This page lists my publications. For a more more updated list and/or the links for the papers, please visit my Google Scholar page.


  1. Analysis of deterministic cyclic gene regulatory network models with delays, Ahsen ME, Hitay Ozbay, S-I Niculescu, Birkhauser (2015).


  1. The Role of Technologies in Supply Chain Efficiency and Resiliency, Ahsen ME, Mohammad Moshref-Javadi. (2024), Impacts of COVID-19 on Supply Chains: Disruptions, Technologies, and Solutions.
  2. A Secant Condition for Cyclic Systems with Time Delays, Ahsen ME, Hitay Ozbay, S-I Niculescu, Time Delay Systems, Springer Verlag (2017).
  3. Analysis of gene regulatory networks under positive feedback, Ahsen ME, Hitay Ozbay, S-I Niculescu, Delay Systems, Springer Verlag (2014).

Publications In Peer-Reviewed Journals

  1. Optimal Linear Ensemble of Binary Classifiers. Ahsen ME, Robert Vogel, Gustavo Stolovitzky. (2024). Bioinformatics Advances.
  2. COVID-19 test-to-stay program for K-12 schools: Opt-in versus opt-out consent model. Anton Ivanov, (6 Authors), Ahsen ME, Sebastian Souyris. (2024), Iscience.
  3. Modeling combination therapies in patient cohorts and cell cultures using correlated drug action. AS Arun, SC Kim, Ahsen ME, Gustavo Stolovitzky. (2024), Iscience.
  4. A primer on the use of machine learning to distil knowledge from data in biological psychiatry. Thomas P Quinn, (13 Authors), Ahsen ME, Stephen J Glatt. (2024), Molecular Psychiatry.
  5. The societal impact of sharing economy platform self-regulations—An empirical investigation. Wencui Han, Xunyi Wang, Ahsen ME, Sunil Wattal. (2022), Information Systems Research.
  6. External validation of an ensemble model for automated mammography interpretation by artificial intelligence. William Hsu, (5 Authors), Ahsen ME, CI Lee. (2022), JAMA Network Open.
  7. Unannotated small RNA clusters associated with circulating extracellular vesicles detect early stage liver cancer. Johann Von Felden, (3 Authors), Ahsen ME,Augusto Villanueva. (2022), Gut.
  8. The Fermi–Dirac distribution provides a calibrated probabilistic output for binary classifiers. SC Kim, AS Arun, Ahsen ME, Robert Vogel, Gustavo Stolovitzky. (2021). PNAS (Proceedings of the National Academy of Science).
  9. A community challenge to evaluate RNA-seq, fusion detection, and isoform quantification methods for cancer discovery. Creason Allison, (20 Authors), Ahsen ME, Kyle Ellrott. (2021). Cell Systems.
  10. Transcriptomic characterization of cancer-testis antigens identifies MAGEA3 as a driver of tumor progression in hepatocellular carcinoma. Craig AJ, (7 Authors), Ahsen ME, Augusto Villanueva. (2021). PLOS Genetics.
  11. Effect of AI explanations on human perceptions of patient-facing AI-powered healthcare systems, Zhang Z, Genc Y, Wang D, Ahsen ME, Fan X. (2021) Journal of Medical Systems
  12. R/PY-SUMMA: An R/Python Package for Unsupervised Ensemble Learning for Binary Classification Problems in Bioinformatics. Ahsen, M. E., Vogel, R., & Stolovitzky, G. A. (2020). Journal of Computational Biology.
  13. Intratumoral heterogeneity and clonal evolution in liver cancer. Losic, B., Craig, A. J., Villacorta-Martin, C., Martins-Filho, S. N., Akers, N., Chen, X.,Ahsen ME,…,Villanueva Augusto. (2020). Nature communications, 11(1), 1-15.
  14.  Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms. Schaffter, T.,(6 Authors), Ahsen ME, (15 Authors), Stolovitzky G. (2020). JAMA network open, 3(3), e200265-e200265.
  15. The transcriptomic response of cells to a drug combination is more than the sum of the responses to the monotherapies. Diaz, J. E., Ahsen, M. E., Schaffter, T., Chen, X., Realubit, R. B., Karan, C., … & Stolovitzky, G. (2020). Elife, 9, e52707.
  16. Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data. Tanevski, J., Nguyen, T., Truong, B., Karaiskos, N., Ahsen, ME, Zhang, X., … & Pham, H. V. (2020). Life science alliance, 3(11).
  17. COSIFER: a python package for the consensus inference of molecular interaction networks. Manica, M., Bunne, C., Mathis, R., Cadow, J., Ahsen, ME., Stolovitzky, G. A., & Martínez, M. R. (2020). Bioinformatics.
  18. Unsupervised Evaluation and Weighted Aggregation of Ranked Classification Predictions. Ahsen, M. E., Vogel, R. M., & Stolovitzky, G. A. (2019). Journal of Machine Learning Research, 20(166), 1-40.
  19.  NeTFactor, a framework for identifying transcriptional regulators of gene expression-based biomarkers. Ahsen, ME, Chun, Y., Grishin, A., Grishina, G., Stolovitzky, G., Pandey, G., & Bunyavanich, S. (2019).Nature Scientific Reports, 9(1), 12970-12970.
  20. Inferring Genome-Wide Interaction Networks Using the Phi-Mixing Coefficient, and Applications to Lung and Breast Cancer, Singh N, Ahsen ME, et. al., IEEE Transactions on Molecular, Biological, and Mulstiscale Communications (2019).
  21. Leveraging Crowdsourcing to accelerate global health solutions, Sage Davis, (3 Authors), Ahsen ME, et al., Nature Biotechnology (2019).
  22. Robust and interpretable assessment of network module identification methods, Choobdar S, Ahsen ME, (21 Authors), Nature Methods (2019).
  23. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen, Menden MP, (13 Authors), Ahsen ME, (11 Authors), Nature Communications (2019).
  24. Radiogenomics Consortium Genome-Wide Association Study Meta-analysis of Late Toxicity after Prostate Cancer Radiotherapy, Kerns SL, (9 Authors), Ahsen ME, (27 Authors), Journal of Natl Cancer Institute (2019).
  25. ExRNA Atlas analysis reveals distinct extracellular RNA cargo types present across human biofluids, Murillo OD, Thistlethwaite W, (19 Authors), Ahsen ME, (35 Authors), Milosavljevic A, Cell (2019).
  26. An Approach to One-Bit Compressed Sensing Based on Probably Approximately Correct Learning Theory, Ahsen ME, Vidyasagar M, Journal of Machine Learning (2019).
  27. Integrated nanoscale deterministic lateral displacement arrays for seperation of extracellular vesicles from clinically-relevant volumes of biological samples, Smith J, Wunsch B and Dogra N and Ahsen ME et. al. , Lab on a Chip (2018).
  28. When Algorithmic Predictions Use Human-Generated Data: A Bias-Aware Classification Algorithm for Breast Cancer Diagnosis, Ahsen ME, Ayvaci MUS, Raghunathan S , Information Systems Research (In Press).
  29. A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection, Slim Fourati,(7 Authors), Ahsen ME et al. , Nature Communications (In Press).
  30. Preference-Sensitive Management of Post-Mammography Decisions in Breast Cancer Diagnosis, Ayvaci MUS, Alagoz O, Ahsen ME, Burnside ES, Production and Operations Management (2018).
  31. A Novel Nasal Brush-based Classifier of Asthma Identified by Machine Learning Analysis of Nasal RNA Sequence Data, Gaurav Pandey, Om Pandey, Angela Rogers, Ahsen ME et al., Scientific Reports, (2018).
  32. Two New Approaches to Compressed Sensing Exhibiting Both Robust Sparse Recovery and the Grouping Effect, Ahsen ME, Niharika Challapalli,Mathukumalli Vidyasagar, Journal of Machine Learning Research (2017).
  33. Error bounds for compressed sensing algorithms with group sparsity: A unified approach, Ahsen ME, Mathukumalli Vidyasagar, Applied and Computational Harmonic Analysis (2017).
  34. Sparse Feature Selection for Classification and Prediction of Metastasis in Endometrial, Ahsen ME et al., BMC Genomics, (2017).
  35. Timing the Use of Breast Cancer Risk Information in Biopsy Decision Making, Ayvaci MUS, Ahsen ME, Raghunathan S, Gharibi Z, Production and Operations Management, 26 (7), p. 1333-1358 (2017).
  36. Estimating Waiting Time for Deceased Donor Renal Transplantion in the Era of New Kidney Allocation System, Furkan Torlak, Mehmet U.S. Ayvaci, Ahsen ME et al., Transplantation Proceedings, 2016.
  37. Analysis of a Gene Regulatory Network Model with Time Delay Using the Secant Condition, Ahsen ME, Hitay Ozbay, S-I Niculescu, IEEE Life Sciences Letters (2016).
  38. Optimized Prediction of Extreme Treatment Outcomes in Ovarian Cancer, Burook Misganaw, Ahsen MEet al., Cancer Informatics (2015).
  39. Mixing Coefficients between discrete and real random variables: Computation and Properties, Ahsen ME, Mathukumalli Vidyasagar, IEEE Transactions on Automatic Control (2014).
  40. On the analysis of a dynamical model representing gene regulatory networks under negative feedback, Ahsen ME, Hitay Ozbay S-I Niculescu, International Journal of Robust and Nonlinear Control (2014).

Publications in Peer-Reviewed Conference Proceedings

  1. When Machines Will Take Over? Algorithms for Human-Machine Collaborative Decision Making in Healthcare. Ahsen ME, Mehmet Ulvi Saygi Ayvaci, Radha Mookerjee. (2024). Proceedings of the 56th Annual Hawaii International Conference on System Sciences.
  2. NeTFactor, a framework for identifying transcriptional regulators of gene expression-based biomarkers.Ahsen ME, Yoojin Chun, Alexander Grishin, Galina Grishina, Gustavo Stolovitzky, Gaurav Pandey, Supinda Bunyavanich. (2020). Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics.
  3. Modelling drug response and resistance in cancer: Oppurtunities and challenges, Niharika Challapalli,Ahsen ME, Mathukumalli Vidyasagar, Proceedings of the IEEE 55rd Annual Conference on Decision and Control (CDC) (2016).
  4. A Secant Condition for Cyclic Systems with Time Delays and its Application to Gene Regulatory Networks, Ahsen ME, Hitay Ozbay, S-I Niculescu, Proceedings of the 12th IFAC Workshop on Time Delay Systems (2015).
  5. A PAC learning approach to One-Bit Compressed Sensing, Ahsen ME, Mathukumalli Vidyasagar, Proceedings of the 2015 American Control Conference (ACC) (2015).
  6. An Approach to one-bit compressed sensing based on probably approximately correct learning theory, Ahsen ME, Mathukumalli Vidyasagar , Proceedings of the IEEE 54rd Annual Conference on Decision and Control (CDC) (2015).
  7. Optimized prediction of extreme treatment outcomes in ovarian cancer, Burook Misganaw, Ahsen ME et. al. , Proceedings of the IEEE 54rd Annual Conference on Decision and Control (CDC) (2015).
  8. Near-ideal behavior of some compressed sensing algorithms, Ahsen ME, M Vidyasagar, In proceedings of the 2014 European Control Conference (ECC) (2014).
  9. Opportunistic wireless charging for mobile social and sensor networks, Eyuphan Bulut, Ahsen ME, Boleslaw K Szymanski, Proceedings of the 2014 Globecom Workshop (2014).
  10. On the computation of mixing coefficients between discrete-valued random variables, Ahsen ME, M Vidyasagar, Proceedings of the 2013 Asian Control Conference (ASCC) (2013).
  11. A novel application of mixing coefficients for reverse-engineering gene interaction networks, Nitin Singh, Ahsen ME, Shiva Mankala, M Vidyasagar, Michael A White, In Proceedings of the 50th Annual Allerton Conference on Communication, Control, and Computing (2013).
  12. Stability analysis of a dynamical model representing gene regulatory networks, Ahsen ME, Hitay Ozbay, Silviu-Iulian Niculescu, In Proceedings of the 10th IFAC workshop on Time Delay Systems (2012).
  13. Inferring weighted and directed gene interaction networks from gene expression data using the phi-mixing coefficient, Nitin Singh, Ahsen ME, Shiva Mankala, M Vidyasagar, Michael White, In Proceedings of the 2012 IEEE International Workshop on, Genomic Signal Processing and Statistics,(GENSIPS) (2012).
  14. A new feature selection algorithm for two-class classification problems and application to endometrial cancer, Ahsen ME, Nitin Kumar Singh, Todd Boren, M Vidyasagar, Michael A White, In proceedings of the IEEE 51st Annual Conference on Decision and Control (CDC) (2012).