Faculty Members Publications

The emergence of new and improved technological advances created severe problems in the security state of the educational certification system. Throughout this paper, a proposal has been made to improve security. Here, Blockchain technology has been introduced as reliable secure storage for the educational certification system, providing an additional facility to the users. That is the validation and authentication of the student’s academic records. Moreover, for security purposes, Blockchain technology can replace the traditional academic certification system and contribute to a new model for sharing student information. After completion of data inclusion and hashing, the blocks will be inserted into the Blockchain network. This proposed model enhances document security and fraud reduction and additionally reduces a significant amount of authentication time almost up to double the current speed. With this system, we will get a certification process in which all data will be digitalized and secured in an unbreakable database with proper authentication and with a noticeable amount of time efficiency.

Ovarian cancer (OC) is one of the most prevalent types of cancer in women. Early and accurate diagnosis is crucial for the survival of the patients. However, the majority of women are diagnosed in advanced stages due to the lack of effective biomarkers and accurate screening tools. While previous studies sought a common biomarker, our study suggests different biomarkers for the premenopausal and postmenopausal populations. This can provide a new perspective in the search for novel predictors for the effective diagnosis of OC. Genetic algorithm has been utilized to identify the most significant biomarkers. The XGBoost classifier is then trained on the selected features and high ROC-AUC scores of 0.864 and 0.911 have been obtained for the premenopausal and postmenopausal populations, respectively. Lack of explainability is one major limitation of current AI systems. The stochastic nature of the ML algorithms raises concerns about the reliability of the system as it is difficult to interpret the reasons behind the decisions. To increase the trustworthiness and accountability of the diagnostic system as well as to provide transparency and explanations behind the predictions, explainable AI has been incorporated into the ML framework. SHAP is employed to quantify the contributions of the selected biomarkers and determine the most discriminative features. Merging SHAP with the ML models enables clinicians to investigate individual decisions made by the model and gain insights into the factors leading to that prediction. Thus, a hybrid decision support system has been established that can eliminate the bottlenecks caused by the black-box nature of the ML algorithms providing a safe and trustworthy AI tool. The diagnostic accuracy obtained from the proposed system outperforms the existing methods as well as the state-of-the-art ROMA algorithm by a substantial margin which signifies its potential to be an effective tool in the differential diagnosis of OC.

Global food security is seriously threatened by plant diseases, which annually cause large losses in agricultural productivity. Early diagnosis and accurate classification of plant diseases are required for disease management programs to be implemented promptly and efficiently. In the area of plant disease classification, Convolutional Neural Networks (CNN) have demonstrated encouraging results in recent years. In this study, we propose a CNN based approach for plant disease classification using a MobileNetV2 based model and transfer learning. The proposed model leverages the MobileNetV2 architecture, known for its lightweight and efficient design, making it well-suited for resource-constrained environments. The pre-trained MobileNetV2 model is modified using transfer learning to accommodate the goal of classifying plant diseases. The model benefits from the characteristics that have been learned from a large-scale dataset through the use of pre-trained weights, leading to improved generalization and reduced training time. We use a standard plant disease dataset with a filtering method as a preprocessing strategy in extended trials to assess the efficiency of the proposed approach. The performance of the model is compared using several cutting-edge techniques, including VGG16, AlexNet and InceptionV3. The experimental findings show that the suggested model performs competitively in classifying plant diseases, surpassing other approaches with an accuracy of 98.56%.

In recent years, social media platforms, particularly twitter, have emerged as crucial sources of public opinion and sentiment. Analyzing sentiment on twitter data presents a significant challenge due to the platform's inherent characteristics, such as brevity, informality, and the prevalence of slang and emojis. This research paper proposes a method for twitter sentiment analysis by leveraging the power of a transformer-based model called RoBERTa. The proposed strategy employs RoBERTa due to its exceptional performance in various natural language processing tasks. Our system captures intricate contextual information and semantic nuances in tweets, making it well-suited for sentiment analysis on this challenging platform. To build an effective sentiment analysis system, the architecture is fine-tuned using a large corpus of twitter data, annotated with sentiment labels. Additionally, we explore various strategies to handle the unique characteristics of twitter data, including tokenization, handling hashtags, user mentions, and URLs, as well as the incorporation of emojis and emoticons. We compare the performance of our model with three other standard machine learning and deep learning models, such as Decision Tree (DT), Support Vector Machine (SVM), and Long Short Term Memory (LSTM) in order to show that our model is superior at correctly analyzing twitter sentiment. The model showcases an exceptional accuracy of 96.78%, highlighting its effectiveness in understanding and classifying sentiment within the context of tweets.

In the burgeoning landscape of e-commerce, the ability to accurately classify product texts is paramount for enhancing user experience and driving business success. Traditional approaches to text classification often struggle with the nuances and complexities inherent in e-commerce product descriptions. In this paper, we propose a novel approach utilizing Gated Recurrent Unit (GRU) to address these challenges and improve product understanding in e-commerce text classification tasks. Our model leverages the inherent sequential nature of product descriptions, effectively capturing long-range dependencies and semantic relationships within the text. We use a standard dataset in extended trials to demonstrate the superiority of our GRU-based approach over conventional methods in terms of classification accuracy and robustness across diverse product categories. Furthermore, we conduct comprehensive analyses to gain insights into the inner workings of our model and its ability to learn meaningful representations of e-commerce text data. The performance of the model is compared using several cutting-edge techniques, including Support Vector Machine (SVM), Random Forest (RF), and Long Short-Term Memory (LSTM) in order to show that our model is superior at correctly classifying e-commerce texts. The experimental findings show that the suggested model performs competitively in classifying e-commerce texts, surpassing other approaches with an accuracy of 98.35%. Our findings underscore the potential of GRU-based approaches for advancing the state-of-the-art in e-commerce text classification, offering promising avenues for future research and practical applications in the domain.

Nishat Tasnim, Asraf Ullah Rahat, Dr. Md. Musfique Anwar “Retrieving Top K% Relevant Patterns for Relation Extraction in Bangla using Distant Supervision”, International Conference on Signal Processing, Information, Communication and System (SPICSON) 2024. 

DOI:10.1109/SPICSCON64195.2024.10940594

Nishat Tasnim, Asraf Ullah Rahat, Tanjim Taharat Aurpa, Dr. Md. Musfique Anwar “Bangla-REX: A Distinct Dataset for Bangla Relation Extraction”, Data in Brief, 2025. 

https://doi.org/10.1016/j.dib.2025.111480

1. M. A. K. Rifat, A. Kabir, and A. Huq, “An Explainable Machine Learning Approach to Traffic Accident Fatality Prediction,” Procedia Computer Science, vol. 246, pp. 1905–1914, 2024, doi: https://doi.org/10.1016/j.procs.2024.09.704. ‌[Presented at the 28th International Conference on Knowledge Based and Intelligent Information and Engineering Systems (KES 2024), as part of a special issue.]

"Impact of Household Chores Situation on Female University Teachers in the Context of Bangladesh” [Single Authored]

Contemporary Issues in Business and Economics, August 2022 (1^st) Chapter 24. Publisher: RED’SHINE PUBLICATION 232, Bilton road, Perivale, Greenford Passcode: UB6 7HL London, UK. DOI: 10.25215/1387734229

“Respectability or Career: The Crisis of Female Academicians in Bangladesh” [1^st Author]

Gender Work and Organization 2025 Conference (GWO 2025), Nantes, France

Y. Sazid and K. Sakib

19th International Conference on Evaluation of Novel Approaches to Software Engineering | ENASE 2024

Y. Sazid, S. Kuri, K. S. Ahmed, and A. Satter

19th International Conference on Evaluation of Novel Approaches to Software Engineering | ENASE 2024

Y. Sazid, M. M. N. Fuad, and K. Sakib

30th Asia-Pacific Software Engineering Conference | APSEC 2023

1. "Subsidies and Inefficiency; a Stochastic Frontier Approach," Contemporary Economic Policy, vol. XV, July, 1997 (with Sakano and Obeng).
2. "Type of management and subsidy Induced Allocative Distortions in Urban Transit Firms --- A Time
   Series Approach", Journal of Transport Economics and Policy, Spring 1996. (with Kofi Obeng) 
3. "Allocative Distortions From Transit Subsidies", International Journal of Transport Economics, February 1995. (with Kofi Obeng) 
4. "The Intended Relationship Between Federal Operating Subsidy and Cost," Public Finance Quarterly, Vol. 23, No.1, January, 1995. 
5. "Sources of Change in U.S. Manufactured Exports during the Eighties", Journal of Economics and
   Finance, Vol. 18, Number 1, Spring 1994 (with Farida Azam). 
6. "Revisiting Relationship Between Growth and Poverty", Review of Black Political Economy, Vol. 22, No. 1, Summer 1993 (with Alonzo Redmon). 
7. "US Export Performance: 1978-1987" Proceedings of the Third Annual Symposium on International
   Economic competitiveness, Institute of International Economic Competitiveness, Radford University, March 23-25, 1990 (with Farida Azam).
8. Modeling Economic Inefficiency from Transit Subsidies, Praeger 1997 (with Kofi Obeng and Ryoichi
   Sakano). This is an advanced level book. 
9. Government Subsidies and Economic  Inefficiency in Public Transit (with Kofi Obeng). This research was done for the US Department of Transportation. The project was funded by the Federal Transit Administration, U.S. Department of Transportation, 1994. 
10. Terms of Trade for Jute: A Note" Bangladesh and UNCTAD V, ed. By K.M. Matin (Dhaka, Bangladesh: B.I.D.S., 1982) with S.R. Osmani, and Q.K. Ahmad. 
11. World Trade in Primary Commodities, the Case of Jute, Bangladesh Institute of Development Studies, Dhaka, Bangladesh, 1979. The project was funded by the Third World Forum.

OTHER PUBLICATIONS  

1. “Which Way is Liberal Democracy Headed”, The Independent, September 27, 2012. 
2. “The Making of Iraq War”, Daily Sun, January, 2012. 
3. "From Plassey to PRSP: The anatomy of poverty creation", The Daily Star, Vol. 5, Aug 2006. 
4. A Doctrinal History of US Foreign Policy: The Missing Link, Greensboro News & Record, January 2002. 
5. “Koran Foretells Inevitable Conflict – A Reply,” Greensboro News & Record, December 2001.

Conference Presentations/Participations/Other Professional Activities 

1. Keynote Speaker at the Golden Jubilee if the Victory Day of Bangladesh and China as the Development Partner of Bangladesh, December 18, 2023.
2. Member, International Best of Regions Award Committee, Accreditation Council for Business Schools and Programs, 2022 and 2023.
3. Evaluator, International Teaching Excellence Award, Accreditation Council for Business Schools and Programs, 2022.
4. Marketing Evolution in the Post Covit Scenario, presented at the Valedictory session, 4^th International Marketing Conference, SIES College of Management Studies, February 13, 2021.
5. Challenges in Higher Education, Annual Meeting of the Higher Education Forum held on December 7, 2019, in Mumbai, India. (Distinguished Speaker) 
6. ACBSP Annual Conference on the Art of Developing Entrepreneurial Leaders, held on June 21-24, 2019, in Houston, Texas, USA, USA.
7. ACBSP Annual Conference on Transforming Student Success through Recruitment, Retention, and Re-entry, June 8-11, Kansas City, Missouri, USA 
8. ACBSP Annual Conference on Preparing Students for Career Success, held on June 23-26, 2017, in Anaheim, California, USA.
9. "Rise of the West: Evidence from the Early Modern Period", East-West University, Dhaka Bangladesh, August 2005. 
10. "Subsidies and Inefficiency: A Stochastic Frontier Approach," with Sakano R. and K. Obeng. Presented at the Western Economic Association meeting held in San Francisco, June 29-July 2, 1996. 
11. "Transit subsidies, Allocative Distortion and Input Demand", with K. Obeng. Presented at the Western Economic Association meeting held in San Francisco, June 29-July 2, 1996.
12. "The Intended Relationship between Federal Operating Subsidy and Cost," with K. Obeng. Presented at the Southern Economic Association Meeting held in San Francisco, July 9-13, 1992.
13. "Government Debt and U.S. German Interest Rate Differential," with Faik Koray. Presented at the Western Economic Association Meeting held in San Francisco, July 9-13, 1992
14. "Twin Deficit Linkages, Some Empirical Results." Presented at the Eastern Economic Association Meeting, Cincinnati, Ohio, March 29-April 1, 1990.
15. "Real Factors in Exchange Rate Determination,” with Farida Azam. Presented at the Eastern Economic Association Meeting, Boston, Mass, March 10-12, 1988.
16. Discussant, Third Annual Symposium of the Institute for International Economic Competitiveness, College of Business and Economics, Radford University, Radford, Virginia, March 23-25, 1990.
17. Participant, Negotiated International Economic Change, Assessing Progress after UNCTAD V, Institute of Developing Studies, Sussex University, Brighton, U.K., June 2-29, 1979.

1. Guilford College Anti-Racism Team: 2003 - 2005. 
2. Greensboro Civic Entrepreneur Initiative: This project aimed to foster community participation in decision-making through leadership development. A three-year project, it was funded by the Pew Charitable Trust and hosted by the Community Foundation of Greensboro. Twenty Cities across the nation participated in it. I was a member of the steering committee.
3. ARC of Greensboro: For more than a decade I have been a member of ARC of Greensboro, an advocacy group for the mentally challenged, and have served as the Treasurer for several years.

1. Project title: Government Subsidy and Economic Efficiency 
2. Funding Agency: U.S. Department of Transportation. Grant amount: $80,802.00