STAR Lab: Sustainable Technology and Applications Research  Lab

Projects

Data Driven Approaches for Blood Glucose Management, Meal Management

• Benzir Md Ahmed, Mohammed Eunus Ali, Mohammad Mehedy Masud, Mohammed Raihan Azad, and Mahmuda Naznin, After-Meal Blood Glucose Level Prediction for Type-2 Diabetic Patients, Heliyon, Elsevier, vol. 10, issue-7, (Impact Factor- 4), April, 2024, https://www.cell.com/heliyon/pdf/S2405-8440(24)04886-2.pdf

• Benzir Md Ahmed, Mohammad Mehedy Masud, Mohammed Eunus Ali, and Mahmuda Naznin, Recent Trends and Techniques of Blood Glucose Level Prediction for Diabetes Control, Smart Health, Elsevier, vol. 32, June, 2024 (Impact Factor- 4.9)

Medical Imaging: 

• Stress Prediction from Bone Image/Cellular Image Analysis

This research project aims to predict the morphological stress and structure analysis from human bone from dicom image of bone. Deep learning based framework can provide a good prediction.

Publication:

• Rabina Awal, Mahmuda Naznin, Tanvir R. Faisal, Machine Learning Based Finite Element Analysis (FEA) Surrogate for Hip Fracture Risk Assessment and Visualization, Expert System with Applications, Elsevier, (Impact Factor 7.5), (accepted), 2025

• Rabina Awal, Mahmuda Naznin, Sarah Doll, Tanvir R. Faisal, Interpretable Machine Learning Classifiers for the Reliable Prediction of Fall Induced Hip Fracture Risk, Machine Leaning for Computaional Science and Engineering, Springer, 2025

• Jamalia Sultana, Mahmuda Naznin,  Tanvir R. Faisal, SSDL–An Efficient Automated Semi-supervised Deep Learning Approach for Patient-specific 3D Reconstruction of Proximal Femur from QCT Images, Medical and Biological Engineering and Computing, Springer (Impact Factor-3.2), 2024 

• Jamalia Sultana, Mashiyat Nayeem, Mahmuda Naznin,  Tanvir R. Faisal, Semi-Supervised Learning Based Femur Segmentation from QCT Images, in Proc. of IEEE 22nd International Conference on Machine Learning and Applications (ICMLA), IEEE, Florida, USA, 2023 

• Jamalia Sultana, Mahmuda Naznin, Tanvir R. Faisal, Automated Femur Isolation In CT Scan Images By Generating Binary Mask-a Critical Step For 3d Femur Reconstruction, Annual Orthopedic Research Society (ORS) Conference, Dallas, Texas, 2023 

• Dipannoy Das Gupta, Mahmuda Naznin, Tanvir R. Faisal, An Automated Approach for 3D Reconstruction of Femur from CT Data via Pixel Clustering, 17th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering, Bonn, Germany, 2021. 

• Saad Maznur, Mohammad Shaown, Mahmuda Naznin, and Tanvir R. Faisal, Perception Thresholding for Noise Removal in Micrographs of Cellular Tissues Obtained from Fluorescence Microscopy, in Proceedings of IMECE, American Society of Mechanical Engineers (ASME), Pittsburgh, PA, USA, 2018. 

Cognitive Data and Science: 

• Emotion Detection from Voice Data in Multi-lingual Framework 

This research project aims to find human emotion or mental state from voice data. The framework can find the different emotional states based on different features extracted from voice data.

Publication: 

• Jamalia Sultana and Mahmuda Naznin, Breaking the Barrier with a Multi-Domain SER, IEEE COMPSAC, June 2022

• Nazia Hossain, and Mahmuda Naznin, Finding Emotion from Multi-Lingual Voice Data, in Proceedings of IEEE COMPSAC,  Madrid, Spain, 2020 (Best Paper Award).

Quality of Service:

• Resource Provisioning for Virtual Environment 

This project aims to forecast virtual network functions, vCPU using Machine Learning. Virtual resource planning optimizes cost in cloud computing and enhance QoS. 

Publication: 

• Zakia Zaman, Fazle Rafsani, Ishrak R Rahman, Sabidur Rahman, Mahmuda Naznin, DeepVRM: Deep Learning Based Virtual Resource Management for Energy Efficiency, Journal of Network and Systems Management, Springer, vol. 31, issue 4, July, 2023 (Impact Factor- 3.6),  https://doi.org/10.1007/S10922-023-09752-1

• Zakia Zaman, Sabidur Rahman, and Mahmuda Naznin, A Novel Approach for VNF Requirement Prediction Using DNN and LSTM, in Proceedings of IEEE Globecom,  Hawaii, USA,  2019.  

• Secured Content Caching in Named Data Network

In this project  aims to provide a secured and efficient content caching strategy for Named Data Network.   

Publication:

• Ms. Mina, Dipannoy Das Gupta, Mahmuda Naznin, LBCC: A Load Balanced Collaborative Caching in Content Based Networking, in Proc. of IEEE UEMCON,  NY, USA, 2023, https://doi.org/10.1109/UEMCON59035.2023.10316034

• Dipannoy Das Gupta, Pranta Biswas, and Mahmuda Naznin, CacheQueue: Efficient Cache Queue Usage in a NDN, IEEE COMPSAC, June 2022

• Abdullah Al Fuad, Sfiullah Sabuj, Zunayed Ahsan, and Mahmuda Naznin, RLB: Randomized load balanced packet forwarding strategy in name based data networking, in Proceedings of The 4th International Conference on Network Systems and Security (NSysS), IEEE, Dhaka, Bangladesh, 2017. 

People

( I have got the opportunity to learn through collaboration with Faculty/Industry people) 

Prof. Alim al Islam, Dept. of CSE, BUET

Prof. Mohammad Mehedy Masud, College of Information Technology, United Arab Emirates University

Dr. Tanvir R. Faisal, 4MLab@ULL (https://www.4mlab.net/),  University of Louisiana, USA

Dr. Suparno Bahar Moni,  Assistant Professor (Orthopedic Surgery), University of Toledo, Ohio, USA

Dr. Sabidur Rahman, AT&T Labs Inc., USA

Current Graduate Students 

Md. Benzir Ahmed, PhD Candidate

Tanjina Helaly, PhD Candidate

Jannatul Fedous Ruma, PhD Student, joined 

Manriul, PhD Student (Co-supervised)  

Mohuwa Paul, MS Candidate

Shreshta Pramanik , MS Student

Shantana Mridha, MS Student

Nazmul Hasan, MS Student

Md. Shakibuzzaman, MS Student (joined)

Undergraduate Thesis Students

 5 Undergraduate Thesis Students (4th year, CSE, BUET)