Nariman Mani

Nariman Mani, Salma Attaranasl

Digital lifestyle coaching systems must personalize peer support as user behavior and engagement evolve while preventing personally identifiable information (PII) and sensitive health information from leaking into analytics and AI pipelines. This creates a practical tension: personalization requires longitudinal linkability, while privacy engineering requires minimization, separation, and controlled re-identification. We present PRISM-Coach, a stakeholder-centered architecture and adaptive peer-group assignment method for privacy-preserving lifestyle coaching. PRISM-Coach separates each user into four bounded views: Identity, Operational, Learning, and Coaching, each with distinct access controls and risk profiles. Building on this separation, the system uses vault-based controlled identity restoration, a privacy-constrained contextual bandit to assign users to eligible peer groups under coach-capacity and stability constraints, and a human-in-the-loop coaching assistant that generates de-identified summaries and draft messages without sending raw PII or PHI to external AI services. We instantiate PRISM-Coach in a commercially deployed lifestyle coaching platform and evaluate it using three years of telemetry from approximately 2,800 users and an in-app needs assessment survey. At the population level, daily check-in adherence increases from 0.35 to 0.68, and engagement rises to 1.35 baseline. In a matched 19-week comparison window, the AI-enabled workflow achieves adherence of 0.74 versus 0.48 under static grouping and higher average weight loss: 5.2 kg versus 3.1 kg. Survey results show that 82% report positive perceived benefit, and 92% report increased privacy confidence after transparency disclosures. These results position PRISM-Coach as a practical blueprint for privacy-by-design adaptive learning systems in everyday wellness.

Xiaozhou Li, Nariman Mani, Jose Sosa Rodriguez et al.

Microservice-based systems impose significant organizational coordination challenges, yet the role of individual developers in shaping organizational coupling (OC) remains underexplored. Prior work largely focuses on structural architectural aspects, leaving gaps in understanding how developer roles influence coordination dynamics over time. This study investigates how different developer roles contribute to OC in a large-scale microservices system. The analysis focuses on three key roles, namely Jacks, representing broad knowledge holders, Mavens, representing deep specialists, and Connectors, representing organizational bridges. A longitudinal repository mining analysis of GitHub data, including commits and issue and pull request interactions, is conducted to operationalize OC and quantify its evolution over time. The results show that Connectors are consistently associated with higher levels of OC, while the co-occurrence of multiple roles within the same developer further amplifies coupling effects. In contrast, Jacks and Mavens exhibit more localized and role-specific influences. These findings indicate that OC in microservices is primarily a role-driven phenomenon rather than an inevitable structural property, providing a foundation for role-aware organizational design and targeted decoupling strategies.