Publications
Selected publications
- An explainable AI decision-support-system to automate loan underwriting (Journal article - 2020)
- A Blockchain Framework in Compliance with Data Protection Law to Manage and Integrate Human Knowledge by Fuzzy Cognitive Maps: Small Business Loans (Conference Paper - 2023)
- Blockchain-based auditing of legal decisions supported by explainable AI and generative AI tools (Journal article - 2024)
- Human-AI Collaboration to Mitigate Decision Noise in Financial Underwriting: A Study on FinTech Innovation in a Lending Firm (Journal article - 2024)
- Evidential reasoning for preprocessing uncertain categorical data for trustworthy decisions: An application on healthcare and finance (Journal article - 2021)
2024
Optimal Data-Driven Strategy for In-House and Outsourced Technological Innovations by Open Banking APIs
Dezem, V., Sachan, S., Macedo, M., & Andrade Longaray, A. (n.d.). Optimal data-driven strategy for in-house and outsourced technological innovations by open banking APIs. Future Business Journal, 10(1). doi:10.1186/s43093-024-00397-3
Secure and Transparent Lawyer-in-the-Loop Medico-Legal Insurance Decisions by Explainable AI and Blockchain Technology
Sachan, S., & Fairclough, G. (2024). Secure and Transparent Lawyer-in-the-Loop Medico-Legal Insurance Decisions by Explainable AI and Blockchain Technology. In S. Li (Ed.), 10th International Conference on Information Management (ICIM) Vol. 2102. University of Cambridge: Springer Nature Switzerland AG. doi:10.1007/978-3-031-64359-0_3
Human-AI Collaboration to Mitigate Decision Noise in Financial Underwriting: A Study on FinTech Innovation in a Lending Firm
Sachan, S., Almaghrabi, F., Yang, J. -B., & Xu, D. -L. (2024). Human-AI Collaboration to Mitigate Decision Noise in Financial Underwriting: A Study on FinTech Innovation in a Lending Firm. International Review of Financial Analysis. doi:10.1016/j.irfa.2024.103149
Blockchain-based auditing of legal decisions supported by explainable AI and generative AI tools
Sachan, S., & Liu (Lisa), X. (2024). Blockchain-based auditing of legal decisions supported by explainable AI and generative AI tools. Engineering Applications of Artificial Intelligence, 129, 107666. doi:10.1016/j.engappai.2023.107666
Blockchain for Ethical and Transparent Generative AI Utilization by Banking and Finance Lawyers; at World Conference on eXplainable Artificial Intelligence (XAI)
Sachan, S., Dezem, V., & Fickett, D. (2024). Blockchain for Ethical and Transparent Generative AI Utilization by Banking and Finance Lawyers. In Unknown Conference (pp. 319-333). Springer Nature Switzerland. doi:10.1007/978-3-031-63800-8_16
2023
The Future of Money: What We Need To Know
Sachan, S. (2023). The Future of Money: What We Need To Know. Retrieved from https://e.issuu.com/embed.html?d=well_connected_july_23&u=benham
A Blockchain Framework in Compliance with Data Protection Law to Manage and Integrate Human Knowledge by Fuzzy Cognitive Maps: Small Business Loans
Sachan, S., Fickett, D. S., Kyaw, N. E. E., Purkayastha, R. S., & Renimol, S. (2023). A Blockchain Framework in Compliance with Data Protection Law to Manage and Integrate Human Knowledge by Fuzzy Cognitive Maps: Small Business Loans. In 2023 IEEE INTERNATIONAL CONFERENCE ON BLOCKCHAIN AND CRYPTOCURRENCY, ICBC. doi:10.1109/ICBC56567.2023.10174925
Integration of Explainable Deep Neural Network with Blockchain Technology: Medical Indemnity Insurance
Sachan, S., & Muwanga, J. (2023). Integration of Explainable Deep Neural Network with Blockchain Technology: Medical Indemnity Insurance. In CEUR Workshop Proceedings Vol. 3554 (pp. 123-128).
2022
Fintech Lending Decisions: An Interpretable Knowledge-Base System for Retail and Commercial Loans
Sachan, S. (2022). Fintech Lending Decisions: An Interpretable Knowledge-Base System for Retail and Commercial Loans. In Communications in Computer and Information Science (pp. 128-140). Springer International Publishing. doi:10.1007/978-3-031-08974-9_10
2021
Evidential reasoning for preprocessing uncertain categorical data for trustworthy decisions: An application on healthcare and finance
Sachan, S., Almaghrabi, F., Yang, J. -B., & Xu, D. -L. (2021). Evidential reasoning for preprocessing uncertain categorical data for trustworthy decisions: An application on healthcare and finance. EXPERT SYSTEMS WITH APPLICATIONS, 185. doi:10.1016/j.eswa.2021.115597
2020
Global and local interpretability of belief rule base
Sachan, S., Yang, J. B., & Xu, D. L. (2020). Global and local interpretability of belief rule base. In Unknown Book (Vol. 12, pp. 68-75). Retrieved from https://www.webofscience.com/
Explainable Artificial Intelligence for Digital Forensics: Opportunities, Challenges and a Drug Testing Case Study
Kelly, L., Sachan, S., Ni, L., Almaghrabi, F., Allmendinger, R., & Chen, Y. -W. (n.d.). Explainable Artificial Intelligence for Digital Forensics: Opportunities, Challenges and a Drug Testing Case Study. In Digital Forensic Science. IntechOpen. doi:10.5772/intechopen.93310
Generalized Stochastic Petri-Net Algorithm with Fuzzy Parameters to Evaluate Infrastructure Asset Management Policy
Sachan, S., & Donchak, N. (2020). Generalized Stochastic Petri-Net Algorithm with Fuzzy Parameters to Evaluate Infrastructure Asset Management Policy. In 2020 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE). doi:10.1109/fuzz48607.2020.9177562
An explainable AI decision-support-system to automate loan underwriting
Sachan, S., Yang, J. -B., Xu, D. -L., Benavides, D. E., & Li, Y. (2020). An explainable AI decision-support-system to automate loan underwriting. EXPERT SYSTEMS WITH APPLICATIONS, 144. doi:10.1016/j.eswa.2019.113100
2019
Maximum likelihood evidential reasoning-based hierarchical inference with incomplete data
Liu, X., Sachan, S., Yang, J. -B., & Xu, D. -L. (2019). Maximum Likelihood Evidential Reasoning-Based Hierarchical Inference with Incomplete Data. In 2019 25TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND COMPUTING (ICAC) (pp. 42-47). doi:10.23919/iconac.2019.8895062
Multi-segment deep convolution neural networks for classification of faults in sensors at railway point systems
Sachan, S., & Donchak, N. (2019). Multi-Segment Deep Convolution Neural Networks for Classification of Faults in Sensors at Railway Point Systems. In 2019 25TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND COMPUTING (ICAC) (pp. 147-152). doi:10.23919/iconac.2019.8895081
Probabilistic dynamic programming algorithm: a solution for optimal maintenance policy for power cables
Sachan, S., & Zhou, C. (2019). Probabilistic dynamic programming algorithm: a solution for optimal maintenance policy for power cables. Life Cycle Reliability and Safety Engineering, 8(2), 117-127. doi:10.1007/s41872-019-00074-3
2018
A hybrid belief rule based decision support system for assessing credit risk for mortgage lending
Sachan, S., Yang, J. -B., & Xu, D. -L. (2018). A hybrid belief rule based decision support system for assessing credit risk for mortgage lending. In https://www.euro-online.org/media_site/reports/EURO29_AB.pdf.
Comments from young scholars: Can machines completely replace humans in manufacturing processes?
Yang, S. (2018). Comments from young scholars: Can machines completely replace humans in manufacturing processes?. FRONTIERS OF ENGINEERING MANAGEMENT, 5(4), 541-547. doi:10.15302/J-FEM-2018207
2017
Multiple Correspondence Analysis to Study Failures in a Diverse Population of a Cable
Sachan, S., Zhou, C., Wen, R., Sun, W., & Song, C. (2017). Multiple Correspondence Analysis to Study Failures in a Diverse Population of a Cable. IEEE TRANSACTIONS ON POWER DELIVERY, 32(4), 1696-1704. doi:10.1109/TPWRD.2016.2615470
2016
Cost Effective Replacement of Power Cables by Stochastic Dynamic Programming Approach
Sachan, S., Zhou, C., Bevan, G., & Alkali, B. (2016). Cost Effective Replacement of Power Cables by Stochastic Dynamic Programming Approach. In 2016 INTERNATIONAL CONFERENCE ON CONDITION MONITORING AND DIAGNOSIS (CMD) (pp. 299-302). Retrieved from https://www.webofscience.com/
Stochastic dynamic programming approach for proactive replacement of power cables
Sachan, S., Chengke Zhou, C. Z., Bevan, G., & Alkali, B. (2016). Stochastic dynamic programming approach for proactive replacement of power cables. In CIRED Workshop 2016 (pp. 80 (4 .)). Institution of Engineering and Technology. doi:10.1049/cp.2016.0680
2015
Failure prediction of power cables using failure history and operational conditions
Sachan, S., Zhou, C., Bevan, G., & Alkali, B. (2015). Failure prediction of power cables using failure history and operational conditions. In 2015 IEEE 11th International Conference on the Properties and Applications of Dielectric Materials (ICPADM) (pp. 380-383). IEEE. doi:10.1109/icpadm.2015.7295288
Prediction of power cable failure rate based on failure history and operational conditions
Sachan, S., Zhou, C., Bevan, G., & Alkali, B. (2015). Prediction of power cable failure rate based on failure history and operational conditions. In http://www.jicable.org/2015/prg_sessions_A1_E10.php. Versailles, France.
A stochastic electrothermal degradation model of power cables
Sachan, S., Wen, R., Xiang, Y., Yao, L., & Zhou, C. (2015). A stochastic electrothermal degradation model of power cables. Gaodianya Jishu/High Voltage Engineering, 41(4), 1178-1187. doi:10.13336/j.1003-6520.hve.2015.04.015