Usman ahmed
I am the last year PhD student in Computer science under the supervision of Dr. Prof. Jerry Chun-Wei Lin (IET Fellow) at department of computer science, electrical engineering, and mathematical sciences, Western Norway University of Applied Sciences, Bergen, Norway.
My general interests lie in active learning, distributed optimization, and effective deep learning methods. I concentrate on acquiring a foundational understanding of distributed and data driven modelling with their interactions with diverse sources of heterogeneity, including variations in the computational infrastructure and inconsistencies in training data. Motivated by these theoretical findings, my objective is to develop practical and efficient distributed and federated training algorithms. This website serves as a platform to showcase my work, share my knowledge, and connect with like-minded professionals in the field of data science.
Latest News (All News):
- (13/04/2023) New paper out - Semi-Supervised Lexicon-Aware Embedding for News Article Time Estimation
- (05/04/2023) Going to attend “Sustainability and democratic practices” at Bergen Summer Research School (BSRS) 2023
Books
Book: Hands-on Exploratory Data Analysis with Python: Perform EDA Techniques to Understand, Summarize, and Investigate Your Data. by Suresh Kumar Mukhiya and Usman Ahmed. Packt Publishing, 2020. Link
Book: Data analytics, Python - Advanced Exploratory Data Analysis With Python - Under Publication, expected early 2023- Manning Publications Co. by Suresh Kumar Mukhiya and Usman Ahmed.
Research Highlights:
- Data pipeline workflows
- Expertise in Generative LLMs
- Custom BERT based Temporal news hyperpatism detection 1.
- Healthcare-focused EHR information extraction 2.
- Pre-processing domain-specific training data 3.
- Fine-tuning pre-trained language models 4.
- Evaluating and refining model performance 5.
- Adapting LLM techniques across industries to fine-tuned domain-specific outputs 6.
- Experience with distributed systems
- AWS/ Cloud services
Highly scalable systems
- Scalable video analytics tool.
- R-CNN, efficient object detection.
- Dynamic frame skipping, low-latency.
- Parallel processing, interdisciplinary collaboration.
- Projects: 1, 2, 3, 4, and 5.
Collaborated with cross-functional teams
- Collaborated with researchers, experts including Norwegian companies next green farming and TL Måkestad (TLM).
- Engaged stakeholders, cross-functional teams.
- Developed algorithms, coordinated data, pipeline integration, and visualization.
Research groups
- Intelligent Knowledge Engineering (IKE) lab
- Duration: Oct 2019 - Current.
- Led by Dr Prof. Jerry Chun-Wei Lin (IET Fellow).
- Cooperated with many distinguished researchers from different (20+) countries.
- Published more than 500+ peer-review papers regarding several major subjects, including data mining and pattern analytics, machine learning, optimization, AI, soft computing, fuzzy-set theory, privacy-preserving and security, and federated learning.
- HVL Data Science Group
- Duration: Oct 2019 - Current.
- Focused on theoretical data science applications for energy, biology, and physics.
- Organizing workshops, seminars, conferences, meetings, and collaborations.
- Artificial Intelligence and Computer Vision Lab (iVision)
- Duration: April 2019 - September 2019.
- Established under the department of Electrical Engineering & Computer Science, Institute of Space Technology, Islamabad.
- Hosts a friendly and research-intensive environment with a strong workplace culture and brings together researchers across the areas of computer vision, machine learning, and signal processing.
- Parallel Computing and Network Research Lab (PCN)
- Duration: March 2016 - July 2018.
- Includes various related aspects such as parallel & distributed computing, IP, wireless, ad-hoc networks.
- Extended its scope to temporal information retrieval, social network analysis, and online privacy issues.
Selected Publications
Journal
Usman Ahmed, Jerry Chun-Wei Lin, and Gautam Srivastava. “Semisupervised Federated Learning for Temporal News Hyperpatism Detection.” IEEE Transactions on Computational Social Systems (2023). IF: 4.7, JCR: Q1, and Norwegian ranking: R1.
Usman Ahmed, Jerry Chun-Wei Lin, and Gautam Srivastava. “Social Media Multiaspect Detection by Using Unsupervised Deep Active Attention.” IEEE Transactions on Computational Social Systems (2022). IF: 4.7, JCR: Q1, and Norwegian ranking: R1.
Usman Ahmed, and Jerry Chun-Wei Lin. “Deep Explainable Hate Speech Active Learning on Social-Media Data.” IEEE Transactions on Computational Social Systems (2022). IF: 4.7, JCR: Q1, and Norwegian ranking: R1.
Usman Ahmed, Jerry Chun-Wei Lin, and Vicente Garcia Diaz. “Automatically Temporal Labeled Data Generation Using Positional Lexicon Expansion for Focus Time Estimation of News Articles.” ACM Transactions on Asian and Low-Resource Language Information Processing (2022). IF: 1.47, JCR: Q2, and Norwegian ranking: R1.
Usman Ahmed, Rutvij H. Jhaveri, Gautam Srivastava, and Jerry Chun-Wei Lin. “Explainable deep attention active learning for sentimental analytics of mental disorder.” Transactions on Asian and Low-Resource Language Information Processing (2022). IF: 1.9, JCR: Q2, and Norwegian ranking: R1.
Usman Ahmed, Jerry Chun-Wei Lin, Gautam Srivastava. “Mitigating Adversarial Evasion Attacks by Deep Active Learning for Medical Image Classification.” Multimedia Tools and Applications 81, no. 29 (2022): 41899-41910. IF: 2.3, JCR: Q2, and Norwegian ranking: R1.
Conference
Usman Ahmed, Jerry Chun-Wei Lin. “Sequence-Driven Analytics and Prediction.” In Proceedings of the 31st ACM International Conference on Information \& Knowledge Management, pp. 5104-5107. (2022). Core: A.
Usman Ahmed, Jerry Chun-Wei Lin, Stefania Tomasiello, and Gautam Srivastava. “Explainable Mental Health Fuzzy Deep Active Learning Technique.” In 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 1-8. IEEE, (2022). Core: B.
For more information
More info about Usman Ahmed can be found in CV or downloaded CV.