By Professor Daoyi Dong

Conference Papers

Wolkowicz MD; Smith JA; Dong D; Dagli SS, 1997, 'Reactor chemistry & microstructure of polypropylene grafts', in ANTEC'97 - PLASTICS SAVING PLANET EARTH, CONFERENCE PROCEEDINGS, VOLS 1 - 3, SOC PLASTICS ENGINEERS, CANADA, TORONTO, pp. 1664 - 1670, presented at 55th Annual Technical Conference of the Society-of-Plastics-Engineers - Plastics Saving Planet Earth (ANTEC 97), CANADA, TORONTO, 27 April 1997 - 02 May 1997

DeMaio VV; Dong D, 1997, 'The effect of chain structure on melt strength of polypropylene and polyethylene', in ANTEC'97 - PLASTICS SAVING PLANET EARTH, CONFERENCE PROCEEDINGS, VOLS 1 - 3, SOC PLASTICS ENGINEERS, CANADA, TORONTO, pp. 1512 - 1516, presented at 55th Annual Technical Conference of the Society-of-Plastics-Engineers - Plastics Saving Planet Earth (ANTEC 97), CANADA, TORONTO, 27 April 1997 - 02 May 1997

Gelbard G; Sherrington DC; Breton F; Benelmoudeni M; Charreyre MT; Dong D, 1994, 'Polymers with ligated peroxotungstic units: Organophosphoryl macroligands for the catalytic epoxidation of alkenes.', in Pittman CU; Carraher CE; Zeldin M; Sheats JE; Culbertson BM (eds.), METAL-CONTAINING POLYMERIC MATERIALS, PLENUM PRESS DIV PLENUM PUBLISHING CORP, DC, WASHINGTON, pp. 265 - 275, presented at International Symposium on Metal-Containing Polymeric Materials, at the 208th National American-Chemical-Society Meeting, DC, WASHINGTON, 20 August 1994 - 25 August 1994

GELBARD G; BRETON F; CHARREYRE MT; DONG D, 1991, 'POLYPYRIDINE-BASED CATALYSTS - EPOXIDATION OF OLEFINS WITH SUPPORTED PEROXOTUNGSTIC COMPLEXES', in MAKROMOLEKULARE CHEMIE-MACROMOLECULAR SYMPOSIA, HUTHIG & WEPF VERLAG, ITALY, SIENA, pp. 353 - 361, presented at 4TH INTERNATIONAL SYMP ON MACROMOLECULAR METAL COMPLEXES, ITALY, SIENA, 30 September 1991 - 05 October 1991, http://dx.doi.org/10.1002/masy.19920590129

Conference Abstracts

Zhu Y; Tian F; Dong D; Young J; Lai J, 2018, 'Study of fish self- adapting behaviour in Karman vortex street using reinforcement learning', in The 13th World Congress in Computational Mechanics, presented at The 13th World Congress in Computational Mechanics, 22 July 2018 - 27 July 2018

Reports

Dong D, 2020, Quantum Cybernetics Technical Committee Reports: Investigating the Role of Quantum Effects in Regulating Quantum and Classical Systems, IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, http://dx.doi.org/10.1109/MSMC.2019.2952458, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000528940200005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1

Dong D; Shi G; Vuglar S; James MR, 2017, Special issue on quantum control Dedicated to the occasion of Prof. Ian Petersen’s 60th birthday, Springer Nature, http://dx.doi.org/10.1007/s11768-017-6200-4

Preprints

Xiao S; Liang W; Wang Y; Dong D; Petersen IR; Ugrinovskii V, 2025, Simultaneous estimations of quantum state and detector through multiple quantum processes, http://dx.doi.org/10.48550/arxiv.2502.11772

Hong Q-Q; Dong D; Henriksen NE; Nori F; He J; Shu C-C, 2025, Precise Quantum Control of Molecular Rotation Toward a Desired Orientation, http://dx.doi.org/10.48550/arxiv.2502.10196

Selim A; Mo H; Pota H; Dong D, 2024, Adaptive BESS and Grid Setpoints Optimization: A Model-Free Framework for Efficient Battery Management under Dynamic Tariff Pricing, http://dx.doi.org/10.48550/arxiv.2408.09989

Liu Y-H; Zeng Y; Tan Q-S; Dong D; Nori F; Liao J-Q, 2024, Optimal control of linear Gaussian quantum systems via quantum learning control, http://dx.doi.org/10.48550/arxiv.2406.05597

Wang Y; Wang X; Qi B; Dong D, 2024, Supervised Learning Guarantee for Quantum AdaBoost, http://dx.doi.org/10.48550/arxiv.2402.02376

Ma H; Mooney GJ; Petersen IR; Hollenberg LCL; Dong D, 2023, Quantum autoencoders using mixed reference states, http://dx.doi.org/10.48550/arxiv.2309.15582

Liu Y; Dong D; Petersen IR; Yonezaw H, 2023, Fault-tolerant $H^\infty$ control for optical parametric oscillators with pumping fluctuations, http://dx.doi.org/10.48550/arxiv.2307.14583

Liu Y; Dong D; Kuang S; Petersen IR; Yonezawa H, 2023, Two-step feedback preparation of entanglement for qubit systems with time delay, http://dx.doi.org/10.48550/arxiv.2307.14599

Bao L; Qi B; Nori F; Dong D, 2023, Exponential sensitivity revival of noisy non-Hermitian quantum sensing with two-photon drives, http://dx.doi.org/10.48550/arxiv.2303.16575

Wang Y; Qi B; Ferrie C; Dong D, 2023, Trainability Enhancement of Parameterized Quantum Circuits via Reduced-Domain Parameter Initialization, http://dx.doi.org/10.48550/arxiv.2302.06858

Shindi O; Yu Q; Girdhar P; Dong D, 2023, Model-free Quantum Gate Design and Calibration using Deep Reinforcement Learning, http://dx.doi.org/10.48550/arxiv.2302.02371

Fan L-B; Shu C-C; Dong D; He J; Henriksen NE; Nori F, 2022, Quantum Coherent Control of a Single Molecular-Polariton Rotation, http://dx.doi.org/10.48550/arxiv.2212.11649

Jiang C; Pan Y; Wu Z-G; Gao Q; Dong D, 2022, Robust optimization for quantum reinforcement learning control using partial observations, http://dx.doi.org/10.48550/arxiv.2206.14420

Wang Z; Chen C; Dong D, 2022, A Dirichlet Process Mixture of Robust Task Models for Scalable Lifelong Reinforcement Learning, http://dx.doi.org/10.48550/arxiv.2205.10787

Liu J; Wang Z; Chen C; Dong D, 2022, Efficient Bayesian Policy Reuse with a Scalable Observation Model in Deep Reinforcement Learning, http://dx.doi.org/10.48550/arxiv.2204.07729

Xie D; Wang Z; Chen C; Dong D, 2022, Depthwise Convolution for Multi-Agent Communication with Enhanced Mean-Field Approximation, http://dx.doi.org/10.48550/arxiv.2203.02896

Dong D; Petersen IR, 2022, Quantum estimation, control and learning: opportunities and challenges, http://dx.doi.org/10.48550/arxiv.2201.05835

Ma H; Dong D; Petersen IR; Huang C-J; Xiang G-Y, 2021, Neural networks for quantum state tomography with constrained measurements, http://dx.doi.org/10.48550/arxiv.2111.09504

Bao L; Qi B; Dong D, 2021, Exponentially-enhanced Quantum Non-Hermitian Sensing via Optimized Coherent Drive, http://dx.doi.org/10.48550/arxiv.2109.04040

Li Y; Aghvami AH; Dong D, 2021, Path Planning for Cellular-Connected UAV: A DRL Solution with Quantum-Inspired Experience Replay, http://dx.doi.org/10.48550/arxiv.2108.13184

Chen Y; Pan Y; Dong D, 2021, Residual Tensor Train: A Quantum-inspired Approach for Learning Multiple Multilinear Correlations, http://dx.doi.org/10.48550/arxiv.2108.08659

Bao L; Qi B; Dong D; Nori F, 2021, Fundamental limits for reciprocal and non-reciprocal non-Hermitian quantum sensing, http://dx.doi.org/10.48550/arxiv.2104.10822

Dong D, 2021, Learning Control of Quantum Systems, http://dx.doi.org/10.48550/arxiv.2101.07461

Ma H; Dong D; Ding SX; Chen C, 2020, Curriculum-based Deep Reinforcement Learning for Quantum Control, http://dx.doi.org/10.48550/arxiv.2012.15427

Wang Z; Chen C; Dong D, 2020, Instance Weighted Incremental Evolution Strategies for Reinforcement Learning in Dynamic Environments, http://dx.doi.org/10.48550/arxiv.2010.04605

Chen Y; Pan Y; Dong D, 2020, Quantum Language Model with Entanglement Embedding for Question Answering, http://dx.doi.org/10.48550/arxiv.2008.09943

Wang Z; Chen C; Dong D, 2020, Lifelong Incremental Reinforcement Learning with Online Bayesian Inference, http://dx.doi.org/10.48550/arxiv.2007.14196

Li Y; Aghvami AH; Dong D, 2020, Intelligent Trajectory Planning in UAV-mounted Wireless Networks: A Quantum-Inspired Reinforcement Learning Perspective, http://dx.doi.org/10.48550/arxiv.2007.13418

Dong D; Shu C-C; Chen J; Xing X; Ma H; Guo Y; Rabitz H, 2020, Learning control of quantum systems using frequency-domain optimization algorithms, http://dx.doi.org/10.48550/arxiv.2005.13080

Ma H; Huang C-J; Chen C; Dong D; Wang Y; Wu R-B; Xiang G-Y, 2020, On compression rate of quantum autoencoders: Control design, numerical and experimental realization, http://dx.doi.org/10.48550/arxiv.2005.11149

Yu Q; Wang Y; Dong D; Petersen IR; Xiang G-Y, 2020, Generation of accessible sets in the dynamical modelling of quantum network systems, http://dx.doi.org/10.48550/arxiv.2004.14663

Yu Q; Dong D; Petersen IR, 2020, Hybrid filtering for a class of nonlinear quantum systems subject to classical stochastic disturbances, http://dx.doi.org/10.48550/arxiv.2004.07050

Yu Q; Wang Y; Dong D; Petersen IR, 2020, On the capability of a class of quantum sensors, http://dx.doi.org/10.48550/arxiv.2003.08679

Wang Y; Yokoyama S; Dong D; Petersen IR; Huntington EH; Yonezawa H, 2019, Two-stage Estimation for Quantum Detector Tomography: Error Analysis, Numerical and Experimental Results, http://dx.doi.org/10.48550/arxiv.1905.05323

Tan L; Dong D; Li D; Xue S, 2019, Quantum Hamiltonian Identification with Classical Colored Measurement Noise, http://dx.doi.org/10.48550/arxiv.1905.01625

Huang C-J; Ma H; Yin Q; Tang J-F; Dong D; Chen C; Xiang G-Y; Li C-F; Guo G-C, 2019, Realization of a quantum autoencoder for lossless compression of quantum data, http://dx.doi.org/10.48550/arxiv.1903.08699

Wu K-D; Hou Z; Xiang G-Y; Li C-F; Guo G-C; Dong D; Nori F, 2019, Detecting Non-Markovianity via Quantified Coherence: Theory and Experiments, http://dx.doi.org/10.48550/arxiv.1903.03359

Zhang S; Liu K; Dong D; Feng X; Pan F, 2019, Subspace Stabilization Analysis for Non-Markovian Open Quantum Systems, http://dx.doi.org/10.48550/arxiv.1901.10088

Wu R-B; Ding H; Dong D; Wang X, 2018, Learning Robust and High-Precision Quantum Controls, http://dx.doi.org/10.48550/arxiv.1811.01884

Wang Y; Dong D; Sone A; Petersen IR; Yonezawa H; Cappellaro P, 2018, Quantum Hamiltonian Identifiability via a Similarity Transformation Approach and Beyond, http://dx.doi.org/10.48550/arxiv.1809.02965

Chen C; Dong D; Li H-X; Chu J; Tarn T-J, 2018, Fidelity-based Probabilistic Q-learning for Control of Quantum Systems, http://dx.doi.org/10.48550/arxiv.1806.03145

Shu C-C; Yuan K-J; Dong D; Petersen IR; Bandrauk AD, 2018, Identifying Strong-Field Effects in Indirect Photofragmentation Reactions, http://dx.doi.org/10.48550/arxiv.1806.04078

Wu C; Qi B; Chen C; Dong D, 2018, Robust Learning Control Design for Quantum Unitary Transformations, http://dx.doi.org/10.48550/arxiv.1806.02140

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