CV

Education

• B.Tech in Mechanical Engineering, Indian Institute of Technology Madras, 2013
• Ph.D in Aerospace Engineering , Texas A&M University, 2019

Work experience

• Data Scientist
  • Amazon Web Services
  • Date: May 2020 -
• Data Scientist
  • TGS NOPEC Geophysical Company
  • Date: September 2019 - March 2020
• Data Scientist II
  • Anadarko Petroleum Corp
  • Date: June 2019 - September 2019
• Data Science Intern
  • Anadarko Petroleum Corp
  • Date: May 2018- August 2018

Skills

• Programming: Matlab,Python
• Machine Learning: ScikitLearn, TensorFlow, PySpark, Ray
• Cloud Platforms: AWS

Publications

Multiway continuous hidden Markov model‐based approach for fault detection and diagnosis

Sen, D., Raihan, D., & Chidambaram, M. Multiway continuous hidden Markov model based approach for fault detection and diagnosis. AIChE Journal. doi:10.1002/aic.14386.

A UKF-PF based hybrid estimation scheme for space object tracking

Raihan, D., Chakravorty, S. A UKF-PF based hybrid estimation scheme for space object tracking. Proceedings of AAS/AIAA Astrodynamics Specialist Conference 2015. Vail-Colorado.

Particle Gaussian Mixture Filters

D. Raihan and S. Chakravorty, "Particle Gaussian Mixture (PGM) filters," 2016 19th International Conference on Information Fusion (FUSION), Heidelberg, 2016, pp. 1369-1376.

An Unscented Kalman-Particle Hybrid Filter for Space Object Tracking

Raihan A. V, D., Chakravorty, S. An Unscented Kalman-Particle Hybrid Filter for Space Object Tracking. J of Astronaut Sci 65, 111–134 (2018). https://doi.org/10.1007/s40295-017-0114-8

Particle Gaussian Mixture Filters-I

Raihan, D., Chakravorty, S. Particle Gaussian Mixture Filters-I”, Automatica, https://doi.org/10.1016/j.automatica.2018.07.023

Particle Gaussian Mixture Filters-II

Raihan, D., Chakravorty, S. ”Particle Gaussian Mixture Filters-II”, Automatica, https://doi.org/10.1016/j.automatica.2018.07.024

Particle Gaussian Mixture Filters-II

D. Raihan and S. Chakravorty, "Particle Gaussian Mixture Filters-II," 2018 21st International Conference on Information Fusion (FUSION), Cambridge, 2018, pp. 1092-1099, doi: 10.23919/ICIF.2018.8455307

Parallel Markov Chain Monte Carlo for Sensor Scheduling

Raihan, D., Faber, W., Chakravorty, S., Hussein, I. ”Parallel Markov Chain Monte Carlo for Sensor Scheduling”, Proceedings of AAS/AIAA Astrodynamics Specialist Conference 2018. Snowbird-Utah.

Sensor Scheduling Under Action Dependent decision Making Epochs

D. Raihan, W. Faber, S. Chakravorty and I. I. Hussein, "Sensor Scheduling Under Action Dependent Decision-Making Epochs," 2019 22th International Conference on Information Fusion (FUSION), Ottawa, ON, Canada, 2019, pp. 1-7.

Particle Gaussian Mixture Filters: Application and Performance Evaluation

D. Raihan and S. Chakravorty, "Particle Gaussian Mixture Filters: Application and Performance Evaluation," 2019 22th International Conference on Information Fusion (FUSION), Ottawa, ON, Canada, 2019, pp. 1-8.

Bayesian Geosteering Using Sequential Monte Carlo Methods

Veettil, D. R. A., & Clark, K. (2020, February 1). Bayesian Geosteering Using Sequential Monte Carlo Methods. Society of Petrophysicists and Well-Log Analysts.

Talks

AAS/AIAA Astrodynamics Specialist Conference

August 13, 2015

Conference at Vail, Colorado, Vail, Colorado

Texas Systems Day

April 08, 2016

Poster at University of Texas, Austin, Austin TX, USA

International Conference on Information Fusion

July 07, 2016

Conference at Heidelberg, Germany, Heidelberg, Germany

Infosymbiotics/DDDAS conference

March 01, 2018

Poster at MIT, USA, Cambridge MA, USA

Texas Systems Day

April 05, 2019

Poster at Texas A&M University, USA, College Station TX, USA

Teaching

Introduction to Aerospace Computation (AERO 220)

Service and leadership

• Reviewer for IEEE Transactions on Signal Processing, Multidimensional Systems and Signal Pro- cessing, ASME Journal of Dynamic Systems, Measurement and Control, IEEE Access, Signal Processing (Elsevier), Journal of Franklin Institute and International conference on Information Fusion.