Abstract Background Psychosis, social anxiety, and autism are clinical constructs that share important phenotypic features, particularly social dysfunction. A critical determinant of social functioning is an individual’s ability to recognize when social cues, such as eye gaze, are meant for them. Emerging computational modeling data in psychosis suggest that altered gaze perception stems from deficits in evidence accumulation – the process of gathering and integrating information – when processing social cues. We investigated whether aberrant evidence accumulation during gaze perception is associated with social functioning or, as a secondary aim, with psychopathology in a transdiagnostic sample with varying levels of psychotic, socially anxious, or autistic characteristics. Methods We examined gaze perception in 111 individuals (aged 14–30) with varying levels of social dysfunction, psychosis proneness, social anxiety, and autistic traits. Drift diffusion models (DDM) characterized key processes driving perceptual judgements in a self-referential gaze perception task, including the efficiency of evidence accumulation. We tested whether evidence accumulation was associated with social functioning, social cognition, and these different psychopathology dimensions. Results Impaired evidence accumulation during gaze perception showed strong associations with impaired social cognition and modest associations with diminished social functioning and elevated psychosis and social anxiety symptoms. Evidence accumulation was not associated with autism traits. Conclusions Evidence accumulation for social cues relates to social cognition – a key determinant of social functioning. It may also be relevant to real-world social functioning and multiple psychopathology dimensions, including psychosis and social anxiety. Therefore, evidence accumulation should be investigated as a mechanism supporting social difficulties and related psychopathology.
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al.· IEEE Transactions on Softwar...· 178 citations· ⚡14
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.
M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al.· e-Informatica Software Engin...· 157 citations· ⚡17
This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al.· Empirical Software Engineeri...· 127 citations· ⚡15
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
The application of agile software methods and more recently the integration of Lean practices contribute to the trend of continuous improvement in the software industry. One such area warranting proper empirical evidence is a project’s operational efficiency when using the Kanban method. This short paper takes a new angle and explores waste in the Kanban-driven software development project context. A preliminary research model is presented for helping the consequent replication of the study. The results from the empirical analysis suggest Kanban can be an effective method in visualizing and organizing the current work, but does not prevent waste from creeping in, although the overall project outcome may be successful.
Marko Ikonen, Petri Kettunen, Nilay V. Oza et al.· EUROMICRO Conference on Soft...· 67 citations· ⚡9
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduSep 14, 2026
The “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.
AI may appear weightless, but every model depends on physical infrastructure. To understand responsible AI, we need to look beyond algorithms and consider the entire lifecycle of the hardware behind them. The post Responsible AI Must Consider Its Afterlife appeared first on GPT-Lab.