Publications

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Papers published or accepted in 2020-2022

 

Niloufar Daemi, Juan S. Borrero, and Balabhaskar Balasundaram. Interdicting low-diameter cohesive subgroups in large-scale social networks. INFORMS Journal on Optimization, February 2022 DOI:10.1287/ijoo.2021.0068. 

 

B. Balasundaram, J.S. Borrero, H. Pan, Graph Signatures: Identification and Optimization. European Journal of Operational Research, 296(3):764–775, February 2022.

 

B. Farmanesh, A. Pourhabib, B. Balasundaram, and A. Buchanan. A Bayesian framework for functional calibration of expensive computational models through non-isometric matching. IISE Transactions, 53(3):352–364, March 2021.

 

Z. Miao and B. Balasundaram. An ellipsoidal bounding scheme for the quasi-clique number of a graph. INFORMS Journal on Computing, 32(3):763–778, August 2020.

 

F. Nasirian, F. M. Pajouh, and B. Balasundaram. Detecting a most closeness-central clique in complex networks. European Journal of Operational Research. 283(2):461-475, June 2020.

 

J. Yang, J.S. Borrero, O.A. Prokopyev, D. Saure, "Sequential Shortest Path Interdiction with Incomplete Information and Limited Feedback," Decision Analysis (2021). Forthcoming.

 

J.S. Borrero, L. Lozano, "Modeling Defender-Attacker Problems as Robust Linear Programs with Mixed-integer Uncertainty Sets," INFORMS Journal on Computing, Vol. 33, No. 4 (2021). 

 

J.S. Borrero, M. Akhgar, P. Krokhmal, "A Scalable Markov Chain Framework for Influence Maximization in Arbitrary Networks," IEEE Transactions on Network Science and Engineering, Vol. 8, No. 3 (2021).

 

J.S. Borrero, O. A. Prokopyev, D. Saure. Learning in Sequential Bilevel Linear Programming. INFORMS Journal on Optimization (2021). Forthcoming.

 

J.L. Walteros, A. Buchanan. Why is maximum clique often easy in practice? Operations Research, 68(6): 1866-1895, 2020. 

 

H. Validi, A. Buchanan. Political districting to minimize cut edges. To appear at Mathematical Programming Computation.

 

M.J. Naderi, A. Buchanan, J.L. Walteros. Worst-case analysis of clique MIPs. To appear at Mathematical Programming. 

 

H. Salemi, A. Buchanan. Solving the distance-based critical node problem. To appear at INFORMS Journal on Computing.

  

H. Validi, A. Buchanan, E. Lykhovyd. Imposing contiguity constraints in political districting models. Operations Research. 70(2): 867-892, 2022.

  

V. Stozhkov, A. Buchanan, S. Butenko, V. Boginski. Continuous cubic formulations for cluster detection problems in networks. To appear at Mathematical Programming.

  

H. Salemi and A. Buchanan. Parsimonius formulations for low-diameter clusters. Mathematical Programming Computation. 12(3): 493-528, 2020.

  

H. Validi, A. Buchanan. The optimal design of low-latency virtual backbones. INFORMS Journal on Computing. Accepted for Publication.

  

T. van de Kracht and S.S. Heragu. Lessons from Modeling and Running the World’s Largest Drive-Through, Mass Vaccination Clinic. INFORMS Journal of Applied Analytics, Vol. 51, No. 2, pp. 91-105, March-April 2021.

  

F. Majzoubi, L. Bai, and S.S. Heragu, The EMS Vehicle Transportation Problem During a Demand Surge. Journal of Global Optimization, Vol. 79, No. 4, pp. 989-1006, 2021.

 
K. A. Jurewicz, D. M. Neyens, K. Catchpole, A. Joseph, S. T. Reeves, J. H. Abernathy III. An observational study of anaesthesia workflow to evaluate physical workspace design and layout. British Journal of Anesthesia. Accepted, 2020.

 

C. Liu, W. Tian, and C. Kan. When AI Meets Additive Manufacturing: Challenges and Emerging Opportunities for Human-Centered Products Development. Journal of Manufacturing Systems. 2022. Accepted for publication

 
 Liu, R. Wang, I. Ho, Z. Kong, C. Williams, S. Babu, and C. Joslin. Toward Online Layer-wise Surface Morphology Measurement in Additive Manufacturing Using a Deep Learning-based Approach. Journal of Intelligent Manufacturing. 2022. Accepted for Publication.

 

 

Y. Chen,  A. Abu-Heiba, S. Kassaee, C. Liu, G. Liu, M. Starke, B. Smith, and A. Momen. Coupled Heat-Power Operation of Smart Buildings via Modular Pumped Hydro Storage. ASME Journal of Energy Resources Technology. 2022. Accepted for Publication.

 

A. Mamun, C. Liu, C. Kan, and W. Tian. Securing cyber-physical additive manufacturing systems by in-situ process authentication using streamline video analysis. Journal of Manufacturing Systems. 62: 429-440, 2022.

  

Y. Li, Z. Shi, C. Liu, W. Tian, Z. Kong, and C. Williams. Augmented Time Regularized Generative Adversarial Network (ATR-GAN) for Data Augmentation in Online Process Anomaly Detection. IEEE Transactions on Automation Science and Engineering, 2022. Accepted for publication.

 

Z. Shi, A. Mamun, C. Kan, W. Tian, and C. Liu. An LSTM-Autoencoder Based Online Side Channel Monitoring Approach for Cyber-Physical Attack Detection in Additive Manufacturing. Journal of Intelligent Manufacturing. 2022. Accepted for Publication.

 

Y. Li, J. VanOsdol, A. Ranjan, and C. Liu. A Multilayer Network-Enabled Ultrasonic Image Series Analysis Approach for Online Cancer Drug Delivery Monitoring. Computer Methods and Programs in Biomedicine. 213: 106505, 2022.

 

Z. Ye, C. Liu, W. Tian, and C. Kan. In-situ Point Cloud Fusion for Layer-wise Monitoring of Additive Manufacturing. Journal of Manufacturing Systems. Vol.61 pp.210-222, 2021.

  

Z. Shi, C. Kan, W. Tian, and C. Liu. A Blockchain-based G-code Protection Approach for Cyber-Physical Security in Additive Manufacturing. ASME Journal of Computing and Information Science in Engineering, 21(4): 041007, 2021.

  

C. Liu, Z. Kong, S. Babu, C. Joslin, and J. Ferguson. An Integrated Manifold Learning Approach for High Dimensional Data Feature Extractions and its Applications to Online Process Monitoring of Additive Manufacturing. IISE Transactions. 53(11), 1215-1230, 2021.

 

Krishnan, D.R., T. Liu. 2022. A Branch-and-cut Algorithm for Pickup-and-delivery Traveling Salesman Problem with Handling Costs. Accepted at Networks.  

  

A. Gupta, T. Liu, C. Crick. Utilizing Time Series Data Embedded in Electronic Health Records to Develop Continuous Mortality Risk Prediction Models using Hidden Markov Models: A Sepsis Case Study. Statistical Methods in Medical Research, 29(11): 3409-3423, 2020.

  

S. Hariharan, T. Liu, M. Z. Shen. Role of Resource Flexibility and Responsive Pricing in Mitigating the Uncertainties in Production Systems. European Journal of Operational Research, 284(2), 498-513, 2020.

  

J. K. Nuamah, Y. Seong, S. Jiang, E. Park, & D. Mountjoy. Evaluating effectiveness of information visualizations using cognitive fit theory: A neuroergonomics approach. Applied Ergonomics, 88, 103173, 2020.

 
L. M. Mazur, R. Adams, P. R. Mosaly, M. P. Stiegler, J. K. Nuamah, K. Adapa, ... & L.B. Marks. Impact of simulation-based training on radiation therapy therapists workload, situation awareness, and performance. Advances in Radiation Oncology, 2020.

 

J. K. Nuamah, P. R. Mosaly, R. Adams, K. Adapa, B. S. Chera, L. B. Marks, & L. M. Mazur. Assessment of Radiation Therapy Technologists’ Workload and Situation Awareness: Monitoring 2 Versus 3 Collocated Display Monitors. Advances in Radiation Oncology, 2020.

  

L. M. Mazur, R. Adams, P. R. Mosaly, J. K. Nuamah, K. Adapa, & L. B. Marks. Impact of Simulation-based Training and Neurofeedback Interventions on Radiation Technologists Workload, Situation Awareness, and Performance. Practical Radiation Oncology, 2020.

 

J. K. Nuamah, K. Adapa, & L. Mazur. Electronic health records (EHR) simulation-based training: a scoping review protocol. BMJ open, 10(8), e036884, 2020.

  

P. R. Mosaly, R. Adams, G. Tracton, J. Dooley, K. Adapa, J. K. Nuamah, ... & L. M. Mazur. Impact of Workspace Design on Radiation Therapist Technicians’ Physical Stressors, Mental Workload, Situation Awareness, and Performance. Practical Radiation Oncology, 2020.

  

R. K. Mehta, & J. K. Nuamah. Relationship Between Acute Physical Fatigue and Cognitive Function During Orthostatic Challenge in Men and Women: A Neuroergonomics Investigation. Human Factors, 0018720820936794, 2020.

  

J. K. Nuamah, C. Rodriguez-Paras, & F. Sasangohar. Veteran-Centered Investigation of Architectural and Space Design Considerations for Post-Traumatic Stress Disorder

(PTSD). HERD: Health Environments Research & Design Journal, 1937586720925554, 2020. 

  

Y. Zhu, J. K. Jayagopal, R. K. Mehta, M. Erraguntla, J. K. Nuamah, A. D. McDonald,  ... & S.H. Chang. Classifying Major Depressive Disorder Using fNIRS During Motor Rehabilita-

tion. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(4), 961-969, 2020. 

 
J. K. Nuamah, R. Mehta, & F. Sasangohar. Technologies for Opioid Use Disorder Management: Mobile App Search and Scoping Review. JMIR mHealth and uHealth, 8(6), e15752, 2020.

  

J. K. Nuamah, F. Sasangohar, M. Erranguntla, & R. K. Mehta. The past, present and future of opioid withdrawal assessment: a scoping review of scales and technologies. BMC medical informatics and decision making, 19(1), 113, 2019.

 
Z. Wang and B. Yao. Multi-Branching Temporal Convolutional Network for Sepsis Prediction. IEEE Journal of Biomedical and Health Informatics, accepted 2021. https://doi.org/10.1109/JBHI.2021.3092835

 

B. Yao, Spatiotemporal Modeling and Optimization for Personalized Cardiac Simulation. IISE Transactions on Healthcare Systems Engineering, accepted 2021. https://doi.org/10.1080/24725579.2021.1879322

 

B. Yao, Y. Chen, and H. Yang, Constrained Markov Decision Process Modeling for Optimal Sensing of Cardiac Events in Mobile Health. IEEE Transactions on Automation Science and Engineering, accepted 2021. https://dx.doi.org/10.1109/TASE.2021.3052483

 

B. Yao and H. Yang. Spatiotemporal Regularization for Inverse ECG Modeling. IISE Transactions on Healthcare Systems Engineering: 1-25. https://doi.org/10.1080/24725579.2020.1823531, accepted 2020.

  

H. D. Kaushik and F. Yousefian, A Method with Convergence Rates for Optimization Problems with Variational Inequality Constraints, SIAM Journal on Optimization, 31 (3): 2171–2198, 2021.

 

A. Jalilzadeh, A. Nedich, U. V. Shanbhag, and F. Yousefian, A Variable Sample-Size Stochastic Quasi-Newton Method for Smooth and Nonsmooth Stochastic Convex Optimization, Mathematics of Operations Research, to appear.

 
F. Yousefian, A. Nedich, and U.V. Shanbhag, On stochastic and deterministic quasi-Newton methods for non-strongly convex optimization: Asymptotic convergence and rate analysis, SIAM Journal on Optimization, 30 (2): 1144-1172, 2020.