Khaled, S. M. and Biswas, A. K. and Rahman, M. L. and Pervin, S. (2005) An Analysis on Human Resource Development in the ICT Sector of Bangladesh. In the 8th International Conference on Computer & Information Technology, Dec. 28–30, 2005, pp. 507–512.
Khaled, S. M. and Biswas, A. K. and Qayum, M. A. and Rahman, M. L. (2006) Present Status of Telecommunication in Bangladesh and its Impact on ICT. In The 9th International Conference on Computer & Information Technology, Dec. 21–23, 2006, pp. 221–226.
Khaled, S. M., Karim, R., Biswas, A. K., Rahman, R. H., Nowsheen, N., & Qayum, M. A. (2007). Optimization of Reliability in a Real Time Security System Controlled by Embedded Internet Technology. Asian Journal of Information Technology, 6(10), 1050-1056.
Biswas, A. K., Hasan, M. M., Chowdhury, A. R., & Babu, H. M. H. (2008). Efficient approaches for designing reversible binary coded decimal adders. Microelectronics journal, 39(12), 1693-1703.
Biswas, A. K., Hasan, M. M., Hasan, M., Chowdhury, A. R., & Babu, H. M. H. (2008, January). A novel approach to design BCD adder and carry skip BCD adder. In 21st international conference on VLSI design (VLSID 2008) (pp. 566-571). IEEE.
Biswas, A. K., Noman, N., & Sikder, A. R. (2010). Machine learning approach to predict protein phosphorylation sites by incorporating evolutionary information. BMC bioinformatics, 11(1), 1-17.
Biswas, A. K., Jamal, L., Mottalib, M. A., & Babu, H. M. H. (2011). Design of a reversible parallel loading shift register. Dhaka Univ. J. Eng & Tech, 1(2), 1-5.
Sultana, A., Hasan, Q. M., Biswas, A. K., Das, S., Rahman, H., Ding, C., & Li, C. (2012, October). Infobox suggestion for Wikipedia entities. In Proceedings of the 21st ACM international conference on Information and knowledge management (pp. 2307-2310)
Biswas, A. K., Zhang, B., Wu, X., & Gao, J. X. (2013, November). QLZCClust: Quaternary lempel-Ziv complexity based clustering of the RNA-seq read block segments. In 13th IEEE International Conference on BioInformatics and BioEngineering (pp. 1-4). IEEE.
Biswas, A. K. and Gao, J. X. annd Wu, X. and Zhang, B. (2013) Integrating RNA-seq transcript signals, Primary and Secondary Structure Information in Differentiating coding and non-coding RNA transcripts. In The 5th International Conference on Bioinformatics and Computational Biology. ISCA, Mar. 4–6, 2013.
Biswas, A. K., Zhang, B., Wu, X., & Gao, J. X. (2013). CNCTDiscriminator: coding and noncoding transcript discriminator—an excursion through hypothesis learning and ensemble learning approaches. Journal of bioinformatics and computational biology, 11(05), 1342002.
Biswas, A. K., Zhang, B., Wu, X., & Gao, J. X. (2014). An Information Integration Approach for Classifying Coding and Non-Coding Genomic Data. In The Proceedings of the Second International Conference on Communications, Signal Processing, and Systems (pp. 1085-1093). Springer, Cham.
Biswas, A. K., Gao, J. X., Zhang, B., & Wu, X. (2014, November). NMF-based LncRNA-disease association inference and Bi-clustering. In 2014 IEEE International Conference on Bioinformatics and Bioengineering (pp. 97-104). IEEE.
Kang, M., Park, J., Kim, D. C., Biswas, A. K., Liu, C., & Gao, J. (2015, November). An integrative genomic study for multimodal genomic data using multi-block bipartite graph. In 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 563-568). IEEE.
Kim, D. C., Kang, M., Biswas, A., Liu, C., & Gao, J. (2015, November). Integrative approach for inference of gene regulatory networks using lasso-based random featuring and application to Psychiatric disorders. In Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 145-150).
Biswas, A. K., Zhang, B., Wu, X., & Gao, J. X. (2015). A multi-label classification framework to predict disease associations of long non-coding RNAs (lncRNAs). In The Proceedings of the Third International Conference on Communications, Signal Processing, and Systems (pp. 821-830). Springer, Cham.
Biswas, A. K., Kang, M., Kim, D. C., Ding, C. H., Zhang, B., Wu, X., & Gao, J. X. (2015). Inferring disease associations of the long non-coding RNAs through non-negative matrix factorization. Network Modeling Analysis in Health Informatics and Bioinformatics, 4(1), 1-17.
Biswas, A. K., Kim, D. C., Kang, M., & Gao, J. X. (2016, December). Robust Inductive Matrix Completion strategy to explore associations between lincRNAs and human disease phenotypes. In 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 334-339). IEEE Computer Society.
Biswas, A. K., Zhang, B., Wu, X., & Gao, J. X. (2016). Improving Consensus Hierarchical Clustering Framework. In Proceedings of the 2015 International Conference on Communications, Signal Processing, and Systems (pp. 781-791). Springer, Berlin, Heidelberg.
Kim, D., Kang, M., Biswas, A., Liu, C., & Gao, J. (2016). Integrative approach for inference of gene regulatory networks using lasso-based random featuring and application to psychiatric disorders. BMC Medical Genomics, 9(2), 111-122.
Sworna, Z. T., UlHaque, M., Tara, N., Hasan Babu, H. M., & Biswas, A. K. (2016). Low‐power and area efficient binary coded decimal adder design using a look up table‐based field programmable gate array. IET Circuits, Devices & Systems, 10(3), 163-172.
Biswas, A. K., & Gao, J. X. (2016). PR2S2Clust: patched rna-seq read segments’ structure-oriented clustering. Journal of Bioinformatics and Computational Biology, 14(05), 1650027.
Kang, M., Park, J., Kim, D. C., Biswas, A. K., Liu, C., & Gao, J. (2016). Multi-block bipartite graph for integrative genomic analysis. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 14(6), 1350-1358.
Sworna, Z. T., Haque, M. U., Babu, H. M. H., Jamal, L., & Biswas, A. K. (2017, July). An Efficient Design of an FPGA-Based Multiplier Using LUT Merging Theorem. In 2017 IEEE Computer Society Annual Symposium on VLSI (ISVLSI) (pp. 116-121). IEEE.
Biswas, A., & Gao, J. (2017, November). LiDiAimc: LincRNA-disease associations through inductive matrix completion. In 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 158-163). IEEE.
Babu, H. M. H., Jamal, L., Dibbo, S. V., & Biswas, A. K. (2017, July). Area and delay efficient design of a quantum bit string comparator. In 2017 IEEE Computer Society Annual Symposium on VLSI (ISVLSI) (pp. 51-56). IEEE.
Biswas, A. K., Kim, D., Kang, M., Ding, C., & Gao, J. X. (2017). Stable solution to l 2, 1-based robust inductive matrix completion and its application in linking long noncoding RNAs to human diseases. BMC Medical Genomics, 10(5), 1-16. Chicago.
Kim, D. C., Kang, M., Biswas, A., Yang, C. R., Wang, X., & Gao, J. X. (2017). Effects of low dose ionizing radiation on DNA damage-caused pathways by reverse-phase protein array and Bayesian networks. Journal of Bioinformatics and Computational Biology, 15(02), 1750006.
Babu, H. M., Mia, M., & Biswas, A. K. (2017). Efficient techniques for fault detection and correction of reversible circuits. Journal of Electronic Testing, 33(5), 591-605.
H. Holme and A. K. Biswas. (2018) Toward pre-pregnancy diagnosis of autism spectrum disorders using machine learning algorithms, in Workshop on Human and Mammalian Genetics and Genomics and the 59th McKusick Short Course. Jackson Laboratory, Bar Harbor, Maine, 2018, pp. 1–1.
Debnath, M., Tripathi, P. K., Biswas, A. K., & Elmasri, R. (2018, November). Preference aware travel route recommendation with temporal influence. In Proceedings of the 2nd ACM SIGSPATIAL Workshop on Recommendations for Location-based Services and Social Networks (pp. 1-9).
Ul Haque, M., Sworna, Z. T., Hasan Babu, H. M., & Biswas, A. K. (2018). A fast fpga-based bcd adder. Circuits, Systems, and Signal Processing, 37(10), 4384-4408.
Biswas, A. K., Kim, D. C., Kang, M., & Gao, J. X. (2018). Robust inductive matrix completion strategy to explore associations between lincrnas and human disease phenotypes. IEEE/ACM transactions on computational biology and bioinformatics, 16(6), 2066-2077.
Pastorino, J., & Biswas, A. K. (2019, November). TexAnASD: Text Analytics for ASD Risk Gene Predictions. In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 1350-1357). IEEE.
Kang, M., Biswas, A., Kim, D. C., & Gao, J. (2019, December). Semi-Supervised Discriminative Transfer Learning in Cross-Language Text Classification. In 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA) (pp. 1031-1038). IEEE.
Peng, J., Debnath, M., & Biswas, A. K. (2021). Efficacy of novel Summation-based Synergetic Artificial Neural Network in ADHD diagnosis. Machine Learning with Applications, 6, 100120.
Biswas, A. K. and Sikder, A. R. and Noman, N. (2010) Incorporating Evolutionary Information in Protein Phosphorylation Site Predictions. In The 8th Asia Pacific Bioinformatics Conference. ISCB, Jan. 18–21.
Pastorino, J., & Biswas, A. K. (2020, December). Hey ML, what can you do for me?. In 2020 IEEE Third International Conference on Artificial Intelligence and Knowledge Engineering (AIKE) (pp. 116-119). IEEE.
Jafarian, J. H., Dincelli, E., Guzik, K., Michaelis, M., Banaei-Kashani, F., & Biswas, A. (2020). Deception against Deception: Toward A Deception Framework for Detection and Characterization of Covert Micro-targeting Campaigns on Online Social Networks. In Workshop on Information Security and Privacy (WISP)
Bekman, T., Abolfathi, M., Jafarian, H., Biswas, A., Banaei-Kashani, F., & Das, K. (2021, September). Practical Black Box Model Inversion Attacks Against Neural Nets. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (pp. 39-54). Springer, Cham.
Biswas, A. K., Verma, G., & Barber, J. O. (2021). Improving Ethical Outcomes with Machine-in-the-Loop: Broadening Human Understanding of Data Annotations. arXiv preprint arXiv:2112.09738.
Pastorino, J., Director, J. W., Biswas, A. K., & Hawbaker, T. J. (2022, April). Determination of optimal set of spatio-temporal features for predicting burn probability in the state of California, USA. In Proceedings of the 2022 ACM Southeast Conference (pp. 151-158).
Michaelis, M., Jafarian, J. H., & Biswas, A. (2022, June). The Dangers of Money and Corporate Power Relating to Online Disinformation. In 2022 23rd IEEE International Conference on Mobile Data Management (MDM) (pp. 470-475). IEEE.
Pastorino, J., & Biswas, A. K. (2022, August). Data adequacy bias impact in a data-blinded semi-supervised GAN for privacy-aware COVID-19 chest X-ray classification. In Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (pp. 1-8).
Mehrpour, O., Hoyte, C., Delva‐Clark, H., Al Masud, A., Biswas, A., Schimmel, J., ... & Goss, F. (2022). Classification of acute poisoning exposures with machine learning models derived from the National Poison Data System. Basic & Clinical Pharmacology & Toxicology, 131(6), 566-574.
Verma, G., Campbell, T., Biswas, A., Riley, J., Browning-Caraballo, T., Puvirajah, A. (2023, April). Informal STEM learning opportunities: Artificial intelligence and micro credentialing as a tool to recognize and develop Teens' STEM Identities. Presented as Poster in the Research in Artificial Intelligence-involved Science Education (RAISE) RIG at the 96th National Association for Research in Science Teaching (NARST) Annual Conference. Chicago, IL.
Mehrpour, O., Hoyte, C., Al Masud, A., Biswas, A., Schimmel, J., Nakhaee, S., ... & Goss, F. (2023). Deep learning neural network derivation and testing to distinguish acute poisonings. Expert Opinion on Drug Metabolism & Toxicology, 19(6), 367-380.
Talk at CU Denver, Data Science Symposium, Denver, Colorado, USA.
Talk at Colorado State University (CSU) Animal Imaging Workshop, Fort Collins, Colorado, USA.
Talk at CU Denver, Data Science Symposium, Denver, Colorado, USA.
Talk at Microsoft Visiting Data Science Educator Program (Summer 2022), Cohort 2, Remote
Talk at CU Denver, Data Science Symposium, Denver, Colorado, USA.