Hello! 👋
I’m a Ph.D. candidate in Computer Science at Wayne State University, specializing in Computer Vision and Image Segmentation. As part of the Trustworthy AI Lab under Dr. Dongxiao Zhu, my research focuses on leveraging Vision-Language Models to enhance segmentation in Medical Imaging and Remote Sensing.
Currently, I’m a Graduate Research Assistant (GRA) in the Computer Science Department, where I explore AI-driven solutions for real-world challenges in trustworthy and interpretable machine learning.
Always open to collaboration and discussions—feel free to connect! 🚀
CONTACT:
I specialize in Computer Vision, specifically focusing on Image Segmentation. My expertise lies in two main areas: Bio-Medical Image Segmentation and Geographical Image Segmentation.
In the field of medical image segmentation, our objective is to accurately identify and segment tumors within different organs of the body, using various imaging modalities such as CT scans, MRI scans, and others.
Regarding geographical image segmentation, our goal is to develop a pedestrian network capable of segmenting different pedestrian objects, including roadways, sidewalks, crosswalks, and curb ramps.
This task is crucial for applications involving satellite/ aerial imagery. Our recent work on this area can be found here: "GeoSAM: Fine-tuning SAM with Sparse and Dense Visual Prompting for Automated Segmentation of Mobility Infrastructure",
Additionally, I also engage in algorithm optimization techniques as part of my work.
Rafi Ibn Sultan, Chengyin Li, Hui Zhu, Prashant Khanduri, Marco Brocanelli, Dongxiao Zhu, "GeoSAM: Fine-tuning SAM with Sparse and Dense Visual Prompting for Automated Segmentation of Mobility Infrastructure", arXiv preprint arXiv:2311.11319.
Chengyin Li, Prashant Khanduri, Yao Qiang, Rafi Ibn Sultan, Indrin Chetty, Dongxiao Zhu, "Auto-Prompting SAM for Mobile Friendly 3D Medical Image Segmentation", arXiv preprint arXiv:2308.14936.
Prashant Khanduri, Chengyin Li, Rafi Ibn Sultan, Yao Qiang, Joerg Kliewer, Dongxiao Zhu, "Proximal Compositional Optimization for Distributionally Robust Learning", The Second Workshop on New Frontiers in Adversarial Machine Learning, 2023.
Chengyin Li, Hassan Bagher-Ebadian, Rafi Ibn Sultan, Dongxiao Zhu, Indrin J. Chetty, "A New Architecture Combining Convolutional and Transformer-Based Networks for Automatic 3D Segmentation of Pelvic Anatomy on CT Images", AAPM(2023) American Association of Physicists in Medicine, 2023.
Chengyin Li, Yao Qiang, Rafi Lbn Sultan, Hassan Bagher-Ebadian, Prashant Khanduri, Indrin J. Chetty, Dongxiao Zhu, "FocalUNETR: A Focal Transformer for Boundary-aware Prostate Segmentation using CT Images", MICCAI(2023) International Conference on Medical Image Computing and Computer Assisted Intervention, 2023.
Md. Simul Hasan Talukder, Md. Nahid Hasan, Rafi Ibn Sultan, Dr. Ajay Krishno Sarkar, Dr. Mahabubur Rahman, "An Enhanced Method for Encrypting Image and Text Data Simultaneously using AES Algorithm and LSB-Based Steganography", 2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE), 2022.
Rafi Ibn Sultan, Md. Nahid Hasan, Mohammad Kasedullah,"Recognition of Basic Handwritten Math Symbols Using Convolutional Neural Network with Data Augmentation." 2021 5th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT). IEEE, 2021. (PDF)
Md Nahid Hasan, Rafi Ibn Sultan, and Mohammad Kasedullah. "An Automated System for Recognizing Isolated Handwritten Bangla Characters using Deep Convolutional Neural Network." 2021 IEEE 11th IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE). IEEE, 2021. (PDF)
Md. Jamil-Ur Rahman, Rafi Ibn Sultan, Firoz Mahmud, Sazid Al Ahsan, Abdul Matin, "Automatic System for Detecting Invasive Ductal Carcinoma Using Convolutional Neural Networks", 33rd TENCON 2018: 2018 IEEE Region 10 Conference, 28-31 October, 2018, Jeju, South Korea, IEEE. (PDF)
Md. Jamil-Ur Rahman, Rafi Ibn Sultan, Firoz Mahmud, Ashadullah Shawon, Afsana Khan,"Ensemble Of Multiple Models For Robust Intelligent Heart Disease Prediction System" , 4th IEEE International Conference on Electrical Engineering and Information and Communication Technology (ICEEICT 2018), 13-15 September, 2018, Dhaka, Bangladesh IEEE. (PDF)