Professor & Expert in Software and AI-Engineering | SE4AI, AI & Machine Learning & MLOps | Quality Assurance Specialist | Researcher & Speaker
Karlstad, Sweden
Joined October 2009
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Proud to share our new paper in JSS! 🎉
An MLOps + AI-driven digital twin to make steel production smarter, greener & more efficient.
🔗 doi.org/10.1016/j.jss.2025.1…
#SmartManufacturing #MLOps #AI
🎯 Model-Based Testing gets AI upgrade! 2025 brings automated test scenario generation from user stories. Smart coverage that adapts in real-time 🧠✨ #ModelBasedTesting #TestGeneration #QualityEngineering #AI #testing #TestAutomation
⬅️ Shift-Left testing is the new QA superpower! Catch bugs early when they cost pennies, not millions. Early detection = faster delivery = happier devs 🔧
#ShiftLeft #QualityEngineering #DevOps #Testing #TechTrends2025
I've identified the most engaging and tweetable insights from the latest AI research. Here are 15 carefully crafted tweet drafts that balance technical depth with accessibility:
Tweet 4:🌍 "World Models" trained on massive video datasets are learning REAL-WORLD PHYSICS!
This could be the biggest AI breakthrough since ChatGPT. Imagine AI that truly understands how the physical world works.
Game. Changer. 🚀
#WorldModels #AI #Physics #MachineLearning
Tweet 5:💊 AI is CRUSHING drug discovery timelines! Machine learning models predict compound efficacy, slashing years off development.
From disease markers in genomics to literature analysis—AI is becoming the ultimate research accelerator. 🧬
#AIHealthcare #DrugDiscovery
Bestoun S. Ahmed retweeted
Happening now at ITEQS'25: Firas is presenting their paper on "Quality Assurance for LLM-RAG Systems: Empirical Insights from Tourism Application Testing."
Bestoun S. Ahmed retweeted
Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach. arxiv.org/abs/2410.21346
🎉 Our paper on Trustworthy ML in Production has been accepted in ACM Computing Surveys! With @Firas__P , we provide a comprehensive overview of robustness in MLOps - from automation to DataOps and ModelOps.
Read it here: arxiv.org/abs/2410.21346
#MLOps #AI #TrustworthyAI
In the era of AI and rapid development of technology and research, letting an article be under review for 2.5 years is really not acceptable; that means, as an editor, you are not doing your job. #Journal
🚀 Researchers are making AI faster and more reliable by "shrinking" LLMs through smart compression techniques. This boosts speed and enhances fairness and trustworthiness in AI decisions. Learn more about this exciting advancement! arxiv.org/abs/2401.05561 #AI #Tech #Innovation
New research in Nature reveals a surprising AI pitfall: training models on AI-generated data can cause "model collapse," leading to nonsense outputs over time. nature.com/articles/d41586-0… #AIResearch #ML #DataScience #ArtificialIntelligence #GenerativeAI
🎉 Excited to share our paper, "Adaptive Data Quality Scoring Operations Framework using Drift-Aware Mechanism for Industrial Applications," is accepted in @JSSoftware🚀 Check it out here: arxiv.org/pdf/2408.06724 #AI #DataQuality #Research #SoftwareEngineering #AI
Our paper "IoT Anomaly Detection Methods and Applications: A Survey" has been selected as an Editor's Choice in the March 2024 edition! 🏆📜
This recognition highlights the high impact of our work within the IoT community over the past two years.
Want to know more about how optimization algorithms can adapt in real-time to changing environments? My latest paper, "An Adaptive Metaheuristic Framework for Changing Environments," has just been accepted for publication on this topic! Download here arxiv.org/abs/2404.12185