Experience
Research
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Sept. 2024 - Present Graduate Research Assistant
Vision Research Lab, UCSB Supervised by Professor B. S. Manjunath - Improve Visual Reasoning capabilities of Multi‑modal Large Language Models (LLM)
- Video Activity Recognition, focusing on identifying temporal interactions between subjects (e.g., humans, animals) with objects (e.g., cups, balls) in a scene, followed by grounding generation. (Preparing for CVPR’25)
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Jul. 2023 - Jun. 2024 Research Assistant
Institute of Robotics & Automataion, BUET (IRAB) Supervised by Dr. Shaikh Anowarul Fattah - Proposed a large‑scale dataset, human‑AI benchmarks, along with a efficient architecture for detecting synthetic/fake songs from platforms like Suno and Udio, which is highly time and memory efficient for long audio. (Submitted to ICLR’25)
- Enhance Robustness of Diffusion‑based Models (e.g. Inpainting) via Self‑Supervised Transformers
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Feb. 2022 - May 2023 Undergraduate Thesis
Dept. of EEE, BUET Supervised by Dr. Shaikh Anowarul Fattah - Designed a semi-supervised transformer enhancing semantic segmentation and depth estimation tasks through symbiosis and a dual compensating augmentation, ensuring object integrity, diversity, and controlled generation [WACV'24].
- Proposed local-global window transformers to mitigate trade-off between detailed & consistent depth map [IEEE JSEN'23].
- Introduced a dataset comprising 2.5 Million real vs. fake images (25 generators) and a novel multi-class strategy to detect both seen and unseen generators amid social-media impairments (compress and downsample) [ICIP'23].
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Feb. 2022 - May 2023 Research Collaboration
University of Texas at Dallas, Texas, USA (Remote) Supervised by Dr. Mohammad Saquib (Professor at UT Dallas) - Developed a semi-supervised ensemble technique to identify the algorithms responsible for generating synthetic speeches amidst perturbations, using mel-spectrogram features. [In Review at ICASSP'24].
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Apr. 2020 - Aug. 2020 Research Collaboration
Princeton University, New Jersey, USA (Remote) Supervised by Dr. Sun-Yuan Kung (Professor at Princeton University) - Proposed horizontal network expansion to reduce cost while maintaining good performance in COVID-19 lesion segmentation from CT scans; all codes, diagrams, and experiments implemented [IEEE TAI]
- Published Paper on IEEE Transactions on Artificial Intelligence (Q1)
- Paper - IEEE Xplore
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Dec. 2019 - Feb. 2022 Undergraduate Research Assistant
Robotics Lab, Dept. of EEE, BUET Jointly supervised by Lecturer Tanvir Mahmud, and Dr. Shaikh Anowarul Fattah - Introduced novel network for Melanoma diagnosis by concurrent multi-image comparison with patient-level contextual data.
- Proposed an efficient AF detection scheme to integrate raw ECG and discrete wavelet transformed features.
- Contributed by introducing stacking ensemble strategy, and implementing all codes, diagrams, experiments in "CovXNet" project.
Professional
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Jan. 2024 - Sept. 2024 Contractor
Google, Washington, USA (Remote) Supervised by Martin Görner (Product Manager for Keras and Tensorflow) - Develop code examples and tutorials for Kaggle competitions using Keras, focusing on Computer Vision and NLP tasks.
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Aug. 2021 - Sept. 2023 Developer Expert
Weights & Biases, California, USA (Remote) Supervised by Morgan McGuire (Director of Growth ML) - Testing WandB in ML projects, troubleshooting issues, optimization, and creating tutorials for effective tracking workflow.
- Integrated WandB pipeline into YOLOv5 and tested it for Underwater Object Detection. (Code - wandb)
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May 2021 - Jul. 2021 Collaboration with NVIDIA
NVIDIA, Santa Clara, USA (Remote) Collaborated with Dr. Chris Deotte (Senior data scientist at NVIDIA) - Worked on COVID-19 Detection and Localization from Chest X-Ray.
- Introduced a Semi-supervised Multi-Stage Transfer Learning scheme to detect abnormalities from limited data.
- Developed a fast BBox-Filter method to remove abnormal bounding boxes using statistical distribution.
- Won Best Student Team Award and ranked 4th globally in SIIM-FISABIO-RSNA COVID-19 Detection Competition.
- Code - GitHub | Video - YouTube
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Nov. 2019 - Present Kaggle Grandmaster
Kaggle Inc., San Francisco, USA (Remote) - Competed with professionals from leading companies like NVIDIA, HuggingFace, H20.ai, and more.
- Ranked 7th (best 5th) among 300,000 contenders and 1st in Bangladesh at the Code section.
- Won 36 Gold, 11 Silver medals in the Code section, and 1 Gold, 3 Silver medals in the Competition section.
Teaching
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2023 - Present MLDL-I - Machine Learning & Deep Learning I (Course + Lab)
IRAB, BUET Co-Creator and Co-Instructor - Theory and hands-on coding for Machine Learning & Deep Learning.
- ML - Backpropagation, Gradient Descent, (Regression, SVM, Tree, KNN) models, K-Means Clustering.
- DL - DNN, CNN, Architectures (VGG, Residual, Inception, Efficient), Image Classification/Segmentation.
- Misc - Data Leakage, Cross-Validation, Augmentation, TensorFlow coding.
- Code & Slide - GitHub.
Reviewer
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2020 - Present Journal/Conference Reviewer
- ICLR 2025 (International Conference on Learning Representations)
- NeurIPS 2024 (Conference on Neural Information Processing Systems)
- ICASSP 2025 (IEEE International Conference on Acoustics, Speech, and Signal Processing)
- WACV 2025 (Winter Conference on Applications of Computer Vision)
- BMVC 2024 (British Machine Vision Conference)
- ISBI 2024 (IEEE International Symposium on Biomedical Imaging)
- IEEE Journal of Translational Engineering in Health and Medicine (IF - 3.4)
- Elsevier Biomedical Signal Processing and Control (IF - 5.1)
- Nature Scientific Reports (IF - 4.4)
Open Source
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2019 - Present Author / Contributor
GitHub - Keras/TensorFlow - Added Conversion to multibackend (JAX/PyTorch),
DeBertaV3
classifier for MCQ task,GroupedQueryAttention
,pad_images
, andto_ordinal
. Ongoing -MelSpectogram
. (Code - GitHub) - gcvit-tf Created from scratch in TensorFlow, explained in a live notebook, converted model weights from PyTorch, and created a live demo. (Code - GitHub | Notebook - Kaggle | Space - HuggingFace)
- TransUnet-tf - Created from scratch in TensorFlow. (Code - GitHub | Notebook - Kaggle)
- LLM-Science-Exam - Multi-backend model for scientific questions using Keras-NLP classifiers for GPU & TPU, with a live notebook for use-case. (Code - GitHub | Notebook - Kaggle)
- audio-cls-models - Conformer and ContextNet papers in TensorFlow, converted from STT to an Audio Recognition task, used for Fake Speech Detection with a live notebook. (Code - GitHub | Notebook - Kaggle)
- LLM-Detect-AI-Generated-Text - Demonstrated synthetic text detection with multi-backend `DebertaV3`. (Code - GitHub | Notebook - Kaggle)
- HuggingFace - Detected and resolved a discretized depth issue in the NYU-Depth-V2 dataset. (PR - GitHub)
- YOLOv5 - Identified and resolved bug related to best model checkpointing. (PR - GitHub)
- Keras/TensorFlow - Added Conversion to multibackend (JAX/PyTorch),
Leadership
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2022 - 2023 Chairperson
IEEE EMBS BUET Student Branch Chapter - Organize IEEE EMBS Society's meetings, seminars, and workshops.
- Ensure member engagement and knowledge enhancement through society meetings.
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2021 - 2022 Secretary
IEEE EMBS BUET Student Branch Chapter - Ensure member engagement and knowledge enhancement through society meetings.
- Assist speakers and guests during these events.
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2019 - 2023 Class Representative (CR)
Section B, Batch 17, Dept. of EEE, BUET - Maintain class in absence of teacher, schedule quizzes, make announcements.
- Assist teacher in taking class seamlessly.
- Communicate as a channel between teacher and class.
Extracurricular
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2017 Physics Olympiad
Bangladesh Physics Olympiad (BdPhO) 10th in Divisional Round -
2015 Math Olympiad
Inter Shaheen Math Olympiad, Bangladesh Air Force Finalist (1st in Divisional Round) -
2014 Math Olympiad
Inter Shaheen Math Olympiad, Bangladesh Air Force Finalist (3rd in Divisional Round) -
2014 Science Fair
Ministry of Science and Technology, Chittagong Finalist (Project - Automatic Street Light Control)