Emil Laftchiev

Emil Laftchiev
  • Biography

    Emil's research interests are in the identification of efficient storage methods using dimension reducing data features. The purpose of this research is to enable rapid continuous localization within the data. Of particular importance to this research is the effect of various uncertainties on the stored data features and on the localization process. Emil has received several speaking awards for presenting his research at the American Control Conference and the College of Engineering Research Symposium at the Pennsylvania State University. Prior to joining MERL Emil served as a Distinguished Teaching Fellow for the College of Engineering at the Pennsylvania State University.

  • Internships with Emil

    • DA1172: Active Learning For Physiological Modeling

      The Data Analytics Group at MERL is seeking a highly motivated, qualified individual to join our internship program in the summer of 2018. The ideal candidate is expected to have a strong background in machine learning with experience and background in active learning. Preferred candidates will also have a background in transfer learning. The candidate is expected to have strong programming skills in Python with experience using pandas, scikit-learn and scipy. Exceptional candidates will also have some Android development experience. Candidates who hold a PhD or in their senior years of a Ph.D. program are encouraged to apply.

    • DA1173: Time Series Pattern Matching and Discovery

      The Data Analytics Group at MERL is seeking a highly motivated, qualified individual to join our internship program in the summer of 2018. The ideal candidate is expected to have a strong background in time series analytics with experience in subsequence matching, feature representation, matching distance development. Preferred candidates will have a background either time series subsequence matching or in time series pattern discovery. The candidate is expected to have strong programming skills in an industrial programming language like C/C++, and a scripting language like Python or Matlab. Candidates who hold a PhD or in their senior years of a Ph.D. program are encouraged to apply.

    See All Internships at MERL
  • MERL Publications

  • Other Publications

    •  Laftchiev, E.I.; Lagoa, C.M.; Brennan, S.N., "Vehicle Localization Using In-Vehicle Pitch Data and Dynamical Models", Intelligent Transportation Systems, IEEE Transactions on, Vol. 16, No. 1, pp. 206-220, Feb 2015.
      BibTeX
      • @Article{6863698,
      • author = {Laftchiev, E.I. and Lagoa, C.M. and Brennan, S.N.},
      • title = {Vehicle Localization Using In-Vehicle Pitch Data and Dynamical Models},
      • journal = {Intelligent Transportation Systems, IEEE Transactions on},
      • year = 2015,
      • volume = 16,
      • number = 1,
      • pages = {206--220},
      • month = {Feb}
      • }
    •  Laftchiev, E.; Lagoa, C.; Brennan, S., "Robust data map design using chance constrained optimization", American Control Conference (ACC), 2014, June 2014, pp. 4573-4580.
      BibTeX
      • @Inproceedings{6858839,
      • author = {Laftchiev, E. and Lagoa, C. and Brennan, S.},
      • title = {Robust data map design using chance constrained optimization},
      • booktitle = {American Control Conference (ACC), 2014},
      • year = 2014,
      • pages = {4573--4580},
      • month = jun
      • }
    •  Laftchiev, E.; Lagoa, C.; Brennan, S., "Multi-attribute data dynamics discontinuity identification: A probabilistic approach using linear modeling", Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on, Dec 2014, pp. 5666-5673.
      BibTeX
      • @Inproceedings{7040276,
      • author = {Laftchiev, E. and Lagoa, C. and Brennan, S.},
      • title = {Multi-attribute data dynamics discontinuity identification: A probabilistic approach using linear modeling},
      • booktitle = {Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on},
      • year = 2014,
      • pages = {5666--5673},
      • month = {Dec}
      • }
    •  Laftchiev, E.; Lagoa, C.; Brennan, S., "Robust map design by outlier point selection for terrain-based vehicle localization", Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on, Dec 2013, pp. 2822-2827.
      BibTeX
      • @Inproceedings{6760311,
      • author = {Laftchiev, E. and Lagoa, C. and Brennan, S.},
      • title = {Robust map design by outlier point selection for terrain-based vehicle localization},
      • booktitle = {Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on},
      • year = 2013,
      • pages = {2822--2827},
      • month = {Dec}
      • }
    •  Laftchiev, E.; Lagoa, C.; Brennan, S., "Terrain-based vehicle localization from real-time data using dynamical models", Decision and Control (CDC), 2012 IEEE 51st Annual Conference on, Dec 2012, pp. 3366-3371.
      BibTeX
      • @Inproceedings{6426351,
      • author = {Laftchiev, E. and Lagoa, C. and Brennan, S.},
      • title = {Terrain-based vehicle localization from real-time data using dynamical models},
      • booktitle = {Decision and Control (CDC), 2012 IEEE 51st Annual Conference on},
      • year = 2012,
      • pages = {3366--3371},
      • month = {Dec}
      • }
  • Videos