Nicolina Peperkorn

PFH Private University of Applied Sciences

Papers

Total Citations

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About

Nicolina Peperkorn is a rising researcher at the intersection of artificial intelligence and mental health diagnostics. Her primary research areas include AI-supported clinical diagnostics, natural language processing in psychotherapy, and human-robot interaction. Her most notable contribution is the pilot study "AI-Supported Diagnostic of Depression Using Clinical Interviews," which explores how machine learning models can analyze patient speech patterns to detect depressive symptoms. This work, already garnering 5 citations since its 2024 publication, represents a critical step toward augmenting traditional psychiatric assessments with objective, data-driven tools. Beyond mental health applications, Peperkorn has also investigated how robots can move beyond simple 2D costmaps for obstacle avoidance, proposing more semantically aware path planning that considers obstacle identity rather than just geometry. This dual focus—applying AI to both clinical psychology and robotics—demonstrates her versatility in bridging human-centered computing with autonomous systems. Her work holds promise for reducing diagnostic delays in mental healthcare while simultaneously making robotic navigation safer and more context-aware.