BibBase beheshti, r

2024 (6)

Associations of Longitudinal BMI-Percentile Classification Patterns in Early Childhood with Neighborhood-Level Social Determinants of Health. Gupta, M.; Phan, T. T.; Lê-Scherban, F.; Eckrich, D.; Bunnell, H. T.; and Beheshti, R. Childhood Obesity. 2024. PMID: 39187268

Paper doi link bibtex 4 downloads

@article{Gupta24Associate,
author = {Gupta, Mehak and Phan, Thao-Ly T. and L\^{e}-Scherban, F\'{e}lice and Eckrich, Daniel and Bunnell, H. Timothy and Beheshti, Rahmatollah},
AUTHOR+an = {1=student; 6=lead},
title = {Associations of Longitudinal BMI-Percentile Classification Patterns in Early Childhood with Neighborhood-Level Social Determinants of Health},
journal = {Childhood Obesity},
year = {2024},
doi = {10.1089/chi.2023.0157},
    note ={PMID: 39187268},
URL = {https://doi.org/10.1089/chi.2023.0157
},
 addendum = {Impact Factor: 1.5},
eprint = { https://doi.org/10.1089/chi.2023.0157
}
}

Impact of COVID-19 Diagnosis on Weight Trajectories of Children in the US National COVID Cohort Collaborative (N3C) . Mottalib, M. M.; Phan, T. T.; Bramante, C. T; Chute, C. G.; A., P. L.; and Beheshti, R. Childhood Obesity. 2024. Article in press
link bibtex

@article {Mottalib2024N3c,
	author = {Mottalib, Md Mozaharul and Phan, Thao-Ly T. and Bramante, Carolyn T and Chute, Christopher G.  and Pyles Lee A.   and  Beheshti, Rahmatollah},
AUTHOR+an = {1=student; 6=lead},
	title = {Impact of {COVID}-19 Diagnosis on Weight Trajectories of Children in the US National {COVID} Cohort Collaborative ({N3C}) },
	year = {2024},
	journal = {Childhood Obesity},
note = {Article in press},
 addendum = {Impact Factor: 1.5}
}

Reliable prediction of childhood obesity using only routinely collected EHRs may be possible. Gupta, M.; Eckrich, D.; Bunnell, H. T.; Phan, T. T.; and Beheshti, R. Obesity Pillars, 12: 100128. 2024.

Reliable prediction of childhood obesity using only routinely collected EHRs may be possible [link]

Paper doi link bibtex

@article{Gupta2024Reliable,
title = {Reliable prediction of childhood obesity using only routinely collected {EHRs} may be possible},
journal = {Obesity Pillars},
volume = {12},
pages = {100128},
year = {2024},
issn = {2667-3681},
doi = {https://doi.org/10.1016/j.obpill.2024.100128},
url = {https://www.sciencedirect.com/science/article/pii/S2667368124000305},
AUTHOR+an = {1=student; 5=lead},
author = {Mehak Gupta and Daniel Eckrich and H. Timothy Bunnell and Thao-Ly T. Phan and Rahmatollah Beheshti},
 addendum = {The flagship journal of the Obesity Medicine Association (OMA). Established in 2024.}
}

Multimodal Sleep Apnea Detection with Missing or Noisy Modalities. Fayyaz, H.; D'Souza, N. S.; and Beheshti, R. In Machine Learning for Healthcare 2024, 2024. In press

Multimodal Sleep Apnea Detection with Missing or Noisy Modalities [link]

Paper link bibtex 1 download

@inproceedings{fayyaz2024multimodal,
      title={Multimodal Sleep Apnea Detection with Missing or Noisy Modalities}, 
      author={Hamed Fayyaz and Niharika S. D'Souza and Rahmatollah Beheshti},
AUTHOR+an = {1=student; 3=lead},
      year={2024},
booktitle={Machine Learning for Healthcare 2024},
note = {In press},
 addendum = {A top-tier and very selective venue in my field. },
url={https://openreview.net/forum?id=DPpA0ggsz6}
}

HealthGAT: Node Classifications in Electronic Health Records using Graph Attention Networks. Piya, F.; Gupta, M.; and Beheshti, R. In 2024 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), pages 132-141, Los Alamitos, CA, USA, jun 2024. IEEE Computer Society

HealthGAT: Node Classifications in Electronic Health Records using Graph Attention Networks [link]

Paper doi link bibtex

@INPROCEEDINGS {piya2024healthgat,
author = {F. Piya and M. Gupta and R. Beheshti},
     AUTHOR+an = {1=student; 2=student; 3=lead},
    addendum = {Acceptance rate: $\sim$25\%},
booktitle = {2024 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)},
title = {Health{GAT}: Node Classifications in Electronic Health Records using Graph Attention Networks},
year = {2024},
volume = {},
issn = {},
pages = {132-141},
doi = {10.1109/CHASE60773.2024.00022},
url = {https://doi.ieeecomputersociety.org/10.1109/CHASE60773.2024.00022},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
month = {jun}
}

Graph Transformers on EHRs: Better Representation Improves Downstream Performance. Poulain, R.; and Beheshti, R. In The Twelfth International Conference on Learning Representations (ICLR), 2024.

Graph Transformers on EHRs: Better Representation Improves Downstream Performance [link]

Paper link bibtex

@inproceedings{poulain23ICLR,
title={Graph Transformers on {EHR}s: Better Representation Improves Downstream Performance},
author = {Poulain, Raphael and Beheshti, Rahmatollah},
    AUTHOR+an = {1=student; 2=lead},
    addendum = {Acceptance rate: 30\%. Considerd as \textbf{top \#1 or \#2 conference in AI/ML.}},
booktitle={The Twelfth International Conference on Learning Representations (ICLR)},
year={2024},
url={https://openreview.net/forum?id=pe0Vdv7rsL}
}

2023 (3)

Bringing At-home Pediatric Sleep Apnea Testing Closer to Reality: A Multi-modal Transformer Approach. Fayyaz, H.; Strang, A.; and Beheshti, R. In Proceedings of the 8th Machine Learning for Healthcare Conference, volume 219, of Proceedings of Machine Learning Research, pages 167–185, 11–12 Aug 2023. PMLR

Bringing At-home Pediatric Sleep Apnea Testing Closer to Reality: A Multi-modal Transformer Approach [link]

Paper link bibtex

@InProceedings{fayyaz23apneaMLHC,
  title = 	 {Bringing At-home Pediatric Sleep Apnea Testing Closer to Reality: A Multi-modal Transformer Approach},
  author =       {Fayyaz, Hamed and Strang, Abigail and Beheshti, Rahmatollah},
  booktitle = 	 {Proceedings of the 8th Machine Learning for Healthcare Conference},
  pages = 	 {167--185},
  year = 	 {2023},
  volume = 	 {219},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {11--12 Aug},
  publisher =    {PMLR},
  pdf = 	 {https://proceedings.mlr.press/v219/fayyaz23a/fayyaz23a.pdf},
  url = 	 {https://proceedings.mlr.press/v219/fayyaz23a.html},
 AUTHOR+an = {1=student; 3=lead},
    addendum = {A top-tier and very selective venue in my field. \textbf{Featured in Sleep Review Magazine}: \url{sleepreviewmag.com/sleep-diagnostics/connected-care/ai-machine-learning/multimodal-ai-sleep-context}},
}

Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods. Poulain, R.; Bin Tarek, M. F.; and Beheshti, R. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, of FAccT '23, pages 1599–1608, New York, NY, USA, 2023. Association for Computing Machinery

Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods [link]

Paper doi link bibtex

@inproceedings{Poulain2023Improve,
author = {Poulain, Raphael and Bin Tarek, Mirza Farhan and Beheshti, Rahmatollah},
    AUTHOR+an = {1=student; 2=student; 3=lead},
    addendum = {Acceptance rate: 25\%},
title = {Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods},
year = {2023},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3593013.3594102},
doi = {10.1145/3593013.3594102},
booktitle = {Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency},
pages = {1599–1608},
numpages = {10},
keywords = {Adversarial Fairness, Algorithmic Fairness, Federated Learning},
location = {Chicago, IL, USA},
series = {FAccT '23}
}

Subtyping patients with chronic disease using longitudinal BMI patterns. Mottalib, M. M.; Jones-Smith, J. C; Sheridan, B.; and Beheshti, R. IEEE Journal of Biomedical and Health Informatics,1-12. 2023.
doi link bibtex 4 downloads

@ARTICLE{Mottalib2023subtyping,
  author={Mottalib, Md Mozaharul and Jones-Smith, Jessica C and Sheridan, Bethany and Beheshti, Rahmatollah},
  journal={IEEE Journal of Biomedical and Health Informatics}, 
  title={Subtyping patients with chronic disease using longitudinal BMI patterns}, 
  year={2023},
              AUTHOR+an = {1=student;4=lead},
addendum = {Impact factor: 7.7},
  volume={},
  number={},
  pages={1-12},
  doi={10.1109/JBHI.2023.3237753}}

2022 (7)

Obesity Prediction with EHR Data: A Deep Learning Approach with Interpretable Elements. Gupta, M.; Phan, T. T; Bunnell, H T.; and Beheshti, R. ACM Transactions on Computing for Healthcare (HEALTH), 3(3): Article 32. 2022.

Obesity Prediction with EHR Data: A Deep Learning Approach with Interpretable Elements [link]

Paper doi link bibtex 7 downloads

@article{Gupta2022ObesityElements,
    title = {{Obesity Prediction with EHR Data: A Deep Learning Approach with Interpretable Elements}},
    year = {2022},
    journal = {ACM Transactions on Computing for Healthcare (HEALTH)},
    author = {Gupta, Mehak and Phan, Thao-Ly T and Bunnell, H Timothy and Beheshti, Rahmatollah},
                    AUTHOR+an = {1=student;4=lead},
    addendum = {\textbf{Cited by 60+}. A recently established journal. },
    number = {3},
    pages = {Article 32},
    volume = {3},
    url = {https://doi.org/10.1145/3506719},
    doi = {10.1145/3506719},
    issn = {2691-1957},
    keywords = {electronic health records, long short-term memory, deep learning, Childhood obesity, temporal data, transfer learning}
}

Predicting Acute Events using the Movement Patterns of Older Adults: An Unsupervised Clustering Method. Ramazi, R.; Bowen, M. E.; and Beheshti, R. Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, BCB 2022, 1(22). 8 2022.

Predicting Acute Events using the Movement Patterns of Older Adults: An Unsupervised Clustering Method [link]

Paper doi link bibtex 4 downloads

@article{Ramazi2022PredictingMethod,
    title = {{Predicting Acute Events using the Movement Patterns of Older Adults: An Unsupervised Clustering Method}},
    year = {2022},
    journal = {Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, BCB 2022},
    author = {Ramazi, Ramin and Bowen, Mary Elizabeth and Beheshti, Rahmatollah},
                    AUTHOR+an = {1=student;3=lead},
    number = {22},
    month = {8},
    volume = {1},
    publisher = {Association for Computing Machinery, Inc},
    url = {https://doi.org/10.1145/3535508.3545561},
    isbn = {9781450393867},
    doi = {10.1145/3535508.3545561},
    addendum = {Acceptance rate: 29\%}
}

Predicting attrition patterns from pediatric weight management programs. Fayyaz, H.; Phan, T. T.; Bunnell, H. T.; and Beheshti, R. In Proceedings of the 2nd Machine Learning for Health symposium, volume 193, of Proceedings of Machine Learning Research, pages 326–342, 11 2022. PMLR

Predicting attrition patterns from pediatric weight management programs [link]

Paper link bibtex

@InProceedings{fayyaz22attrition,
  title = 	 {Predicting attrition patterns from pediatric weight management programs},
  author =       {Fayyaz, Hamed and Phan, Thao-Ly T. and Bunnell, H. Timothy and Beheshti, Rahmatollah},
   AUTHOR+an = {1=student;4=lead},
addendum = {Acceptance rate: 32\%},
  booktitle = 	 {Proceedings of the 2nd Machine Learning for Health symposium},
  pages = 	 {326--342},
  year = 	 {2022},
  volume = 	 {193},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {11},
  publisher =    {PMLR},
  pdf = 	 {https://proceedings.mlr.press/v193/fayyaz22a/fayyaz22a.pdf},
  url = 	 {https://proceedings.mlr.press/v193/fayyaz22a.html}
}

An Extensive Data Processing Pipeline for MIMIC-IV. Gupta, M.; Gallamoza, B.; Cutrona, N.; Dhakal, P.; Poulain, R.; and Beheshti, R. In Proceedings of the 2nd Machine Learning for Health symposium, volume 193, of Proceedings of Machine Learning Research, pages 311–325, 11 2022. PMLR

An Extensive Data Processing Pipeline for MIMIC-IV [link]

Paper link bibtex

@InProceedings{gupta22mimic,
  title = 	 {An Extensive Data Processing Pipeline for MIMIC-IV},
  author =       {Gupta, Mehak and Gallamoza, Brennan and Cutrona, Nicolas and Dhakal, Pranjal and Poulain, Raphael and Beheshti, Rahmatollah},
                AUTHOR+an = {1=student;2=student;3=student;4=student;5=student;6=lead},
addendum={Acceptance rate: 32\%. \textbf{Cited by 30+}},
  booktitle = 	 {Proceedings of the 2nd Machine Learning for Health symposium},
  pages = 	 {311--325},
  year = 	 {2022},
  volume = 	 {193},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {11},
  publisher =    {PMLR},
  pdf = 	 {https://proceedings.mlr.press/v193/gupta22a/gupta22a.pdf},
  url = 	 {https://proceedings.mlr.press/v193/gupta22a.html}
}

Developing Acute Event Risk Profiles for Older Adults With Dementia in Long-Term Care Using Motor Behavior Clusters Derived From Deep Learning. Ramazi, R.; Bowen, M. E.; Flynn, A. J; and Beheshti, R. Journal of the American Medical Directors Association. 2022.
doi link bibtex 2 downloads

@article{Ramazi2022DevelopingLearning,
    title = {{Developing Acute Event Risk Profiles for Older Adults With Dementia in Long-Term Care Using Motor Behavior Clusters Derived From Deep Learning}},
    year = {2022},
    journal = {Journal of the American Medical Directors Association},
    author = {Ramazi, Ramin and Bowen, Mary Elizabeth and Flynn, Aidan J and Beheshti, Rahmatollah},
            AUTHOR+an = {1=student;4=lead},
addendum = {\textbf{Impact factor: 7.8}. A top journal in  long-term care and geriatrics.},
    doi = {https://doi.org/10.1016/j.jamda.2022.04.009},
    issn = {1525-8610},
    keywords = {Falls, clustering, delirium, dementia, real-time locating system, urinary tract infections}
}

Few-Shot Learning with Semi-Supervised Transformers for Electronic Health Records. Poulain, R.; Gupta, M.; and Beheshti, R. In Proceedings of the Machine Learning for Healthcare (MLHC-2022), 2022.
link bibtex

@inproceedings{Poulain2022Few-ShotRecords,
    title = {{Few-Shot Learning with Semi-Supervised Transformers for Electronic Health Records}},
    year = {2022},
    booktitle = {Proceedings of the Machine Learning for Healthcare (MLHC-2022)},
    author = {Poulain, Raphael and Gupta, Mehak and Beheshti, Rahmatollah},
            AUTHOR+an = {1=student;2=student;3=lead},
    addendum = {A top-tier and very selective venue in my field}
}

Flexible-window Predictions on Electronic Health Records. Gupta, M.; Phan, T. T; Bunnell, H T.; and Beheshti, R. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 36, pages 12510-12516, 2022. AAAI

Flexible-window Predictions on Electronic Health Records [link]

Paper doi link bibtex

@inproceedings{Gupta2022Flexible-windowRecords,
    title = {{Flexible-window Predictions on Electronic Health Records}},
    year = {2022},
    booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
 volume={36}, 
url={https://ojs.aaai.org/index.php/AAAI/article/view/21520}, 
DOI={10.1609/aaai.v36i11.21520},  number={11}, 
    author = {Gupta, Mehak and Phan, Thao-Ly T and Bunnell, H Timothy and Beheshti, Rahmatollah},
                AUTHOR+an ={1=student;4=lead},
addendum = {Acceptance rate: $\sim$25\%},
    publisher = {AAAI},
    pages={12510-12516}
}

2021 (4)

Predicting cardiovascular health trajectories in time-series electronic health records with LSTM models. Guo, A.; Beheshti, R.; Khan, Y. M; Langabeer, J. R; and Foraker, R. E BMC Medical Informatics and Decision Making, 21(1): 1–10. 2021.
link bibtex

@article{Guo2021PredictingModels,
    title = {{Predicting cardiovascular health trajectories in time-series electronic health records with LSTM models}},
    year = {2021},
    journal = {BMC Medical Informatics and Decision Making},
    author = {Guo, Aixia and Beheshti, Rahmatollah and Khan, Yosef M and Langabeer, James R and Foraker, Randi E},
                        AUTHOR+an = {2=me},
addendum = {Impact factor: 2.8},
    number = {1},
    pages = {1--10},
    volume = {21},
    publisher = {BioMed Central}
}

Predicting progression patterns of type 2 diabetes using multi-sensor measurements. Ramazi, R.; Perndorfer, C.; Soriano, E. C; Laurenceau, J.; and Beheshti, R. Smart Health, 21: 100206. 2021.
doi link bibtex 1 download

@article{Ramazi2021PredictingMeasurements,
    title = {{Predicting progression patterns of type 2 diabetes using multi-sensor measurements}},
    year = {2021},
    journal = {Smart Health},
    author = {Ramazi, Ramin and Perndorfer, Christine and Soriano, Emily C and Laurenceau, Jean-Philippe and Beheshti, Rahmatollah},
                    AUTHOR+an = {1=student;5=lead},
addendum = {Elsevier's CiteScore: 4.9},
    pages = {100206},
    volume = {21},
    doi = {https://doi.org/10.1016/j.smhl.2021.100206},
    issn = {2352-6483},
    keywords = {Continuous glucose monitoring, Deep learning, Multi-modal data, Predictive modeling, Type 2 diabetes}
}

Transformer-based Multi-target Regression on Electronic Health Records for Primordial Prevention of Cardiovascular Disease. Poulain, R.; Gupta, M.; Foraker, R.; and Beheshti, R. In 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pages 726–731, 2021.
doi link bibtex 1 download

@inproceedings{Poulain2021Transformer-basedDisease,
    title = {{Transformer-based Multi-target Regression on Electronic Health Records for Primordial Prevention of Cardiovascular Disease}},
    year = {2021},
    booktitle = {2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)},
    author = {Poulain, Raphael and Gupta, Mehak and Foraker, Randi and Beheshti, Rahmatollah},
                    AUTHOR+an = {1=student;2=student;4=lead},
    pages = {726--731},
    doi = {10.1109/BIBM52615.2021.9669441},
    addendum = {Acceptance rate: 20\%}
}

Concurrent imputation and prediction on EHR data using bi-directional GANs. Gupta, M.; Phan, T. T; Bunnell, H T.; and Beheshti, R. In Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, pages Article 7, Gainesville, Florida, 2021. Association for Computing Machinery

Concurrent imputation and prediction on EHR data using bi-directional GANs [link]

Paper doi link bibtex 1 download

@inproceedings{Gupta2021ConcurrentGANs,
    title = {{Concurrent imputation and prediction on EHR data using bi-directional GANs}},
    year = {2021},
    booktitle = {Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics},
    author = {Gupta, Mehak and Phan, Thao-Ly T and Bunnell, H Timothy and Beheshti, Rahmatollah},
        AUTHOR+an = {1=student;4=lead},
    pages = {Article 7},
    publisher = {Association for Computing Machinery},
    url = {https://doi.org/10.1145/3459930.3469512},
    address = {Gainesville, Florida},
    doi = {10.1145/3459930.3469512},
    keywords = {electronic health record, adversarial training, recurrent neural network},
    addendum = {Acceptance rate: 29\%}
}

2019 (2)

Multi-Modal Predictive Models of Diabetes Progression. Ramazi, R.; Perndorfer, C.; Soriano, E.; Laurenceau, J.; and Beheshti, R. In Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, pages 253–258, New York, NY, USA, 2019. Association for Computing Machinery
doi link bibtex 1 download

@inproceedings{Ramazi2019Multi-ModalProgression,
    title = {{Multi-Modal Predictive Models of Diabetes Progression}},
    year = {2019},
    booktitle = {Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics},
    author = {Ramazi, Ramin and Perndorfer, Christine and Soriano, Emily and Laurenceau, Jean-Philippe and Beheshti, Rahmatollah},
                    AUTHOR+an = {1=student;5=lead},
    pages = {253--258},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    isbn = {9781450366663},
    doi = {10.1145/3307339.3342177},
    addendum = {Acceptance rate: 27\%}
}


%%%%%%%%%%%%%%%% OWN PAPERS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Using Agent-Based Models to Understand Health-Related Social Norms. Sukthankar, G.; and Beheshti, R. In Social-Behavioral Modeling for Complex Systems, 27, pages 633–654. John Wiley and Sons, Ltd, 2019.
doi link bibtex

@incollection{Sukthankar2019UsingNorms,
    title = {{Using Agent-Based Models to Understand Health-Related Social Norms}},
    year = {2019},
    booktitle = {Social-Behavioral Modeling for Complex Systems},
    author = {Sukthankar, Gita and Beheshti, Rahmatollah},
    AUTHOR+an = {2=me},
    addendum = {Invited Book Chapter},
    chapter = {27},
    pages = {633--654},
    publisher = {John Wiley and Sons, Ltd},
    isbn = {9781119485001},
    doi = {10.1002/9781119485001.ch27}
}

2018 (1)

A predictive model of rat calorie intake as a function of diet energy density. Beheshti, R.; Treesukosol, Y.; Igusa, T.; and Moran, T. H. American Journal of Physiology - Regulatory Integrative and Comparative Physiology, 315(2): R255-R266. 8 2018.
doi link bibtex

@article{Beheshti2018ADensity,
    title = {{A predictive model of rat calorie intake as a function of diet energy density}},
    year = {2018},
    journal = {American Journal of Physiology - Regulatory Integrative and Comparative Physiology},
    author = {Beheshti, Rahmatollah and Treesukosol, Yada and Igusa, Takeru and Moran, Timothy H.},
                        AUTHOR+an = {1=me},
    number = {2},
    month = {8},
    pages = {R255-R266},
    volume = {315},
    publisher = {American Physiological Society},
    doi = {https://doi.org/10.1152/ajpregu.00337.2017},
    issn = {15221490},
    pmid = {29341825},
    keywords = {High-energy diet, Palatability, Predictive model, Rats}
}

2017 (2)

Taking dietary habits into account: A computational method for modeling food choices that goes beyond price. Beheshti, R.; Jones-Smith, J. C.; and Igusa, T. PLOS ONE, 12(5): e0178348. 5 2017.

Taking dietary habits into account: A computational method for modeling food choices that goes beyond price [link]

Paper doi link bibtex

@article{Beheshti2017TakingPrice,
    title = {{Taking dietary habits into account: A computational method for modeling food choices that goes beyond price}},
    year = {2017},
    journal = {PLOS ONE},
    author = {Beheshti, Rahmatollah and Jones-Smith, Jessica C. and Igusa, Takeru},
                        AUTHOR+an = {1=me},
    number = {5},
    month = {5},
    pages = {e0178348},
    volume = {12},
    publisher = {Public Library of Science},
    url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0178348},
    doi = {10.1371/JOURNAL.PONE.0178348},
    issn = {1932-6203},
    pmid = {28542615},
    keywords = {Agent-based modeling, Budgets, Decision making, Diet, Eating habits, Fats, Food, Nutrition}
}

Comparing methods of targeting obesity interventions in populations: An agent-based simulation. Beheshti, R.; Jalalpour, M.; and Glass, T. A. SSM - Population Health, 3: 211–218. 12 2017.
doi link bibtex

@article{Beheshti2017ComparingSimulation,
    title = {{Comparing methods of targeting obesity interventions in populations: An agent-based simulation}},
    year = {2017},
    journal = {SSM - Population Health},
    author = {Beheshti, Rahmatollah and Jalalpour, Mehdi and Glass, Thomas A.},
                        AUTHOR+an = {1=me},
    month = {12},
    pages = {211--218},
    volume = {3},
    publisher = {Elsevier},
    doi = {10.1016/J.SSMPH.2017.01.006},
    issn = {2352-8273},
    keywords = {Agent-based modeling, Effectiveness, Influence maximization, Intervention targeting, Obesity, Simulation, Social networks}
}

2016 (2)

Simulated Models Suggest That Price per Calorie Is the Dominant Price Metric That Low-Income Individuals Use for Food Decision Making. Beheshti, R.; Igusa, T.; and Jones-Smith, J. The Journal of Nutrition, 146(11): 2304–2311. 2016.
doi link bibtex

@article{Beheshti2016SimulatedMaking,
    title = {{Simulated Models Suggest That Price per Calorie Is the Dominant Price Metric That Low-Income Individuals Use for Food Decision Making}},
    year = {2016},
    journal = {The Journal of Nutrition},
    author = {Beheshti, Rahmatollah and Igusa, Takeru and Jones-Smith, Jessica},
                        AUTHOR+an = {1=me},
    number = {11},
    pages = {2304--2311},
    volume = {146},
    doi = {10.3945/jn.116.235952}
}

Negotiations in Holonic multi-agent systems. Beheshti, R.; Barmaki, R.; and Mozayani, N. In Recent Advances in Agent-based Complex Automated Negotiation, pages 107–118. Springer, 2016.
link bibtex

@incollection{Beheshti2016NegotiationsSystems,
    title = {{Negotiations in Holonic multi-agent systems}},
    year = {2016},
    booktitle = {Recent Advances in Agent-based Complex Automated Negotiation},
    author = {Beheshti, Rahmatollah and Barmaki, Roghayeh and Mozayani, Nasser},
                        AUTHOR+an = {1=me},
    pages = {107--118},
    publisher = {Springer}
}

2015 (3)

A hybrid modeling approach for parking and traffic prediction in urban simulations. Beheshti, R.; and Sukthankar, G. AI and SOCIETY, 30(3): 333–344. 2015.
link bibtex

@article{Beheshti2015ASimulations,
    title = {{A hybrid modeling approach for parking and traffic prediction in urban simulations}},
    year = {2015},
    journal = {AI and SOCIETY},
    author = {Beheshti, Rahmatollah and Sukthankar, Gita},
                        AUTHOR+an = {1=me},
    number = {3},
    pages = {333--344},
    volume = {30},
    publisher = {Springer London},
    issn = {0951-5666},
    language = {English}
}

Cognitive Social Learners: An Architecture for Modeling Normative Behavior. Beheshti, R.; Ali, A. M.; and Sukthankar, G. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, pages 2017–2023, Austin, TX, 1 2015.
link bibtex

@inproceedings{Beheshti2015CognitiveBehavior,
    title = {{Cognitive Social Learners: An Architecture for Modeling Normative Behavior}},
    year = {2015},
    booktitle = {Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence},
    author = {Beheshti, Rahmatollah and Ali, Awrad Mohammed and Sukthankar, Gita},
                        AUTHOR+an = {1=me},
    month = {1},
    pages = {2017--2023},
    address = {Austin, TX}
}

Modeling Tipping Point Theory using Normative Multi-agent Systems. Beheshti, R.; and Sukthankar, G. In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 1731–1732, 2015.
link bibtex

@inproceedings{Beheshti2015ModelingSystems,
    title = {{Modeling Tipping Point Theory using Normative Multi-agent Systems}},
    year = {2015},
    booktitle = {Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS)},
    author = {Beheshti, Rahmatollah and Sukthankar, Gita},
                        AUTHOR+an = {1=me},
    pages = {1731--1732}
}

2014 (3)

A Normative Agent-based Model for Predicting Smoking Cessation. Beheshti, R.; and Sukthankar, G. In Proceedings of the International Conference on Autonomous Agents and Multi-agent Systems (AAMAS), pages 557–564, 2014.
link bibtex

@inproceedings{Beheshti2014ACessation,
    title = {{A Normative Agent-based Model for Predicting Smoking Cessation}},
    year = {2014},
    booktitle = {Proceedings of the International Conference on Autonomous Agents and Multi-agent Systems (AAMAS)},
    author = {Beheshti, Rahmatollah and Sukthankar, Gita},
                        AUTHOR+an = {1=me},
    pages = {557--564}
}

HOMAN, a learning based negotiation method for holonic multi-agent systems. Beheshti, R.; and Mozayani, N. Journal of Intelligent and Fuzzy Systems, 26(2): 655–666. 2014.
link bibtex

@article{Beheshti2014HOMANSystems,
    title = {{HOMAN, a learning based negotiation method for holonic multi-agent systems}},
    year = {2014},
    journal = {Journal of Intelligent and Fuzzy Systems},
    author = {Beheshti, Rahmatollah and Mozayani, Nasser},
                        AUTHOR+an = {1=me},
    number = {2},
    pages = {655--666},
    volume = {26},
    publisher = {IOS Press}
}

Negotiations in Holonic Multi-agent systems. Beheshti, R.; Barmaki, R.; and Mozayani, N. In Proceedings of the International Workshop on Agent-based Complex Automated Negotiations (ACAN), 2014.
link bibtex

@inproceedings{Beheshti2014NegotiationsSystems,
    title = {{Negotiations in Holonic Multi-agent systems}},
    year = {2014},
    booktitle = {Proceedings of the International Workshop on Agent-based Complex Automated Negotiations (ACAN)},
                        AUTHOR+an = {1=me},
    author = {Beheshti, Rahmatollah and Barmaki, Roghayeh and Mozayani, Nasser}
}

2013 (2)

Analyzing Agent-based Models using Category Theory. Beheshti, R.; and Sukthankar, G. In IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT), pages 280–286, 2013.
link bibtex

@inproceedings{Beheshti2013AnalyzingTheory,
    title = {{Analyzing Agent-based Models using Category Theory}},
    year = {2013},
    booktitle = {IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT)},
    author = {Beheshti, Rahmatollah and Sukthankar, Gita},
                        AUTHOR+an = {1=me},
    pages = {280--286}
}

Improving Markov Chain Monte Carlo Estimation with Agent-Based Models. Beheshti, R.; and Sukthankar, G. In Proceedings of the International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP), pages 495–502, 2013.
link bibtex

@inproceedings{Beheshti2013ImprovingModels,
    title = {{Improving Markov Chain Monte Carlo Estimation with Agent-Based Models}},
    year = {2013},
    booktitle = {Proceedings of the International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP)},
    author = {Beheshti, Rahmatollah and Sukthankar, Gita},
                        AUTHOR+an = {1=me},
    pages = {495--502}
}

2012 (1)

Extracting Agent-Based Models of Human Transportation Patterns. Beheshti, R.; and Sukthankar, G. In Proceedings of the ASE/IEEE International Conference on Social Informatics, pages 157–164, 2012.
link bibtex

@inproceedings{Beheshti2012ExtractingPatterns,
    title = {{Extracting Agent-Based Models of Human Transportation Patterns}},
    year = {2012},
    booktitle = {Proceedings of the ASE/IEEE International Conference on Social Informatics},
    author = {Beheshti, Rahmatollah and Sukthankar, Gita},
                        AUTHOR+an = {1=me},
    pages = {157--164}
}

2011 (1)

A New Mechanism for Negotiations in Multi-Agent Systems Based on ARTMAP Artificial Neural Network. Beheshti, R.; and Mozayani, N. In Agent and Multi-Agent Systems: Technologies and Applications, volume 6682, of Lecture Notes in Computer Science, pages 311–320. Springer Berlin Heidelberg, 2011.
link bibtex

@incollection{Beheshti2011ANetwork,
    title = {{A New Mechanism for Negotiations in Multi-Agent Systems Based on ARTMAP Artificial Neural Network}},
    year = {2011},
    booktitle = {Agent and Multi-Agent Systems: Technologies and Applications},
    author = {Beheshti, Rahmatollah and Mozayani, Nasser},
                        AUTHOR+an = {1=me},
    pages = {311--320},
    series = {Lecture Notes in Computer Science},
    volume = {6682},
    publisher = {Springer Berlin Heidelberg}
}

2009 (4)

Predicting opponents offers in multi-agent negotiations using ARTMAP neural network. Beheshti, R.; and Mozayani, N. In Proceedings of International Conference on Future Information Technology and Management Engineering (FITME), pages 600–603, 2009.
link bibtex

@inproceedings{Beheshti2009PredictingNetwork,
    title = {{Predicting opponents offers in multi-agent negotiations using ARTMAP neural network}},
    year = {2009},
    booktitle = {Proceedings of International Conference on Future Information Technology and Management Engineering  (FITME)},
    author = {Beheshti, Rahmatollah and Mozayani, Nasser},
                        AUTHOR+an = {1=me},
    pages = {600--603}
}

A multi-objective genetic algorithm method to support multi-agent negotiations. Beheshti, R.; and Rahmani, A. T In Proceedings of International Conference on Future Information Technology and Management Engineering (FITME), pages 596–599, 2009.
link bibtex

@inproceedings{Beheshti2009ANegotiations,
    title = {{A multi-objective genetic algorithm method to support multi-agent negotiations}},
    year = {2009},
    booktitle = {Proceedings of International Conference on Future Information Technology and Management Engineering  (FITME)},
    author = {Beheshti, Rahmatollah and Rahmani, Adel T},
                        AUTHOR+an = {1=me},
    pages = {596--599}
}

A New Hybrid Evolutionary Method With Ant Colony and PSO Algorithms Based on Fuzzy Decision Making. Beheshti, R.; Mozayani, N.; and Rahmani, A. T In Proceedings of the International Conference of Iranian Operation Research Society, 2009.
link bibtex

@inproceedings{Beheshti2009AMaking,
    title = {{A New Hybrid Evolutionary Method With Ant Colony and PSO Algorithms Based on Fuzzy Decision Making}},
    year = {2009},
    booktitle = {Proceedings of the International Conference of Iranian Operation Research Society},
                        AUTHOR+an = {1=me},
    author = {Beheshti, Rahmatollah and Mozayani, Nasser and Rahmani, Adel T}
}

A Pairwise Classification Method with Support Vector Machines, Based on Game Theory and Alpha-beta Algorithm. Beheshti, R.; Analui, M.; and Minaei-Bidgol, B. In Proceedings of the International Conference of Iranian Operation Research Society, 2009.
link bibtex

@inproceedings{Beheshti2009AAlgorithm,
    title = {{A Pairwise Classification Method with Support Vector Machines, Based on Game Theory and Alpha-beta Algorithm}},
    year = {2009},
    booktitle = {Proceedings of the International Conference of Iranian Operation Research Society},
                        AUTHOR+an = {1=me},
    author = {Beheshti, Rahmatollah and Analui, Morteza and Minaei-Bidgol, Behrouz}
}