Md Abdus Sahid
Pronouns: he/him/his
About
I am 🍓 Md Abdus Sahid better known as Sahid Saif, 🎓 graduated from the Computer Science and Engineering Department ⊆ Hajee Mohammad Danesh Science and Technology University (HSTU) in November 2023 where I am advised by Professors Dr. Md Palash Uddin and Hasi Saha. This bachelor phase, additionally, unlocked the door to research for me.
Open to Collaboration
I would love to collaborate on research in federated learning, large language models, machine learning, and their interplays, with the aim of submitting our work to top venues such as ICML, ICLR, NeurIPS, AAAI, JMLR, ACL, COLING, COLT, NAACL, EMNLP etc. Feel free to reach me if you want.
Research
I am consistently enthusiastic about designing straightforward and well-founded algorithms that are applicable, scalable, and adaptable to real-world challenges. The genuine fascination in this area stems, moreover, from what we can do when we integrate advanced learning techniques with a system. My research interest is on federated learning, large language models, and machine learning, examining their interplay with the aim of making impactful contributions to industry.
Federated Learning
In federated learning, a machine learning framework, multiple entities (clients) collaborate under the guidance of a central server or service provider to tackle machine learning tasks. Each client maintains its raw data locally, refraining from sharing or transferring it. Instead, they transmit focused updates, which are promptly aggregated to collectively achieve the learning objective. Federated learning, however, faces formidable challenges, notably in communication efficiency, data heterogeneity, computational constraints, privacy and security, and so on. My goal is to overcome these hurdle.
Research Topics
- Federated Learning: Communication Efficiency, Personalization, and Heterogeneity.
- Large Language Models: Fine-tuning, Personalization, Bias and Fairness, and Hallucination.
Awards
Dean's List 2021, Issued by CSE Faculty, HSTU.
Activities
During the period from 2018 to 2020, I have participated in the Technocracy 2019 and NCPC 2020 onsite programming contests. Additionally, I have taken part in numerous online programming contests on various platforms such as Codeforces, Codechef, and UVa in that period. Furthermore, I have served on the program committees of Programmers Arena in 2019, 2020, and 2022.
Vita
đź“ŤFor the most up-to-date information, kindly refer to my sterling Curriculum Vita .
FutureTech Analytics Research Lab (FARL)
Center for Multidisciplinary Research and Development (CeMRD)
Hajee Mohammad Danesh Science and Technology University
Clarification for the prolonged timeframe: (i) Academic union strike actions for nearly 3.5 months to achieve their demands in 2018. (ii) Furthermore, the COVID-19 pandemic exacerbated the situation.
Service
Journal Reviewer
- Artificial Intelligence in Medicine [Elsevier]
- Computers in Biology and Medicine [Elsevier]
- Database: The Journal of Biological Databases and Curation [Oxford University Press]
- Expert Systems with Applications [Elsevier]
- International Journal of Medical Informatics [Elsevier]
- Neurocomputing [Elsevier]
Conference Reviewer
- The 6th International Conference on Machine Learning and Intelligent Systems (MLIS 2024), Kampar, Perak, Malaysia.
News
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Nov 30, 2024
I am invited to serve as a reviewer for the International Journal of Medical Informatics.
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Nov 25, 2024
I am invited to serve as a reviewer for the Computers in Biology and Medicine journal.
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Oct 8, 2024
💡 Journal paper “Towards Privacy-Preserving Alzheimer’s Disease Classification: Federated Learning on T1-weighted MRI Data” has accepted in Digital Health (Sage Publisher).
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Aug 30, 2024
💡 Conference paper “Enhancing Parallelism in Cross-silo Federated Learning for Brain Disease Classification” has accepted in 2024 IEEE Conference on Computing, Applications, and Systems (COMPAS).
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Jul 9, 2024
I’m thrilled to share that I received the Dean’s List award in my final year of undergraduate studies.
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Jun 1, 2024
I am invited to serve as a reviewer for several journals, including Artificial Intelligence in Medicine, Database: The Journal of Biological Databases and Curation, Expert Systems with Applications, and Neurocomputing.
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Apr 28, 2024
I am invited to serve as a reviewer for the 6th International Conference on Machine Learning and Intelligent Systems (MLIS 2024).
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Mar 18, 2024
đź’ˇ My first combined first author journal paper Performance discrepancy mitigation in heart disease prediction for multisensory inter-datasets is published in PeerJ Computer Science.
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Mar 5, 2024
💡 Journal paper “Predictive modeling of multi-class diabetes mellitus using machine learning and filtering iraqi diabetes data dynamics” has accepted in PLOS ONE.
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Feb 12, 2024
💡 Journal paper “Performance Discrepancy Mitigation in Heart Disease Prediction for Multi-sensory Inter-Datasets” has accepted in PeerJ Computer Science.
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Jun 18, 2023
I will deliver a lecture on the topics of the curse of dimensionality and dimensionality reduction techniques at the CSE department of HSTU.
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Aug 29, 2022
đź’ˇ My first conference paper Effect of Imbalance Data Handling Techniques to Improve the Accuracy of Heart Disease Prediction using Machine Learning and Deep Learning is published in IEEE.
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Jul 5, 2021
Participated in Technocracy 2019, an inter-university programming contest hosted by RUET.
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Feb 20, 2020
Participated in National collegiate programming contest 2020, an inter-university programming contest hosted by MIST.
