News

• New!  June 2026: Successfully defended my Ph.D. dissertation at The University of Texas at Austin! 🎓
• New!  May 2026: Invited Talk: Efficient and Reliable AI for Real-World Healthcare Deployment at the AI, ML, and Computer Vision Meetup. Watch Recording.
• New!  April 2026: Selected as a 2026 MLCommons ML & Systems Rising Star (Acceptance Rate 22.9%)
• New!  November 2025: Our paper on Adaptive Vision GNN with Exponential Decay Gating (AdaptViG) accepted to WACV 2026.
• New!  October 2025: Our paper on Optimal Vision GNNs via Ramanujan Spectral Optimization (SearchViG) accepted to LOG 2025.
• New!  October 2025: Our research on efficient AI for 3D medical imaging featured in UT ECE News.
• New!  September 2025: Our paper on Learnable Weighted Multi-Scale Logits Mixing for Medical Image Segmentation (LoMiX) accepted to NeurIPS 2025.
• August 2025: Invited Talk: EffiDec3D: An Optimized Decoder for High-Performance and Efficient 3D Medical Image Segmentation at the AI, ML, and Computer Vision Meetup. Watch Recording.
• July 2025: Our paper introducing ultra-lightweight 2D CNN-based architecture (MK-UNet) accepted to ICCV 2025 CVAMD Workshop as an Oral talk.
• July 2025: Our paper on improved hybrid 2D CNN-Transformer architecture (EDLDNet) accepted to Biomedical Signal Processing and Control.
• July 2025: Received the 🏆 MIDL 2025 Travel Award to attend and present PRIME in Salt Lake City.
• July 2025: Received the 🏆 MICCAI 2025 NIH Travel Award to attend and present EfficientMedNeXt in Daejeon, with support for main conference and satellite registrations, plus MICCAI Society membership.
• June 2025: Our paper on lightweight 3D segmentation (EfficientMedNeXt) accepted to MICCAI 2025 with 🏆 Highlight award (top 4.87% of submissions).
• May 2025: I have joined GE Healthcare, San Ramon as a 2025 AI/ML PhD Intern.
• April 2025: Received the 🏆 CVPR 2025 Broadening Participation Award to attend and present our recent work, EffiDec3D, at CVPR in Nashville.
• Read more…

  • October 2025: Presented a poster at iMAGiNE Consortium at AMD on Training-Free Dataset Pruning for Polyp Segmentation via Community Detection in Similarity Networks.
  • September 2025: Our efficient 3D segmentation paper (EfficientMedNeXt) received the 🏆 Highlight badge at MICCAI 2025 (top 4.87% of submissions).
  • July 2025: Attended MIDL 2025 and delivered an Oral talk on our paper, PRIME, on data efficient AI.
  • July 2025: Invited Talk: Training-Free Dataset Pruning for Polyp Segmentation via Community Detection in Similarity Networks at San Ramon Journal Club, GE Healthcare.
  • June 2025: Invited Talk: EffiDec3D: An Optimized Decoder for High-Performance and Efficient 3D Medical Image Segmentation at San Ramon Journal Club, GE Healthcare.
  • June 2025: Attended CVPR 2025 and presented our two papers (EffiDec3D and From Data to Design).
  • June 2025: Attended Stanford AI Week 2025 with an in-person attendance scholarship (AIMI, RAISE, and Pediatric AIMI Symposiums).
  • May 2025: Selected to participate in the MIDL 2025 Doctoral Symposium in Salt Lake City.
  • April 2025: Invited Talk: Towards Efficient AI for Biomedical Imaging: Reducing Computation and Data Demands at Stanford MedAI. Watch Recording.
  • April 2025: Our efficient 3D segmentation paper (EffiDec3D) received the 🏆 Highlight award at CVPR 2025 (top 2.98% of submissions).
  • April 2025: Guest Lecture: Deep Learning in Biomedical Imaging at ECE379K: Machine Learning and Data Analytics for EdgeAI course, UT Austin.
  • March 2025: Our paper on data-driven architecture (From Data to Design) accepted to CVPRW 2025 on Efficient Large Vision Models.
  • March 2025: Our paper addressing data inefficiency by applying community detection in image similarity network (PRIME) accepted to MIDL 2025 as Oral talk.
  • February 2025: Our paper on efficient 3D segmentation (EffiDec3D) accepted to CVPR 2025 with 🏆 Highlight award (top 2.98% of submissions).
  • February 2025: Attended UT System Trauma Research Symposium 2025.
  • January 2025: Presented a poster at GAIN 2025 on Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation.
  • December 2024: One paper on 2D medical image segmentation (MDNet) accepted to ICASSP 2025.
  • October 2024: Our collaborative research with Dell Med on Biomedical imaging featured in UT News.
  • October 2024: One paper introducing computationally efficient vision model (RapidNet) accepted to WACV 2025.
  • September 2024: One abstract (Few-shot Image Denoising) accepted to EPFL Latsis Symposium on Smart Microscopy 2024 from internship at NIH.
  • August 2024: Invited Talk: Gave a talk at NHLBI, NIH on Efficient Deep Learning for Biomedical Imaging.
  • August 2024: Presented a poster at NIH on Universal Light Microscopy Denoising via Lightweight Multi-scale Convolutional Transformer.
  • July 2024: Won 🏆 The Texas Health Catalyst Award 2024 for our Medical Image Segmentation via Cascaded Attention Decoding.
  • May 2024: I have joined Office of AI Research (OAIR), NHLBI, NIH as 2024 Summer IRTA Fellow to work with Sarah Hopper and Christian Combs.
  • April 2024: One paper addressing the robustness of finetuning vision foundation model for polyp segmentation (PP-SAM || [Code]) accepted to CVPRW 2024 on Domain adaptation Explainability and Fairness in AI for Medical Image Analysis.
  • March 2024: Received the prestigious 🏆 Summer IRTA Fellowship from Office of AI Research (OAIR), NHLBI, NIH to work with Sarah Hopper, Christian Combs, and Hui Xue.
  • February 2024: Two papers introducing efficient multi-scale convolutional attention-based decoder for 2D medical image segmentation (EMCAD || [Code]) and dynamic graph construction-based vision backbone (GreedyViG || [Code]) accepted to CVPR 2024.
  • January 2024: Presented a poster at GAIN 2024 on Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation.
  • August 2023: One paper introducing a graph convolution-based decoder for 2D medical image segmentation (G-CASCADE) accepted to WACV 2024.
  • July 2023: Received 🏆 Professional Development Award by the Graduate School, UT Austin.
  • May 2023: Spending Summer 2023 in Robert Bosch Research, Pittsburgh as Machine Learning Reseach Intern.
  • April 2023: Won the 🏆 Ram’s Horn Best Project Award in Digital Video course by Prof. Alan Bovik, UT Austin.
  • March 2023: Received the 🏆 Best Poster Award (for CASCADE) by Graduate and Industry Networking (GAIN 2023), UT Austin.
  • March 2023: Presented a poster at GAIN 2023 on Medical Image Segmentation via Cascaded Attention Decoding.
  • March 2023: One paper introducing a multi-scale hierarchical network and combinatorial supervision (MERIT) accepted to MIDL 2023.
  • October 2022: One paper introducing the first convolutational attention-based decoding (CASCADE) accepted to WACV 2023.
  • May 2022: Received the 🏆 Feldman Graduate Research Fellowship, The University of Texas at Austin.
  • January 2022: I have started the Doctor of Philospohy in Electrical and Computer Engineering, The University of Texas at Austin (UT Austin). I have joined the System Level Design Group (SLD) advised by Prof. Radu Marculescu.

Selected Publication [Full List]

2025

• New!  [WACV 2026]   AdaptViG: Adaptive Vision GNN with Exponential Decay Gating.
  Mustafa Munir, Md Mostafijur Rahman, Radu Marculescu.
  2026 IEEE/CVF Winter Conference on Applications of Computer Vision
  [Paper] [arxiv] [Code]
• New!  [NeurIPS 2025]   LoMix: Learnable Weighted Multi-Scale Logits Mixing for Medical Image Segmentation.
  Md Mostafijur Rahman, Radu Marculescu.
  2025 Advances in Neural Information Processing Systems
  [Paper] [arxiv] [Code]
• New!  [MICCAI 2025]   EfficientMedNeXt: Multi-Receptive Dilated Convolutions for Medical Image Segmentation.
  Md Mostafijur Rahman, Mustafa Munir, Radu Marculescu.
  🏆 Highlight
  2025 International Conference on Medical Image Computing and Computer Assisted Intervention
  [Paper] [Code]
• New!  [CVPR 2025]   EffiDec3D: An Optimized Decoder for Efficient High-Performance 3D Medical Image Segmentation.
  Md Mostafijur Rahman, Radu Marculescu.
  🏆 Highlight
  Proceedings of the 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition
  [Paper] [Code]
• New!  [ICCV 2025]   MK-UNet: Multi-kernel Lightweight CNN for Medical Image Segmentation.
  Md Mostafijur Rahman, Radu Marculescu.
  🏆 Oral
  Proceedings of the 2025 International Conference on Computer Vision Workshops
  [Paper] [arxiv] [Code]
• New!  [MIDL 2025]   Training-Free Dataset Pruning for Polyp Segmentation via Community Detection in Similarity Networks.
  Md Mostafijur Rahman, Radu Marculescu.
  🏆 Oral
  Medical Imaging with Deep Learning
  [Paper] [Code]
• New!  [LOG 2025]   SearchViG: Optimal Vision GNNs via Ramanujan Spectral Optimization.
  Mustafa Munir, Md Mostafijur Rahman, Xiwen Wei, Yuedong Yang, Radu Marculescu.
  2025 Learning on Graphs Conference
  [Paper] [arxiv] [Code]
• [WACV 2025]   RapidNet: Multi-Level Dilated Convolution Based Mobile Backbone.
  Mustafa Munir, Md Mostafijur Rahman, and Radu Marculescu.
  🏆 GAIN Best Poster Award 2025
  Proceedings of the 2025 IEEE/CVF Winter Conference on Applications of Computer Vision
  [Paper] [arxiv] [Code]
• [CVPR 2025]   From Data to Design: Leveraging Frequency Statistics for Efficient Neural Network Architectures.
  Mustafa Munir, Guihong Li, Md Mostafijur Rahman, Radu Marculescu.
  Proceedings of the 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops
  [Paper]
• [J-BPSC 2025]   An Efficient Dual-Line Decoder Network with Multi-Scale Convolutional Attention for Multi-organ Segmentation.
  Riad Hassan, M. Rubaiyat Hossain Mondal, Sheikh Iqbal Ahamed, Fahad Mostafa, Md Mostafijur Rahman.
  Biomedical Signal Processing and Control
  [Paper] [Code]
• [ICASSP 2025]   MDNet: Multi-Decoder Network for Abdominal CT Organs Segmentation.
  Debesh Jha, Nikhil Kumar Tomar, Koushik Biswas, Gorkem Durak, Matthew Antalek, Zheyuan Zhang, Bin Wang, Md Mostafijur Rahman, Hongyi Pan, Alpay Medetalibeyoglu, Yury Velichko, Daniela Ladner, Amir Borhani, Ulas Bagci.
  Proceedings of the 2025 IEEE International Conference on Acoustics, Speech, and Signal Processing
  [Paper] [arxiv] [Code]

2024

• [CVPR 2024]   EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation.
  Md Mostafijur Rahman, Mustafa Munir, and Radu Marculecu.
  Proceedings of the 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition
  [Paper] [arxiv] [Code]
• [CVPR 2024]   GreedyViG: Dynamic Axial Graph Construction for Efficient Vision GNNs.
  Mustafa Munir, William Avery, Md Mostafijur Rahman, and Radu Marculecu.
  Proceedings of the 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition
  [Paper] [arxiv] [Code]
• [CVPR 2024]   PP-SAM: Perturbed Prompts for Robust Adaptation of Segment Anything Model for Polyp Segmentation.
  Md Mostafijur Rahman, Mustafa Munir, Debesh Jha, Ulas Bagci, and Radu Marculescu.
  Proceedings of the 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops
  [Paper] [arxiv] [Code]
• [WACV 2024]   G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation.
  Md Mostafijur Rahman, Radu Marculescu.
  Proceedings of the 2024 IEEE/CVF Winter Conference on Applications of Computer Vision
  [Paper] [arxiv] [Code]

2023

• [MIDL 2023]   Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation.
  Md Mostafijur Rahman, Radu Marculescu.
  Medical Imaging with Deep Learning
  [Paper] [arxiv] [Code]
• [WACV 2023]   Medical Image Segmentation via Cascaded Attention Decoding.
  Md Mostafijur Rahman, Radu Marculescu.
  🏆 GAIN Best Poster Award 2023; 🏆 The Texas Health Catalyst Award 2024; 🏆 UT Proof of Concepts Award 2025; 🏆 NSF I-corps Award 2025
  Proceedings of the 2023 IEEE/CVF Winter Conference on Applications of Computer Vision
  [Paper] [Code]

< 2022

• [SIGSPATIAL GeoAI 2021]   Mapping Road Safety Barriers Across Street View Image Sequences: A Hybrid Object Detection and Recurrent Model.
  Md Mostafijur Rahman, Arpan Man Sainju, and Zhe Jiang.
  2021 ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery
  [Paper]
• [ICIEV 2019]   Bangla Handwritten Basic Character Recognition Using Deep Convolutional Neural Network.
  Chandrika Saha, Rahat Hossain Faisal, and Md Mostafijur Rahman.
  Proceedings of the 2019 International Conference on Informatics, Electronics, and Vision
  [Paper]
• [J-SIVP 2018]   MCCT: a Multi-channel Complementary Census Transform for Image Classification.
  Md Mostafijur Rahman, Shanto Rahman, and Mohammad Shoyaib.
  Signal, Image and Video Processing
  [Paper]
• [JIVP 2017]   DTCTH: a Discriminative Local Pattern Descriptor for Image Classification.
  Md Mostafijur Rahman, Shanto Rahman, Rayhanur Rahman, Mainul Hossain, and Mohammad Shoyaib.
  EURASIP Journal on Image and Video Processing
  [Paper]
• [JIVP 2016]   An Adaptive Gamma Correction for Image Enhancement.
  Shanto Rahman, Md Mostafijur Rahman, M. Abdullah-Al-Wadud, Golam Dastegir Al-Quaderi, and Mohammad Shoyaib.
  Used by NIH in MIPAV API
  EURASIP Journal on Image and Video Processing
  [Paper]
• [ICCIT 2015]   Noise Adaptive Binary Pattern for Face Image Analysis.
  Md Mostafijur Rahman, Shanto Rahman, Minhas Kamal, M. Abdullah-Al-Wadud, Emon Kumar Dey, and Mohammad Shoyaib.
  🏆 Best Paper Award
  Proceedings of the 2015 International Conference on Computer and Information Technology
  [Paper]

Awards

• MIDL Travel Award, MIDL - July 2025
• MICCAI NIH Travel Award, MICCAI - July 2025
• CVPR Broadening Participation Award, CVPR - June 2025
• NSF I-corps Award (team member), National Science Foundation (NSF) - 2025–2026
• Stanford AIMI In-person Attendance Scholarship, Stanford AIMI - June 2025
• Proof of Concepts Award (team member), The University of Texas at Austin - 2025
• Texas Health Catalyst Award (team member), The University of Texas at Austin - 2024
• IRTA Fellowship, Office of AI Research (OAIR), National Institutes of Health (NIH) - Summer 2024
• Professional Development Award, The University of Texas at Austin - July 2023
• Ram’s Horn Best Project Award, The University of Texas at Austin - May 2023
• Best Poster Award, Graduate and Industry Networking (GAIN), The University of Texas at Austin - March 2023
• Feldman Graduate Research Fellowship, The University of Texas at Austin - Summer 2022
• Graduate Council Research Fellowship, The University of Alabama, Tuscaloosa - 2021
• Innovation Award, Access to Information (A2I), Prime Minister’s Office, Bangladesh - 2018
• Research Grant, University Grants Commission (UGC), Bangladesh - 2017-2018
• Best Paper Award (1st Prize), Int. Conference on Computer and Information Technology (ICCIT) - December 2015
• Graduate Research Fellowship, Ministry of Information and Communication Technology, Bangladesh - 2015-2016

Teaching Experience

Jan 2022 – May 2022
The University of Texas at Austin (UT Austin)
Graduate Teaching Assistant, Department of Electrical and Computer Engineering
— Course: EE319K Introduction to Embedded Systems by Dr. Jonathan Valvano
Dec 2020 – Jan 2021
University of Barishal (BU), Bangladesh
Assistant Professor, Department of Computer Science and Engineering
— Supervised student research and projects on artificial intelligence.
Sep 2016 – Dec 2020
University of Barishal (BU), Bangladesh
Lecturer, Department of Computer Science and Engineering
— Designed and taught courses: Programming Fundamentals | Object Oriented Programming | Artificial Intelligence | Digital Image Processing | Discrete Mathematics
– Supervised student research and projects

Professional Experience

May 2025 – Present
GE Healthcare, San Ramon, CA, USA
AI/ML PhD Intern
— Advised by: Dr. Bruno Astuto A. Nunes and Dr. Ravi Soni
— Working on Lightweight/Efficient AI and Medical Image Analysis
Jan 2022 – Present
The University of Texas at Austin (UT Austin)
Graduate Research Assistant, Department of Electrical and Computer Engineering
— Advised by: Dr. Radu Marculescu
— Working on Medical Imaging, Computer Vision, Lightweight/Efficient AI, Generative AI, and Multi-modal AI
May 2024 – Aug 2024
National Institutes of Health (NIH)
Summer IRTA Fellow, National Heart, Lung, and Blood Institute (NHLBI)
— Advised by: Dr. Sarah Hooper and Dr. Christian Combs
— Worked on Lightweight/Efficient AI for universal light microscopy image denoising
May 2023 – Aug 2023
Bosch Research, Pittsburgh, USA
Machine Learning Research Intern
— Advised by: Dr. Chaithanya Kumar Mummadi and Dr. Filipe Condessa
— Worked on monocular/single-image depth prediction with deep learning
Jan 2021 – Aug 2021
The University of Alabama, Tuscaloosa
Graduate Research Assistant, Department of Computer Science
— Advised by: Dr. Zhe Jiang
— Worked on deep learning, image processing, and spatial data mining
May 2016 – Sep 2016
Samsung Research, Bangladesh
Senior Software Engineer, Advanced Solution Group
— R&D on Android applications for autistic children
Jan 2015 – May 2016
University of Dhaka, Bangladesh
Graduate Research Assistant, Institute of Information Technology
— Advised by: Dr. Mohammad Shoyaib
— Worked on machine learning, image processing, and pattern recognition
Jan 2014 – Jun 2014
Progoti Systems Ltd. (SureCash), Bangladesh
Software Engineer Intern, Software Engineering Division
— Developed large-scale web apps (SureCash web) and Android applications

Advising & Mentoring

• Riad Hassan (MS, Bangladesh University of Engineering and Technology (BUET). Current: Green University of Bangladesh)
  — Co-authored a Journal of Biomedical Signal Processing and Control article
• SM Nuruzzaman Nobel (BS, Bangladesh University of Business & Technology (BUBT). Current: Monash University Malaysia)
• Abu Saem Shefatullah (BS, BU. First job: Google)
  — Coached ICPC’2018, ICPC’2019
• Chandrika Saha (BS, BU. First job: Outlier)
  — Co-authored ICISET’2018, ECCE’2019, ICIEV’2019
• Umme Habiba (BS, BU. First job: Green University of Bangladesh)
  — Co-authored ECCE’2019, ICIEV’2019
• Md Rasel Howlader (BS, BU)
  — Co-authored ECCE’2019
• Md Aminul Islam (BS, BU)
  — Co-authored IC4ME2’2019
• Sharmin Sultana (BS, BU)
  — Co-authored ICASERT’2019
• Nazifa Akter (BS, BU)
  — Co-authored ICASERT’2019
• Badal Chandra Mitra (BS, BU)
  — Co-authored IC4ME2’2019
• Ayesha Akter (BS, BU)
  — Co-authored IC4ME2’2019
• Sadia Khan Rupa (MS, Bangladesh University of Professionals (BUP))
• Samiul Islam Jehad (BS, BU. First job: Enosis Solutions)
  — Coached ICPC’2017

Academic Services

Conference Reviewer
ICLR 2026, ICCV 2025, MICCAI 2025, CVPR 2025, ICLR 2025, ISBI 2025, WACV 2025, NeurIPS 2024, MICCAI 2024, CVPR 2024, WACV 2024, ISBI 2024, WACV 2023
Journal Reviewer
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), IEEE Transactions on Medical Imaging (TMI), Medical Image Analysis (MedIA), IEEE Transactions on Image Processing (TIP), Pattern Recognition Letters, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Computers in Biology and Medicine, Expert Systems with Applications, PLOS ONE
Shadow Reviewer
WACV 2026, CVPR 2025, NeurIPS 2023, NeurIPS 2022, IEEE Transactions on Medical Imaging (TMI)

Presentations

Sep 2025
Highlight Poster
EfficientMedNeXt: Multi-Receptive Dilated Convolutions for Medical Image Segmentation
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Daejeon, South Korea
Sep 2025
Invited Talk
EfficientMedNeXt: Multi-Receptive Dilated Convolutions for Medical Image Segmentation
San Ramon Journal Club, GE Healthcare
Aug 2025
Invited Talk
EffiDec3D: An Optimized Decoder for High-Performance and Efficient 3D Medical Image Segmentation
The AI, ML, and Computer Vision Meetup, Voxel51 Events
Aug 2025
Internship Talk
Lightweight Architecture for Edge-AI
GE Healthcare, San Ramon, California
Jul 2025
Invited Talk
Training-Free Dataset Pruning for Polyp Segmentation via Community Detection in Similarity Networks
San Ramon Journal Club, GE Healthcare
Jul 2025
Highlight Poster
Training-Free Dataset Pruning for Polyp Segmentation via Community Detection in Similarity Networks
Medical Imaging with Deep Learning (MIDL), Salt Lake City, Utah
Jul 2025
Conference Talk
Training-Free Dataset Pruning for Polyp Segmentation via Community Detection in Similarity Networks
Medical Imaging with Deep Learning (MIDL), Salt Lake City, Utah
Jun 2025
Invited Talk
EffiDec3D: An Optimized Decoder for High-Performance and Efficient 3D Medical Image Segmentation
San Ramon Journal Club, GE Healthcare
Jun 2025
Highlight Poster
EffiDec3D: An Optimized Decoder for Efficient High-Performance 3D Medical Image Segmentation
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, Tennessee
Jun 2025
Poster
From Data to Design: Leveraging Frequency Statistics for Efficient Neural Network Architectures
IEEE/CVF CVPR Workshops, Nashville, Tennessee
Apr 2025
Invited Talk
Towards Efficient AI for Biomedical Imaging: Reducing Computation and Data Demands
Stanford MedAI
Apr 2025
Poster
EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation
iMAGiNE Consortium, The University of Texas at Austin (UT Austin)
Apr 2025
Guest Lecture
Deep Learning in Biomedical Imaging
ECE379K (Machine Learning and Data Analytics for EdgeAI), The University of Texas at Austin (UT Austin)
Jan 2025
Poster
Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation
Graduate and Industry Networking Event (GAIN), UT Austin
Aug 2024
Invited Talk
Efficient Deep Learning for Biomedical Imaging
National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH)
Aug 2024
Internship Poster
Universal Light Microscopy Denoising via Lightweight Multi-scale Convolutional Transformer
National Institutes of Health (NIH)
Aug 2024
Internship Talk
Universal Light Microscopy Denoising via Lightweight Multi-scale Convolutional Transformer
Office of AI Research (OAIR), National Institutes of Health (NIH)
Jun 2024
Poster
EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, Washington
Jun 2024
Poster
GreedyViG: Dynamic Axial Graph Construction for Efficient Vision GNNs
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, Washington
Jun 2024
Poster
PP-SAM: Perturbed Prompts for Robust Adaptation of Segment Anything Model for Polyp Segmentation
IEEE/CVF CVPR Workshops, Seattle, Washington
Jan 2024
Poster
G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation
Graduate and Industry Networking Event (GAIN), UT Austin
Jan 2024
Poster
G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii
Aug 2023
Internship Poster
Single Image Depth Prediction with Deep Scene Regularization
Bosch Center for Artificial Intelligence (BCAI), Pittsburgh
Jul 2023
Poster
Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation
Medical Imaging with Deep Learning (MIDL), Nashville, Tennessee
Jul 2023
Spotlight Talk
Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation
Medical Imaging with Deep Learning (MIDL), Nashville, Tennessee
Mar 2023
Poster
Medical Image Segmentation via Cascaded Attention Decoding
iMAGiNE Consortium, The University of Texas at Austin (UT Austin)
Jan 2023
Poster
Medical Image Segmentation via Cascaded Attention Decoding
Graduate and Industry Networking Event (GAIN), UT Austin
Jan 2023
Poster
Medical Image Segmentation via Cascaded Attention Decoding
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii
Dec 2015
Conference Talk
Noise Adaptive Binary Pattern for Face Image Analysis
International Conference on Computer and Information Technology (ICCIT), Dhaka, Bangladesh

Contact