Ashkan Sami
ashkan sami

Prof Ashkan Sami

  

Biography

Prof. Ashkan Sami, a faculty member in the Computer Science department at Edinburgh Napier University with an emphasis on Software Engineering, is dedicated to the use of foundation models for solving research problems in a broad spectrum of disciplines, including Software Engineering, medicine, and engineering.

In his academic journey, Prof. Sami has engaged in wide range of interdisciplinary and transdisciplinary research, striving to contribute meaningfully to these areas. His efforts have led to publications in respected journals and presentations at notable conferences. Prof. Sami has been honored with several national awards in industrial and applied research, acknowledging his contributions to the field.

From 2015 to 2020, Ashkan embraced the entrepreneurial world, leading his startup company. This experience has enriched his perspective in both academia and industry.

His work has gained media attention, including features in the BBC, The Register, and Stack Overflow team blogs, as well as international news outlets in China, Japan, Germany, and Spain.

Prof. Sami's academic achievements are distinguished by a Ph.D. from Tohoku University in Japan, obtained in 2006, which led to a significant research grant from MEXT and an assistant professorship at the university. His educational background also includes an M.Sc. in AI and Robotics from Shiraz University (1996) and a B.Sc. from Virginia Tech (1991).

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6 results

A case study of fairness in generated images of Large Language Models for Software Engineering tasks

Conference Proceeding
Sami, M., Sami, A., & Barclay, P. (2023)
A case study of fairness in generated images of Large Language Models for Software Engineering tasks. In 2023 IEEE International Conference on Software Maintenance and Evolution (ICSME). https://doi.org/10.1109/icsme58846.2023.00051
Bias in Large Language Models (LLMs) has significant implications. Since they have revolutionized content creation on the web, they can lead to more unfair outcomes, lack of i...

CoBRA without experts: New paradigm for software development effort estimation using COCOMO metrics

Journal Article
Feizpour, E., Tahayori, H., & Sami, A. (2023)
CoBRA without experts: New paradigm for software development effort estimation using COCOMO metrics. Journal of Software: Evolution and Process, 35(12), Article e2569. https://doi.org/10.1002/smr.2569
Software development effort estimation (SDEE) is a critical activity in developing software. Accurate effort estimation in the early phases of software design life cycle has i...

Application of Deep Learning in Generating Structured Radiology Reports: A Transformer-Based Technique

Journal Article
Moezzi, S. A. R., Ghaedi, A., Rahmanian, M., Mousavi, S. Z., & Sami, A. (in press)
Application of Deep Learning in Generating Structured Radiology Reports: A Transformer-Based Technique. Journal of Digital Imaging, https://doi.org/10.1007/s10278-022-00692-x
Since radiology reports needed for clinical practice and research are written and stored in free-text narrations, extraction of relative information for further analysis is di...

De novo design of novel protease inhibitor candidates in the treatment of SARS-CoV-2 using deep learning, docking, and molecular dynamic simulations

Journal Article
Arshia, A. H., Shadravan, S., Solhjoo, A., Sakhteman, A., & Sami, A. (2021)
De novo design of novel protease inhibitor candidates in the treatment of SARS-CoV-2 using deep learning, docking, and molecular dynamic simulations. Computers in Biology and Medicine, 139, Article 104967. https://doi.org/10.1016/j.compbiomed.2021.104967
The main protease of SARS-CoV-2 is a critical target for the design and development of antiviral drugs. 2.5 M compounds were used in this study to train an LSTM generative net...

An Empirical Study of C++ Vulnerabilities in Crowd-Sourced Code Examples

Journal Article
Verdi, M., Sami, A., Akhondali, J., Khomh, F., Uddin, G., & Karami Motlagh, A. (2022)
An Empirical Study of C++ Vulnerabilities in Crowd-Sourced Code Examples. IEEE Transactions on Software Engineering, 48(5), 1497-1514. https://doi.org/10.1109/tse.2020.3023664
Software developers share programming solutions in Q&A sites like Stack Overflow, Stack Exchange, Android forum, and so on. The reuse of crowd-sourced code snippets can facili...

Malware detection based on mining API calls

Conference Proceeding
Sami, A., Yadegari, B., Rahimi, H., Peiravian, N., Hashemi, S., & Hamze, A. (2010)
Malware detection based on mining API calls. In SAC '10: Proceedings of the 2010 ACM Symposium on Applied Computing (1020-1025). https://doi.org/10.1145/1774088.1774303
Financial loss due to malware nearly doubles every two years. For instance in 2006, malware caused near 33.5 Million GBP direct financial losses only to member organizations o...

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