1. Ciallella, H, Russo D, Zhu H* Predictive Multitask Deep Learning Modeling of Estrogen Receptor Activity. Society of Toxicology 58th Annual Meeting, Baltimore, Maryland, March 2019.
  2. Russo D, Zhu H* Developing Mechanism-Based Animal Toxicity Models: A Chemocentric Approach Using Big Data. American Society for Cellular and Computational Toxicology 6th Annual Meeting, Bethesda, MD, September 2018. (2018 Toxicology in 21th Century student award presentation)
  3. Russo D, Zorn K, Clark AM, Korotocov A, Tkachenko V, Zhu H, Ekins S Comparison of multiple machine learning algorithms, descriptors, and metrics for estrogen receptor binding. Society of Toxicology 57th Annual Meeting, San Antonio, TX, March 2018.
  4. Zhao L, Wang W, Russo D, Aleksunes LM, Zhu H* Mechanism-Driven Computational Modeling of Hepatotoxicity Based on Chemical Information, Biological Data, and Toxicity Pathways. Society of Toxicology 57th Annual Meeting, San Antonio, TX, March 2018.
  5. Wang W, Russo D, Huang R, Xia M, Zhu H* Mechanistic evaluation of chemicals that induce oral acute toxicity by mitochondrial membrane disruption: big data profiling and analysis. American Society for Cellular and Computational Toxicology 6th Annual Meeting, Gaithersburg, Maryland, September 2017. (2017 Toxicology in 21th Century student award presentation)
  6. Russo D, Wang W, Strickland J, Shende S, Zhu H* CIIProCluster: Developing read-­across predictive toxicity models using big data. Society of Toxicology 56th Annual Meeting, Baltimore, Maryland, March 2017.
  7. Wang W, Sedykh A, Sun H, Zhao L, Russo D, Yan B, Zhu H* Virtual gold nanoparticle library: simulation, modeling, and experimental validation. Society of Toxicology 56th Annual Meeting, Baltimore, Maryland, March 2017. (2017 Drug Discovery Toxicology student award presentation)
  8. Wang Y, Wang W, Zhu H* Profiling Pesticide Landscape from Different Regulatory Agencies: Prioritize Potential Environmental Hazard Compounds by Comparing the Chemical and Biological Diversities. Society of Toxicology 56th Annual Meeting, Baltimore, Maryland, March 2017.
  9. Zhao L, Wang W, Sedykh A, Zhu H* Experimental errors in QSAR modeling sets: what we can do and what we cannot do. Society 252th national meeting, Philadelphia, PA, August, 2016.
  10. Wang W, Sedykh A, Zhao L, Yan B, Zhu H* Virtual Gold Nanoparticles. American Chemical Society 252th national meeting, Philadelphia, PA, August, 2016.
  11. Wang W, Russo D, Kim M, Zhao L, Huang R, Xia M, Hartung, T, Zhu H* Profiling and Evaluating Environmental Chemicals that Induce Oral Acute Toxicity Using Mitochondrial Membrane Potential Disruption Assay, Big Data and New Read-across Strategy. Society of Toxicology 55th Annual Meeting, New Orleans, Louisiana, March 2016.
  12. Kim M T, Zhu H* From QSAR to big data: Developing mechanism-driven predictive models for animal toxicity. American Chemical Society 250th national meeting, Boston, MA, August, 2015.
  13. Russo D P, Wang W, Kim M T, Pinolini D, Zhu H* CIIPro: An online cheminformatics portal for large scale chemical data analysis. American Chemical Society 250th national meeting, Boston, MA, August, 2015.
  14. Kim T. M., Wang W., Sedykh A., Huang R., Xia M., Zhu H* From individual datasets to big data: developing mechanism-driven predictive liver toxicity models. Society of Toxicology 54th Annual Meeting, San Diego, California, March 2015.
  15. Wang W., Sedykh A., Yan B., Zhu H* Quantitative Nanostructure Toxicity Relationship: Developing Predictive Cell Recognition Models for Gold Nanoparticles. Society of Toxicology 54th Annual Meeting, San Diego, California, March 2015.
  16. Kim T. M., Sedykh A., Zhang J., Huang R., Xia M., Zhu H* Profiling environmental chemicals that induce the antioxidant response pathway using cell-based assays and cheminformatics tools. Society of Toxicology 53th Annual Meeting, Phoenix, Arizona, March 2014.
  17. Kim T. M., Lallier B., Zhang J., Russo D., Mayer-Bacon C., Boison A., Kotchoni S. O., Martin J. V., Zhu H* Computational profiling of the binding mechanisms of GAPAA receptor ligands. American Chemical Society 245th national meeting, Indianapolis, IN, September, 2013.
  18. Zhang J., Zhu H* Applying Novel Data Mining Techniques to Create a New Chemical Database of Environmental Interest. American Chemical Society 244th national meeting, Philadelphia, PA, August, 2012
  19. Kim T. M., Zhu H* Combinatorial Quantitative Structure-Activity Relationship (QSAR) Modeling of Oral Bioavailability. American Chemical Society 244th national meeting, Philadelphia, PA, August, 2012.
  20. Zhu H* Solimeo R. L., Quantitative Structure-Activity Relationship Modeling of Animal Ocular Toxicity. Society of Toxicology 51th Annual Meeting, San Francisco, CA, March 2012.
  21. Zhu H, Zhang L., Staab J., Sedykh A., Tang H., Gomez S., Rusyn I., Tropsha A. Incorporation of ToxCast in vitro assay data and relevant toxicity pathway information improves the external prediction accuracy of Quantitative Structure-Activity Relationship (QSAR) Models of Chemical Hepatotoxicity. Society of Toxicology 50th Annual Meeting, Washington DC, March 2011.
  22. Low Y., Uehara T., Minowa Y., Yamada H., Ohno Y., Urushidani T., Sedykh A., Fourches D., Zhu H., Rusyn I., Tropsha A. Predictive value of chemical and toxicogenomic descriptors for drug-induced hepatotoxicity. Society of Toxicology 50th Annual Meeting, Washington DC, March 2011.
  23. Zhang L., Zhu H., Afantitis A., Melagraki G., Sarimveis H., Rusyn I., and Tropsha A. Quantitative Structure-Activity Relationship (QSAR) Modeling of Estrogen Receptor (ER) Binding Affinity and Virtual Screening for Potential Endocrine Disrupting Compounds (EDCs). Society of Toxicology 50th Annual Meeting, Washington DC, March 2011.
  24. Afantitis A., Melagraki G., Sarimveis H., Zhang L., Zhu H., and Tropsha A. Combinatorial QSAR Modeling of Toxicity Data Using 2D & 3D Chemical Descriptors. Book of abstract, 18th European Symposium on Quantitative Structure Activity Relationships, Rhodes, Greece September 2010
  25. Tang H., Zhu H., Sedykh A., Zhang L., Richard A. M., Rusyn I., Tropsha A. Toxicity reference database (ToxRefDB) to develop predictive toxicity models and prioritize compounds for future toxicity testing. American Chemical Society 240th national meeting, Boston, MA, August, 2010.
  26. Zhang L., Zhu H., Sedykh A., Tang H., Richard A. M., Rusyn I., Tropsha A. Using ToxCast in vitro Assays in the Hierarchical Quantitative Structure-Activity Relationship (QSAR) Modeling for Predicting in vivo Toxicity of Chemicals. Abstract 192; The 49th National Meeting of the Society of Toxicology, Salt Lake City, UT, March 2010.
  27. Sedykh A., Zhu H., Tang H., Zhang L., Richard A., Rusyn I., and Tropsha A. Using in vitro Dose-Response Profiles To Enhance QSAR Modeling of in vivo Toxicity. Abstract 185; The 49th National Meeting of the Society of Toxicology, Salt Lake City, UT, March 2010.
  28. Zhang L., Zhu H., Rusyn I., Judson R., Dix D., Houck K., Martin M., Richard A., Kavlock R., and Tropsha A. Cheminformatics Analysis of EPA ToxCast Chemical Libraries to Develop Predictive Toxicity Models and Prioritize Compounds for in vivo Toxicity Testing. EPA ToxCast Data Analysis Summit, RTP, NC, May 2009.
  29. Zhu H., Sedykh, A., Zhang, L., Rusyn I., and Tropsha, A. Using ToxCAST cell-viability and gene-expression assays as biological descriptors in QSAR modeling of animal toxicity endpoints. EPA ToxCast Data Analysis Summit, RTP, NC, May 2009.
  30. Zhu, H.; Martin, T. M.; Ye, L.; Young, D. M.; Tropsha, A. Combinatorial QSAR Modeling of Rat Acute Toxicity by Oral Exposure. Abstract 1125; The 48th National Meeting of the Society of Toxicology, Baltimore, MD, March 2009.
  31. Eastling, M.; Tropsha, A.; Ye, L.; Zhu, H.; Martin, T.; Moudgal, C. Quantitative Structure Toxicity Relationships (QSTR) Models for Predicting Acute/Sub-acute and Sub-Chronic/Chronic Adverse Effect Levels. Abstract 1124; The 48th National Meeting of the Society of Toxicology, Baltimore, MD, March 2009.
  32. Zhang, L.; Zhu, H.; Rusyn, I.; Judson, R.; Dix, D.; Houck, K.; Martin, M.; Richard, A.; Kavlock, R.; Tropsha, A. Cheminformatics Analysis of EPA ToxCAST Chemical Libraries to Identify Domains of Applicability for Predictive Toxicity Models and Prioritize Compounds for Toxicity Testing. Abstract 1088; The 48th National Meeting of the Society of Toxicology, Baltimore, MD, March 2009.
  33. Ye, L.; Zhu, H.; Golbraikh, A. and Tropsha, A. Establishing a balance between prediction accuracy and applicability domain of QSAR models. American Chemical Society 235th national meeting, New Orleans, LO, March 2008.
  34. Tropsha, A.; Golbraikh, A. and Zhu, H. Applicability domains, space coverage, and predictive power of QSAR models. American Chemical Society 235th national meeting, New Orleans, LO, March 2008.
  35. Golbraikh, A.; Zhu, H.; Ye, L.; Wang-Bell, M.; Tang, H. and Tropsha, A. Automatic detection of outliers prior to QSAR studies. American Chemical Society 235th national meeting, New Orleans, LO, March 2008.
  36. Zhu H.; Ye L.; Rusyn I.; Richard A.; Golbraikh A.; Tropsha A. Two-step Quantitative Structure Activity Relationship modeling of in vivo toxicity using in vitro cytotoxicity data. Abstract 245; The 47th National Meeting of the Society of Toxicology, Seattle, WA, March 2008.
  37. Rodgers A. D.; Zhu H.; Rusyn I.; Tropsha A. QSAR Modeling of Human Liver Adverse Effects Database Using kNN method. Abstract 244; The 47th National Meeting of the Society of Toxicology, Seattle, WA, March 2008
  38. Zhang L, Zhu H, Oprea T, Tropsha A. QSAR modeling of blood–brain barrier permeability of diverse organic compounds. Book of abstracts, American Chemical Society 234th national meeting, Boston, MA, August 2007.
  39. Zhu H., Rusyn I., Richard A., Tropsha A. The utilization of NTP-HTS data in predictive ADME/tox modeling. U.S. EPA International Science Forum on Computational Toxicology, Research Triangle Park, NC, May, 2007.
  40. Zhu H., Fourches D., Varnek A., Papa E., Gramatica P., Tetko I. V., Öberg T., Cherkasov A., Tropsha A. Combinational QSAR Modeling of Chemical Toxicants Tested Against Tetrahymena Pyriformis, U.S. EPA International Science Forum on Computational Toxicology, Research Triangle Park, NC, May, 2007.
  41. Zhu H., Wang K., Rusyn I., Richard A., Tropsha A. The utilization of NTP-HTS data in predictive ADME/tox modeling. The 46th National Meeting of Society of Toxicity, Charlotte, NC, March, 2007.
  42. Zhu H., Shi N., Fan Y., Zhou J. Activity and Conformation Changes of Dihydrofolate Reductase Induced by Denaturants, The 7th National Conference on Enzymology, Haikou, China, 1997. (In Chinese)