responses.
  • Nanoinformatics. Development of methodologies and tools to assess the environmental and human health impact of nanomaterials, including nanostructure–activity relationships and advanced data management systems for nanoparticle data.
  • Risk assessment. Data-driven approaches for the risk assessment of chemicals, including new methods for data fusion and uncertainty reduction, ensemble approaches and prioritization schemes to improve the accuracy of toxicity models, and geospatial models for exposure and risk assessment.


  • PhD, Universitat Rovira i Virgili, Computer Science
  • MAS, Universitat Rovira i Virgili, Educational Technology
  • MS, Universitat de Barcelona, Chemistry

Affiliations and Professional Service

  • Institute of Electrical and Electronics Engineers (IEEE) – Senior Member
  • Association for Computing Machinery (ACM)
  • Internet Society (ISOC)

Awards and Recognitions

  • Chair of the Modeling WG in the Nanosafety Cluster, European Commission, 2012–2016
  • EU Co-Chair for the Community of Research of Predictive Modeling for Human Health, U.S.-EU Dialog on nanoEHS, 2013–2015
  • Faculty Member of the NSF/EPA Center for Environmental Implications of Nanotechnology (UC CEIN), UCLA, 2008–2016



  • Thomas M, Schram M, Fox K, Strube J, Oblath NS, Rallo R, Kennedy ZC, Varga T, Battu AK, Barrett CA. Distributed heterogeneous compute infrastructure for the study of additive manufacturing systems. MRS Advances, 2020, 5(29-30), 1547-1555.
  • Laureanti J, Brandi J, Offor E, Engel D, Rallo R, Ginovska B, Martinez X, Baaden M, Baker N.A. Visualizing biomolecular electrostatics in virtual reality with UnityMol-APBS. Protein Science, 2020, 29(1), 237-246.


  • Escorihuela L, Martorell B, Rallo R, Fernandez A. Toward the computational and experimental characterization for risk assessment of metal oxide nanoparticles. Environmental Science: Nano, 2018, 5, 2241-2251.
  • Liu R, Rallo R, Cohen Y. Fractal Dimension Calculation for Big Data Using Box Locality Index. Annals of Data Science, 2018, 5(4), 549-563.
  • Gu H, Rahardianto A, Gao LX, Caro XP, Giralt J, Rallo R, Christofides PD, Cohen, Y. Fouling indicators for field monitoring the effectiveness of operational strategies of ultrafiltration as pretreatment for seawater desalination. Desalination, 2018, 431 ,86-99.
  • Escorihuela L, Fernandez F, Rallo R, Martorell B. Molecular dynamics simulations of zinc oxide solubility: from bulk down to nanoparticles. Food and Chemical Toxicology 2018, 112, 518-525.
  • Puzyn T, Jeliazkova N, Sarimveis H, Marchese Robinson RL, Lobaskin V, Rallo R, Richarz AN, Gajewicz A, Papadopulos MG, Hastings J, Cronin MTD, Benfenati E, Fernandez A. Perspectives from the NanoSafety Modelling Cluster on the validation criteria for (Q)SAR models used in nanotechnology. Food and Chemical Toxicology 2018, 112, 478-494.


  • Banares M, Hasse A, Puzyn T, Tran L, Lobaskin V, Rallo R, Oberdorster G. CompNanoTox2015: Novel Perspectives from a European Conference on Computational Nanotoxicology on predictive Nanotoxicology. Nanotoxicology 2017, 11(7), 839-845.
  • Manshian B, Pokhrel S, Himmelreich U, Tamm K, Sikk L, Fernandez A, Rallo R, Tamm t, Madler L, Soenen S. In silico design of optimal dissolution kinetics of Fe-doped ZnO nanoparticles results in Cancer-specific Toxicity in a Preclinical Rodent Model. Advanced Healthcare Materials, 2017, (6),9.


  • Tämm K, Sikk L, Burk J, Rallo R, Pokhrel S, Mädler L, Scott-Fordsmand JJ, Burk P, Tamm T. Parametrization of nanoparticles: development of full-particle nanodescriptors. Nanoscale 2016, 8, 16243-16250.
  • Toporova AP, Toporov AA, Rallo R, Leszczynska D, Leszczynski J. Nano-QSAR: Genotoxicity of Multi-Walled Carbon Nanotubes. Int. J. Environ. Res., 2016, 10(1): 59-64


  • Rallo R, Fernandez F, Giralt F. Modeling the Toxicity of Metal Oxide Nanoparticles. Toxicology Letters, 2015, 238 (2), S46-S47.
  • Kamath P, Raitano G, Fernández A, Rallo R, Benfenati E. In silico exploratory study using structure-activity relationship models and metabolic information for prediction of mutagenicity based on the Ames test and rodent micronucleus assay. SAR and QSAR in Environmental Research, 2015, 12, 1017-1031
  • Marchese-Robinson RL, Cronin RTD, Richarz AN, Rallo R. An ISA-TAB-Nano based data collection framework to support data-driven modelling of nanotoxicology. Beilstein Journal of Nanotechnology, 2015, 6, 1978-1999
  • Fernández A, Rallo R, Giralt F. Prioritization of in silico models and molecular descriptors for the assessment of ready biodegradability. Environmental Research, 2015, 142, 161-168
  • Toropova AP, Toropov AA, Kudyshkin VO, Rallo R. Prediction of the Q-e parameters from structures of transfer chain agents. J. Polym. Res. 2015, 22,128
  • Liu R, Rallo R, Bilal M, Cohen Y. Quantitative Structure-Activity Relationships for Cellular Uptake of Surface-Modified Nanoparticles. Combinatorial Chemistry and High Throughput Screening, 2015, 18 (4), 365-375
  • Kamath P, Fernández A, Giralt F, Rallo R. Predicting Cell Association of Surface-Modified Nanoparticles Using Protein Corona Structure – Activity Relationships (PCSAR). Current Topics in Medicinal Chemistry, 2015, (15)18, 1930-1937
  • Toropov AA, Rallo R, Toropova AP. Use of Quasi-SMILES and Monte Carlo Optimization to Develop Quantitative Feature Property/Activity Relationships (QFPR/QFAR) for Nanomaterials. Current Topics in Medicinal Chemistry, 2015, (15)18, 1837-1844
  • Toropova AP, Toropov AA, Rallo R, Leszczynska D, Leszczynski J. Optimal descriptor as a translator of eclectic data into prediction of cytotoxicity for metal oxide nanoparticles under different conditions. Ecotoxicology and Environmental Safety, 2015, 112, 39-45


  • Pascual X, Gu H, Bartman A, Zhu A, Rahardianto A, Giralt J, Rallo R, et al. Fault Detection and Isolation in a Spiral-Wound Reverse Osmosis (RO) Desalination Plant. Ind. Eng. Chem. Res., 2014, 53 (8), 3257–3271


  • Liu R, France B, George S, Rallo R et al. Association Rule Mining of Cellular Responses induced by Metal and Metal Oxide Nanoparticles. Analyst, 2013 139 (5), 943-953
  • Liu R, Hassan T, Rallo R, Cohen Y. HDAT: web-based high-throughput screening data analysis tools. Computational Science & Discovery, 2013, 6 014006
  • Nendza M, Gabbert S, Kühne R, Lombardo A, Roncaglioni A, Benfenati E, Benigni R, Bossa C, Strempel S, Scheringer M, Fernández A, Rallo R, et al. A comparative survey of chemistry-driven in silico methods to identify hazardous substances under REACH. Regul Toxicol Pharmacol. 2013, 66(3):301-314.
  • Liu R, Zhang HY, Ji ZX, Rallo R et al. Development of Structure – Activity Relationship for Metal Oxide Nanoparticles. Nanoscale, 2013 5(12):5644-53.
  • Pascual X, Gu H, Bartman AR, Zhu, A, Rahardianto A, Giralt J, Rallo R et al. Data-driven models of steady state and transient operations of spiral-wound RO plant. Desalination, 2013 316:154-161
  • Patel T, Telesca D, Rallo R et al. Hierarchical Rank Aggregation with Applications to Nanotoxicology. Journal of Agricultural, Biological and Environmental Statistics, 2013 18(2):159-177
  • Liu R, Rallo R et al. Nano-SAR Development for Bioactivity of Nanoparticles with Considerations of Decision Boundaries. Small, 2013 27(9-10):1842-52
  • Strebel K, Espinosa G, Giralt F, Kindler A, Rallo R et al. Modelling airborne benzene in space and time with self-organizing maps and Bayesian techniques. Environmental Modelling & Software 2013 41: 151-162.


  • Zhang H, Ji Z, Xia T, Meng H, Low-Kam C, Liu R, Pokhrel S, Lin S, Wang X, Liao Y, Wang M, Li L, Rallo R et al. Use of Metal Oxide Nanoparticle Band Gap to Develop a Predictive Paradigm for Oxidative Stress and Acute Pulmonary Inflammation. ACS Nano, 2012 6(5):4349-68 (ISI Web of Science- Highly cited paper – Chemistry – top 1%)
  • Cohen Y, Rallo R et al. In Silico Analysis of Nanomaterials Hazard and Risk. Accounts of Chemical Research, 2012 46(3):802-812.
  • Liu R, Lin S, Rallo R et al. Automated Phenotype Recognition for Zebrafish Embryo Based In Vivo High Throughput Toxicity Screening of Engineered Nano-Materials. PLoS ONE 2012 7(4): e35014. (PLoS ONE – highly cited paper – Top 25%)
  • Fernández A; Lombardo A; Rallo R et al. Quantitative consensus of bioaccumulation models for integrated testing strategies. Environment International, 2012 45:51-58


  • Liu H, Surawanvijit S, Rallo R et al. Analysis of Nanoparticle Agglomeration in Aqueous Suspensions via Constant-Number Monte Carlo Simulation. Environmental Science and Technology, 2011 45(21): 9284-9292
  • Liu R, Rallo R, Cohen Y. Unsupervised Feature Selection using Incremental Least Squares. International Journal of Information and Decision Making, 2011 10(6):967-987
  • Liu R, Rallo R et al. Classification Nano-SAR development for Cytotoxicity of Metal Oxide Nanoparticles. Small, 2011 7(8):1118-1126
  • Zhang H, Xia T, Meng H, Xue M, George S, Ji Z, Wang X, Liu R, Wang M, France B, Rallo R et al. Differential Expression of Syndecan-1 Mediates Cationic Nanoparticle Toxicity in Undifferentiated versus Differentiated Normal Human Bronchial Epithelial Cells. ACS Nano, 2011 5(4):2756-2769
  • George S, Xia T, Rallo R, Zhao Y, Ji Z, Lin S, Wang X, Zhang H, France B, Schoenfeld D, Damoiseaux R, Liu R, Lin S, Bradley KA, Cohen Y, Nel AE. Use of a high-throughput screening approach coupled with in vivo zebrafish embryo screening to develop hazard ranking for engineered nanomaterials. ACS Nano. 2011 5(3):1805-17. doi: 10.1021/nn102734s.
  • Damoiseaux R; George S; Li M; Pokhrel S; Ji Z; France B; Xia T,Suarez E; Rallo R et al. No time to lose – high throughput screening to assess nanomaterial safety. Nanoscale, 2011 3(4):1345-1360
  • Rallo R et al. Self-Organizing Map Analysis of Toxicity-related Cell Signaling Pathways for Metal and Metal Oxide Nanoparticles. Environmental Science and Technology, 2011 45(4): 1695-1702


  • Martinez I, Grifoll J, Rallo R, Giralt F. Multimedia environmental chemical partitioning from molecular information. Science of the Total Environment, 2010 409(2):412-422
  • Bartman A., Lyster E., Rallo R., Christofides PD., Cohen Y. (2010) Mineral Scaling Monitoring for reverse osmosis desalination via real-time membrane surface image analysis. Desalination, 273(1):64-71
  • Pistocchi A, Groenwold J, Lahr J, Loos M, Mujica M, Ragas A, Rallo R et al. Mapping Cumulative Environmental Risks: Examples from the EU NoMiracle Project. Environ. Model. Assess. 2010 16(2):119-133
  • Sorensen PB, Giralt F, Rallo R et al. Conscious worst-case definition for risk assessment, part II A methodological case study for pesticide risk assessment. Science of the Total Environment, 2010 :3860-3870


  • Lyster E, Au J, Rallo R et al. Coupled 3-D Hydrodynamics and Mass Transfer Analysis of Mineral Scaling-Induced Flux Decline in a Laboratory Plate-and-Frame Reverse Osmosis Membrane Module. Journal of Membrane Science, 2009 339,39:48
  • Fernández A, Rallo R, Giralt F. Uncertainty reduction in environmental data with conflicting information. Environ Sci Technol. 2009 43(13):5001-6
  • Solanas A, Gavalda A, Rallo R. Micro-SOM: A Linear-Time Multivariate Microaggregation Algorithm Based on Self-Organizing Maps. ICANN, Lecture Notes in Computer Science, 2009 5768:525-535


  • Libotean D, Giralt J, Giralt F, Rallo R, Wolfe T, Cohen Y. Neural Network Approach for Modeling the Performance of Reverse Osmosis Membrane Desalting. Journal of Membrane Science, 2008 (326)2,408:419
  • Libotean D, Giralt J, Rallo R, Cohen Y, Giralt F, Ridgway HF, Rodriguez G, Phipps D. Organic Compounds Passage through RO Membranes. Journal of Membrane Science, 2008 (313)1-2:23-43


  • Rallo R, Espinosa G Giralt F. Using an ensemble of neural based QSARs for the prediction of toxicological properties of chemical contaminants, Trans IChemE Part B. Process Safety and Environmental Protection, 2005 83(B4), 387-392


  • Rallo R, Ferré-Giné J, Arenas A, Giralt F. Neural Virtual Sensor for the Inferential Prediction of Product Quality from Process Variables. Computers and Chemical Engineering 2002 (26) 12, 1735-54


  • Giralt F, Arenas A, Ferre-Giné J, Rallo R, Kopp GA. The simulation and Interpretation of free turbulence with a cognitive neural system. Physics of Fluids, 2000 12, 1826


  • Ferre-Giné J, Rallo R, Arenas A, Giralt F. Extraction of structures from turbulent signals. Artificial Intelligence in Engineering, 1997 11, 413-419


  • Ferre-Giné J, Rallo R, Arenas A, Giralt F. Identification of coherent structures in turbulent shear flows with a fuzzy ARTMAP neural network. International Journal of neural Systems, 1996 7, 559-568