Loneliness is one of the strongest predictors of attrition and underperformance among international students, yet most arrive without a strategy for building the support systems that would prevent it. This chapter argues that durable social networks abroad have to be designed rather than stumbled into. The chapter pairs the comfort-zone-to-growth-zone model with concrete strategies for diversifying connections beyond co-national circles: joining clubs and organizations, seeking faculty mentors, working with International Student Services advisors, volunteering in the local community, and intentionally cultivating cross-cultural friendships. It treats co-national clustering with care; bonding ties matter. The chapter also argues that students who build bridging ties early enjoy measurable gains in belonging, academic outcomes, and post-graduation networks. The chapter also takes seriously the role AI chatbots are now playing in everyday emotional support and offers a clear-eyed account of what they can and cannot replace. The case study of Yingze Ma, a Chinese undergraduate studying physiology at the University of Alberta, traces a “wake-up call” moment and the slow rebuild that followed. Readers come away with a network blueprint and the language to explain why building one is a communication skill, not a personality test.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
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