Ankit Agrawal

Research Associate Professor

Department of Electrical Engineering and Computer Science
McCormick School of Engineering and Applied Science
Northwestern University

Office: M384, TECH
Technological Institute
2145 Sheridan Road
Evanston, Illinois 60208-3118

Ph: 847-868-0130
Fax: 847-491-4455
Email: ankitag AT eecs.northwestern.edu
[CUCIS] [Google Scholar] [DBLP]

Recent Highlights

  • 07/2017: Invited to give a keynote lecture for Materials Genome Symposium at C-MRS 2017. See Northwestern news article.
  • 05/2017: Invited to NSF workshop on Advancing and Accelerating Materials Innovation through the Synergistic Interaction among Computation, Experiment, and Theory: Opening New Frontiers.
  • 03/2017: Awarded Northwestern Data Science Initiative Grant: Social Media mining of caregiver experiences: Opportunity for preventing caregiver burnout.
  • See more here

Research Interests

Data Mining, High Performance Computing, Materials Informatics, Healthcare Informatics, Social Media Analytics.

Education

Professional Experience

  • Research Associate Professor, Northwestern University, Mar. 2013 - present.
  • Research Assistant Professor, Northwestern University, Sep. 2010 - Feb. 2013.
  • Postdoctoral Fellow, Northwestern University, Sep. 2009 - Aug. 2010.
  • Research Assistant, Iowa State University, Jan. 2007 - Aug. 2009.

Research Grants

  1. Senior Personnel, “BD Spokes: SPOKE: MIDWEST: Collaborative: Integrative Materials Design (IMaD): Leverage, Innovate, & Disseminate”, National Science Foundation (NSF), $123,847 (Total $989,700), 2017-2020. [IIS-1636909]

  2. PI, “Social Media mining of caregiver experiences: Opportunity for preventing caregiver burnout”, Northwestern Data Science Initiative, $25,000, 2017-2017.

  3. PI, “Data-driven analytics for understanding processing-structure-property-performance relationships in steel alloys”, Northwestern Data Science Initiative, $45,000, 2016-2017. [DSI]

  4. Co-PI, “Scaling up the screening of molecular networks in the rational design of optically active materials”, Northwestern Data Science Initiative, $9,000 (Total $45,000), 2016-2017.

  5. PI, “Analyzing caregiving experience on Twitter”, Feinberg School of Medicine, $14,246, 2015-2016.

  6. Co-PI, “SIMPLEX: Data-driven Discovery of Novel Thermoelectric Materials”, Defense Advanced Research Projects Agency (DARPA), $601,250 (Total $1,559,999), 2015-2018. [N66001-15-C-4036]

  7. Co-PI, “Scalable, In-situ Clustering and Data Analysis for Extreme Scale Scientific Computing”, Department of Energy (DOE), $1,219,899, 2015-2018. [DE-SC0014330]

  8. Co-PI, “SHF:Medium:Collaborative Research: Scalable Algorithms for Spatio-temporal Data Analysis”, National Science Foundation (NSF), $709,342 (Total $934,342), 2014-2018. [CCF-1409601]

  9. PI, “Advanced Materials Center for Excellence: Center for Hierarchical Materials Design (CHiMaD)”, National Institute of Standards and Technology (NIST), $450,000 (Total $25,000,000), 2014-2018. [70NANB14H012]

  10. Co-PI, “EAGER: Scalable Big Data Analytics”, National Science Foundation (NSF), $300,000, 2013-2016. [IIS-1343639]

  11. Co-PI, “MURI: MANAGING THE MOSAIC OF MICROSTRUCTURE: Image analysis, data structures, mathematical theory of microstructure, and hardware for the structure-property relationship”, Air Force Office of Scientific Research (AFOSR), Department of Defense (DOD), $750,000 (Total $5,658,616), 2012-2017. [FA9550-12-1-0458]

  12. Northwestern Co-I, “Scalable Data Management, Analysis, and Visualization (SDAV) Institute”, Department of Energy (DOE), $750,000 (Total $25,000,000), 2012-2018. [DE-SC0007456]

  13. Senior Researcher, “Expeditions in Computing: Understanding Climate Change: A Data Driven Approach”, National Science Foundation (NSF), $900,000 (Total $10,000,000), 2010-2016. [CCF-1029166]

  14. Co-PI, “EAGER: Discovering Knowledge from Scientific Research Networks”, National Science Foundation (NSF), $256,000, 2011-2014. [ACI-1144061]

  15. Research Participant, “Scalable and Power Efficient Data Analytics for Hybrid Exascale Systems”, Department of Energy (DOE), $705,000, 2010-2014. [DE-SC0005340]

Selected Publications

  1. A. Agrawal and A. Choudhary, “Perspective: Materials informatics and big data: Realization of the ‘fourth paradigm’ of science in materials science,” APL Materials, vol. 4, no. 053208, pp. 1–10, 2016. [url] [bib]

    @article{AC16APLMat,
      author = {Agrawal, Ankit and Choudhary, Alok},
      title = {Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science},
      journal = {APL Materials},
      year = {2016},
      pages = {1-10},
      volume = {4},
      number = {053208}
    }
    
  2. R. Liu, A. Kumar, Z. Chen, A. Agrawal, V. Sundararaghavan, and A. Choudhary, “A Predictive Machine Learning Approach for Microstructure Optimization and Materials Design,” Nature Scientific Reports, vol. 5, no. 11551, 2015. [url] [bib]

    @article{LKC15,
      author = {Liu, Ruoqian and Kumar, Abhishek and Chen, Zhengzhang and Agrawal, Ankit and Sundararaghavan, Veera and Choudhary, Alok},
      title = {A Predictive Machine Learning Approach for Microstructure Optimization and Materials Design},
      journal = {Nature Scientific Reports},
      year = {2015},
      volume = {5},
      number = {11551}
    }
    
  3. A. Agrawal, P. D. Deshpande, A. Cecen, G. P. Basavarsu, A. N. Choudhary, and S. R. Kalidindi, “Exploration of data science techniques to predict fatigue strength of steel from composition and processing parameters,” Integrating Materials and Manufacturing Innovation, vol. 3, no. 8, pp. 1–19, 2014. [url] [bib]

    @article{ADC14,
      author = {Agrawal, Ankit and Deshpande, Parijat D and Cecen, Ahmet and Basavarsu, Gautham P and Choudhary, Alok N and Kalidindi, Surya R},
      title = {Exploration of data science techniques to predict fatigue strength of steel from composition and processing parameters},
      journal = {Integrating Materials and Manufacturing Innovation},
      year = {2014},
      pages = {1-19},
      volume = {3},
      number = {8}
    }
    
  4. B. Meredig, A. Agrawal, S. Kirklin, J. E. Saal, J. W. Doak, A. Thompson, K. Zhang, A. Choudhary, and C. Wolverton, “Combinatorial screening for new materials in unconstrained composition space with machine learning,” Physical Review B, vol. 89, no. 094104, pp. 1–7, 2014. BM and AA are co-first authors. [url] [bib]

    @article{MAK14,
      author = {Meredig, Bryce and Agrawal, Ankit and Kirklin, S and Saal, J E and Doak, J W and Thompson, A and Zhang, Kunpeng and Choudhary, Alok and Wolverton, Christopher},
      title = {Combinatorial screening for new materials in unconstrained composition space with machine learning},
      journal = {Physical Review B},
      year = {2014},
      number = {094104},
      volume = {89},
      pages = {1-7},
      note = {**BM and AA are co-first authors**}
    }
    
  5. J. S. Mathias, A. Agrawal, J. Feinglass, A. J. Cooper, D. W. Baker, and A. Choudhary, “Development of a 5 year life expectancy index in older adults using predictive mining of electronic health record data,” Journal of the American Medical Informatics Association, vol. 20, pp. e118–e124, 2013. JSM and AA are co-first authors. [url] [bib]

    @article{MAF13,
      title = {Development of a 5 year life expectancy index in older adults using predictive mining of electronic health record data},
      author = {Mathias, Jason Scott and Agrawal, Ankit and Feinglass, Joe and Cooper, Andrew J and Baker, David William and Choudhary, Alok},
      journal = {Journal of the American Medical Informatics Association},
      year = {2013},
      volume = {20},
      pages = {e118-e124},
      publisher = {BMJ Publishing Group Ltd},
      note = {**JSM and AA are co-first authors**}
    }
    
  6. M. Patwary, D. Palsetia, A. Agrawal, W.-keng Liao, F. Manne, and A. Choudhary, “Scalable Parallel OPTICS Data Clustering Using Graph Algorithmic Techniques,” in Proceedings of 25th International Conference on High Performance Computing, Networking, Storage and Analysis (Supercomputing, SC’13), 2013, pp. 1–12. Article No. 49. [url] [bib]

    @inproceedings{PPA13,
      author = {Patwary, Mostofa and Palsetia, Diana and Agrawal, Ankit and Liao, Wei-keng and Manne, Fredrik and Choudhary, Alok},
      title = {Scalable Parallel OPTICS Data Clustering Using Graph Algorithmic Techniques},
      booktitle = {Proceedings of 25th International Conference on High Performance Computing, Networking, Storage and Analysis (Supercomputing, SC'13)},
      year = {2013},
      note = {Article No. 49},
      pages = {1-12}
    }
    
  7. M. Patwary, D. Palsetia, A. Agrawal, W.-keng Liao, F. Manne, and A. Choudhary, “A new scalable parallel DBSCAN algorithm using the disjoint-set data structure,” in ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2012, pp. 1–11. Article No. 62. [url] [bib]

    @inproceedings{PPA12,
      title = {A new scalable parallel DBSCAN algorithm using the disjoint-set data structure},
      author = {Patwary, Mostofa and Palsetia, Diana and Agrawal, Ankit and Liao, Wei-keng and Manne, Fredrik and Choudhary, Alok},
      booktitle = {ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC)},
      pages = {1--11},
      year = {2012},
      note = {Article No. 62},
      organization = {IEEE}
    }
    
  8. A. Agrawal and X. Huang, “Pairwise Statistical Significance of Local Sequence Alignment Using Sequence-Specific and Position-Specific Substitution Matrices,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. 1, pp. 194–205, 2011. [url] [bib]

    @article{AH11,
      author = {Agrawal, Ankit and Huang, Xiaoqiu},
      title = {Pairwise Statistical Significance of Local Sequence Alignment Using Sequence-Specific and Position-Specific Substitution Matrices},
      journal = {IEEE/ACM Transactions on Computational Biology and Bioinformatics},
      publisher = {IEEE},
      volume = {8},
      number = {1},
      pages = {194--205},
      year = {2011}
    }
    
  9. A. Agrawal and X. Huang, “PSIBLAST_PairwiseStatSig: Reordering PSI-BLAST hits using pairwise statistical significance,” Bioinformatics, vol. 25, no. 8, pp. 1082–1083, 2009. [url] [bib]

    @article{AH09b,
      author = {Agrawal, Ankit and Huang, Xiaoqiu},
      title = {PSIBLAST_PairwiseStatSig: Reordering PSI-BLAST hits using pairwise statistical significance},
      journal = {Bioinformatics},
      volume = {25},
      number = {8},
      pages = {1082-1083},
      year = {2009},
      publisher = {Oxford Univ Press}
    }