Faculty Directory
Ankit Agrawal


Ph.D. Computer Science, Iowa State University, Ames, IA

B.Tech. Computer Science and Engineering, Indian Institute of Technology, Roorkee, India

Research Interests

My research deals with high performance data mining and their applications in materials science, healthcare, social media, bioinformatics, etc., with most of the applications research done in collaboration with other researchers in respective fields.

Our ability to collect huge amounts of data (popularly known as big data) in practically all fields has greatly surpassed our analytical capability to make sense of it, underscoring the emergence and popularity of the Fourth paradigm of science, which is data-driven science and discovery. The challenge in big data mining lies not only in the size and scale of the data, but also its complexity – high-dimensional, multi-scale, spatio-temporal, and other types of complex data are becoming more commonplace. Further, different application domains introduce their own challenges and constraints. My research on high performance data mining aims at a coherent integration of high performance computing (HPC) and data mining, so as to address these challenges and enable large-scale data-guided discovery in various application domains.

Selected Publications

  • Jha, Dipendra; Wolverton, Christopher; Ward, Logan; Foster, Ian; Yang, Zijiang; Wei-Keng, Liao; Choudhary, Alok; Agrawal, Ankit, IRNet, Association for Computing Machinery:2385-2393 (2019).
  • Han, Dianwei; Agrawal, Ankit; Liao, Wei-Keng; Choudhary, Alok Nidhi, Parallel DBSCAN Algorithm Using a Data Partitioning Strategy with Spark Implementation, Institute of Electrical and Electronics Engineers Inc.:305-312 (2019).
  • Paul, Arindam; Acar, Pinar; Liao, Wei keng; Choudhary, Alok; Sundararaghavan, Veera; Agrawal, Ankit, Microstructure optimization with constrained design objectives using machine learning-based feedback-aware data-generation, Computational Materials Science 160:334-351 (2019).
  • Yang, Zijiang; Yabansu, Yuksel C.; Jha, Dipendra; Liao, Wei keng; Choudhary, Alok N.; Kalidindi, Surya R.; Agrawal, Ankit, Establishing structure-property localization linkages for elastic deformation of three-dimensional high contrast composites using deep learning approaches, Acta Materialia 166:335-345 (2019).
  • Jha, Dipendra; Ward, Logan; Paul, Arindam; Liao, Wei keng; Choudhary, Alok; Wolverton, Chris; Agrawal, Ankit, ElemNet, Scientific reports 8(1) (2018).
  • Jha, Dipendra; Singh, Saransh; Al-Bahrani, Reda; Liao, Wei Keng; Choudhary, Alok; De Graef, Marc; Agrawal, Ankit, Extracting grain orientations from EBSD patterns of polycrystalline materials using convolutional neural networks, Microscopy and Microanalysis 24(5):497-502 (2018).
  • Yang, Zijiang; Li, Xiaolin; Brinson, L Catherine; Choudhary, Alok N.; Chen, Wei; Agrawal, Ankit, Microstructural materials design via deep adversarial learning methodology, Journal of Mechanical Design, Transactions of the ASME 140(11) (2018).
  • Agrawal, Ankit; Choudhary, Alok, An online tool for predicting fatigue strength of steel alloys based on ensemble data mining, International Journal of Fatigue 113:389-400 (2018).
  • Gopalakrishnan, Kasthurirangan; Khaitan, Siddhartha K.; Choudhary, Alok; Agrawal, Ankit, Deep Convolutional Neural Networks with transfer learning for computer vision-based data-driven pavement distress detection, Construction and Building Materials 157:322-330 (2017).