March 22, 2016 Read More →

Ankush Chakrabarty

 

Postdoctoral Fellow20160118_034801000_iOS

Harvard John A. Paulson School of Engineering and Applied Sciences,
Harvard University, Cambridge, MA 02138.

Research
  • Wearable Artificial Pancreas
  • Embedded Control
  • Model Predictive Control
  • Machine Learning
  • Optimization
  • State and Unknown Input Estimation
Recent Publications
  • Journal:
    1. A. Chakrabarty, S. Zavitsanou, F. J. Doyle III, E. Dassau, Event-Triggered Model Predictive Control For Embedded Artificial Pancreas Systems. Preprint available, IEEE Trans. Biomedical Engineering, May 2017.
    2. E. Dassau, E. Renard, J.E. Place, A. Farret, M.J. Pelletier, J. Lee, L.M. Huyett, A. Chakrabarty, F.J. Doyle III and H.C. Zisser, Intraperitoneal Insulin Delivery Provides Superior Glycemic Regulation to Subcutaneous Insulin Delivery in Model Predictive Control‐based Fully‐automated Artificial Pancreas in Patients with Type 1 Diabetes: A Pilot Study. Diabetes, Obesity, and Metabolism, 2017.
    3. O. Choudhury, A. Chakrabarty, S. J. Emrich, Highly Accurate and Efficient Data-Driven Methods For Genotype Imputation. Accepted, IEEE Transactions on Computational Biology and Bioinformatics, 2017.
    4. J. H. Abel, A. Chakrabarty, F. J. Doyle III, Nonlinear Model Predictive Control for Populations of Circadian Oscillators. Emerging Applications of Control and System Theory, 2017.
    5. A. Chakrabarty, M. Corless, G.T. Buzzard, S.H. Zak, A.E. Rundell, State and Unknown Input Observers for Nonlinear Systems with Bounded Exogenous Disturbances. IEEE Trans. Automatic Control, 2017.
    6. A. Chakrabarty, R. Ayoub, S.H. Zak, S. Sundaram, Delayed Unknown Input Observers For Discrete-Time Linear Systems With Guaranteed Performance. Systems and Control Letters, Vol. 103, pp. 9 – 15, 2017.
    7. S. Zavitsanou, A. Chakrabarty, E. Dassau, F. J. Doyle III, Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas. Processes 4(4), pp. 35, 2016.
    8. A. Chakrabarty, G.T. Buzzard, S.H. Zak, Output-Tracking Quantized Explicit Nonlinear Model Predictive Control Using Multi-Class Support Vector Machines. Preprint available, IEEE Trans. Industrial Electronics, December 2016, doi:10.1109/TIE.2016.2638401.
    9. A. Chakrabarty, G.T. Buzzard, F. Zhu, S.H. Zak, A.E. Rundell, Simultaneous Unknown Input And Sensor Noise Reconstruction For Nonlinear Systems With Boundary Layer Sliding Mode Observers. Under Review.
    10. S. C. Johnson, A. Chakrabarty, J. Hu, S.H. Zak, R.A. DeCarlo, Dual-Mode Robust Fault Estimation for Switched Linear Systems with State Jumps. Conditionally accepted, Nonlinear Analysis: Hybrid Systems.
    11. X. Li, F. Zhu, A. Chakrabarty, S.H. Zak, Non-Fragile Fault-Tolerant Fuzzy Observer-Based Controller Design for Nonlinear Systems. IEEE Trans. Fuzzy Systems, Vol 24 (6), pp. 1679 – 1689.
    12. A. Chakrabarty, V. Dinh, G.T. Buzzard, M. Corless, S.H. Zak, A.E. Rundell, Support Vector Machine Informed Explicit Nonlinear Model Predictive Control. IEEE Trans. Automatic Control, Vol 62 (1), pp. 135 — 148.
    13. N. Tomar, O. Choudhury, A. Chakrabarty, and R.K. De. An integrated pathway system modeling of Saccharomyces cerevisiae HOG pathway: a Petri net based approach. Molecular biology reports 40, no. 2: 1103-1125, 2013.
    14. A. Chakrabarty, H. Jain, and A. Chatterjee. Volterra kernel based face recognition using artificial bee colony optimization. Engineering Applications of Artificial Intelligence 26, no. 3: 1107-1114, 2013.
    15. A. Chakrabarty, S. Banerjee, S. Maity, and A. Chatterjee. Fuzzy model predictive control of non-linear processes using convolution models and foraging algorithms. Measurement 46, no. 4: 1616-1629, 2013.
    16. A. Chakrabarty, O. Choudhury, P. Sarkar, A. Paul, and D. Sarkar. Hyperspectral image classification incorporating bacterial foraging-optimized spectral weighting. Artificial Intelligence Research 1, no. 1: pp. 63, 2012.
    17. S. Banerjee, A. Chakrabarty, S. Maity, A. Chatterjee. Feedback linearizing indirect adaptive fuzzy control with foraging based on-line plant model estimation. Applied Soft Computing, 11(4), 3441-3450, 2011.

 

  • Conference:
    1. A. Chakrabarty, S. Zavitsanou, F. J. Doyle III, E. Dassau, Model Predictive Control with Event-Triggered Communication for an Embedded Artificial Pancreas, Accepted, IEEE Conference on Control Technology and Applications (CCTA), 2017.
    2. J. H. Abel, A. Chakrabarty, F. J. Doyle III, Nonlinear Model Predictive Control For Circadian Entrainment Using Small-Molecule Pharmaceuticals. Accepted, IFAC World Congress 2017.
    3. A. Chakrabarty, S. Zavitsanou, F. J. Doyle III, E. Dassau, Reducing Controller Updates Via Event-Triggered Model
      Predictive Control In An Embedded Artificial Pancreas. Accepted, American Control Conference, 2017.
    4. A. Raha, A. Chakrabarty, V. Raghunathan, G. T. Buzzard, Ultrafast Embedded Explicit Model Predictive Control for Nonlinear Systems. Accepted, American Control Conference, 2017.
    5. S. Zak, A. Chakrabarty, G. T. Buzzard, Unknown Input Estimation Using Sliding Mode Observers for Nonlinear Systems Characterized by Incremental Multiplier Matrices. Accepted, American Control Conference, 2017.
    6. A. Chakrabarty, G.T. Buzzard, E. Fridman, S.H. Zak, Unknown Input Estimation via Observers for Nonlinear Systems with Measurement Delays. IEEE Conference on Decision and Control, Las Vegas, NV, 2016, pp. 2308-2313.
    7. A. Chakrabarty, S.H. Zak, S. Sundaram, State and Exogenous Input Observers for Discrete-Time Nonlinear Systems. IEEE Conference on Decision and Control, Las Vegas, NV, 2016, pp. 7111 – 7116.
    8. H. Zhang, A. Chakrabarty, R. Ayoub, G.T. Buzzard, S. Sundaram, Sampling based Explicit Model Predictive Control for Tracking of Nonlinear Systems. IEEE Conference on Decision and Control, Las Vegas, NV, 2016, pp.4722 – 4727.
    9. O. Choudhury, A. Chakrabarty, S. J. Emrich, HAPI-Gen: Highly Accurate Phasing and Imputation of Genotype Data. Accepted, 7th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, October 2016, Seattle, WA.
    10. A. Chakrabarty, M.J. Corless, G.T. Buzzard, S.H. Zak, A.E. Rundell, Sufficient Conditions for Exogeneous Input Estimation In Nonlinear Systems. Proc. 2016 American Control Conference (ACC), Boston, MA, pp. 103–108.
    11. A. Chakrabarty, S. Sundaram, M. Corless, G.T. Buzzard, S.H. Zak, A.E. Rundell, Distributed Unknown Input Observers For Interconnected Nonlinear Systems: Application To Gene Regulatory Networks. Proc. 2016 American Control Conference (ACC), Boston, MA, pp. 2478–2483.
    12. A. Chakrabarty, G.T. Buzzard, M. Corless, S.H. Zak, A.E. Rundell, Correcting Hypothalamic-Pituitary-Adrenal Axis Dysfunction Using Observer-based Explicit Nonlinear Model Predictive Control. 36th Annual Conference IEEE EMBS 2014, Chicago, USA.
    13. A. Chakrabarty, V. Dinh, G.T. Buzzard, S.H. Zak, and A.E. Rundell. Robust explicit nonlinear model predictive control with integral sliding mode. In American Control Conference (ACC), 2014, Portland, USA, pp. 2851–2856.
    14. A. Chakrabarty, S.M. Pearce, R.P. Nelson, and A.E. Rundell. Treating acute myeloid leukemia via HSC transplantation: A preliminary study of multi-objective personalization strategies. In American Control Conference (ACC), 2013, Washington D.C., USA, pp. 3790–3795.
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