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2020 – today
- 2023
[j13]Mengsha Yao, Susan E. Luczak, I. Gary Rosen:
Tracking and blind deconvolution of blood alcohol concentration from transdermal alcohol biosensor data: A population model-based LQG approach in Hilbert space. Autom. 147: 110699 (2023)- [j12]Clemens Oszkinat
, Susan E. Luczak, I. G. Rosen:
Uncertainty Quantification in Estimating Blood Alcohol Concentration From Transdermal Alcohol Level With Physics-Informed Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 34(10): 8094-8101 (2023) - [c13]Maria Allayioti, Clemens Oszkinat, Emily Saldich, Larry Goldstein, Susan E. Luczak, Chunming Wang, I. G. Rosen:
Parametric and Non-Parametric Estimation of a Random Diffusion Equation-Based Population Model for Deconvolving Blood/Breath Alcohol Concentration from Transdermal Alcohol Biosensor Data with Uncertainty Quantification*. ACC 2023: 313-318 - [c12]Haoxing Liu, Larry Goldstein, Susan E. Luczak, I. G. Rosen:
Delta-Method Induced Confidence Bands for a Parameter-Dependent Evolution System with Application to Transdermal Alcohol Concentration Monitoring. CDC 2023: 6211-6216 - 2022
- [j11]Clemens Oszkinat, Susan E. Luczak, I. Gary Rosen:
An abstract parabolic system-based physics-informed long short-term memory network for estimating breath alcohol concentration from transdermal alcohol biosensor data. Neural Comput. Appl. 34(21): 18933-18951 (2022) - [c11]Clemens Oszkinat, Susan E. Luczak, I. G. Rosen:
Physics-Informed Learning: Distributed Parameter Systems, Hidden Markov Models, and the Viterbi Algorithm. ACC 2022: 266-271 - 2021
- [c10]Mengsha Yao, Susan E. Luczak, I. G. Rosen:
Linear Quadratic Gaussian Control of Random Abstract Parabolic Systems. CDC 2021: 3306-3311
2010 – 2019
- 2019
- [j10]Melike Sirlanci, Susan E. Luczak, Catharine E. Fairbairn, Dahyeon Kang, Ruoxi Pan, Xin Yu, I. Gary Rosen:
Estimating the distribution of random parameters in a diffusion equation forward model for a transdermal alcohol biosensor. Autom. 106: 101-109 (2019) - [j9]Asif Zubair, I. Gary Rosen, Sergey V. Nuzhdin, Paul Marjoram:
Bayesian model selection for the Drosophila gap gene network. BMC Bioinform. 20(1): 327:1-327:12 (2019) - 2017
- [c9]Melike Sirlanci, Susan E. Luczak, I. Gary Rosen:
Approximation and convergence in the estimation of random parameters in linear holomorphic semigroups generated by regularly dissipative operators. ACC 2017: 3171-3176 - 2014
- [j8]I. Gary Rosen, Susan E. Luczak, Jordan Weiss:
Blind deconvolution for distributed parameter systems with unbounded input and output and determining blood alcohol concentration from transdermal biosensor data. Appl. Math. Comput. 231: 357-376 (2014) - [c8]I. Gary Rosen, Chunming Wang, Weiwei Hu, Michael Hankin, Rongjie Lai, Mark E. Thompson, Stephen R. Forrest:
Estimation of parameters in a distributed parameter model for thin film layered organic photovoltaic cells. ACC 2014: 1039-1044 - 2013
- [c7]Susan E. Luczak, I. Gary Rosen, Jordan Weiss:
Determining blood and/or breath alcohol concentration from transdermal alcohol data. ACC 2013: 473-478 - [c6]I. Gary Rosen, Susan E. Luczak, Weiwei Hu, Michael Hankin:
Discrete-Time Blind Deconvolution for Distributed Parameter Systems with Dirichlet Boundary Input and Unbounded Output with Application to a Transdermal Alcohol Biosensor. SIAM Conf. on Control and its Applications 2013: 160-167 - 2010
- [j7]Anthony F. J. Levi, I. G. Rosen:
A Novel Formulation of the Adjoint Method in the Optimal Design of Quantum Electronic Devices. SIAM J. Control. Optim. 48(5): 3191-3223 (2010)
2000 – 2009
- 2008
- [j6]Miguel A. Dumett, I. G. Rosen, J. Sabat, A. Shaman, L. Tempelman, Chunming Wang, R. M. Swift:
Deconvolving an estimate of breath measured blood alcohol concentration from biosensor collected transdermal ethanol data. Appl. Math. Comput. 196(2): 724-743 (2008) - 2005
- [c5]Michael A. Demetriou, I. G. Rosen:
Unknown Input Observers for a class of distributed parameter systems. CDC/ECC 2005: 3874-3879 - 2002
- [j5]Anupam Madhukar, Tyler Parent, I. Gary Rosen, Chunming Wang:
An Elementary Model for Control of a Semiconductor Etching Process. SIAM Rev. 44(4): 678-695 (2002) - [j4]I. G. Rosen, Tyler Parent, Baris Fidan, Chunming Wang, Anupam Madhukar:
Design, development, and testing of real-time feedback controllers for semiconductor etching processes using in situ spectroscopic ellipsometry sensing. IEEE Trans. Control. Syst. Technol. 10(1): 64-75 (2002) - [c4]Michael A. Demetriou, I. G. Rosen:
Variable structure model reference adaptive control of parabolic distributed parameter systems. ACC 2002: 4371-4376 - 2001
- [j3]I. Gary Rosen, Tyler Parent, Carolyn Cooper, Ping Chen, Anupam Madhukar:
A neural-network-based approach to determining a robust process recipe for the plasma-enhanced deposition of silicon nitride thin films. IEEE Trans. Control. Syst. Technol. 9(2): 271-284 (2001) - [c3]Baris Fidan, I. G. Rosen, Tyler Parent, Anupam Madhukar:
Multi-variable adaptive control of CF4/O2 plasma etching of silicon nitride thin films. ACC 2001: 1280-1285 - [c2]I. Gary Rosen, Color Wang, George Hajj, Xingcan Pi, Brian Wilson:
An adjoint method based approach to data assimilation for a distributed parameter model for the ionosphere. CDC 2001: 4406-4408 - 2000
- [c1]Baris Fidan, Tyler Parent, I. G. Rosen, Anupam Madhukar:
Spectroscopic ellipsometry (SE) based real-time control of CF4 /O2 plasma etching of silicon nitride. ACC 2000: 4006-4010
1990 – 1999
- 1994
- [j2]Michael A. Demetriou, I. Gary Rosen:
On the persistence of excitation in the adaptive estimation of distributed parameter systems. IEEE Trans. Autom. Control. 39(5): 1117-1123 (1994)
1980 – 1989
- 1988
- [j1]J. S. Gibson, I. G. Rosen:
Approximation of discrete-time LQG compensators for distributed systems with boundary input and unbounded measurement. Autom. 24(4): 517-529 (1988)
Coauthor Index
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