Vitika Soni

Designed and analyzed behavioral and human-AI experiments with 150+ participants, quantifying trust, reliance, accuracy, response time, and decision behavior using structured experimental measures. Developed and compared Linear Regression, Elastic Net, SVR, KNN, Random Forest, XGBoost, and stacking ensembles, achieving held-out R2 values of 0.81–0.93 across behavioral and physiological prediction tasks. Applied hypothesis testing, nonparametric inference, correlation analysis, effect sizes, reliability analysis, and FDR correction to quantify experimental effects and assess relationships among behavioral and physiological variables.

Graduate Researcher — Intelligent Systems at Indian Institute of Technology Mandi (2024 – 2026)

• Designed and analyzed behavioral and human-AI experiments with 150+ participants, quantifying trust, reliance, accuracy, response time, and decision behavior using structured experimental measures.
• Developed and compared Linear Regression, Elastic Net, SVR, KNN, Random Forest, XGBoost, and stacking ensembles, achieving held-out R2 values of 0.81–0.93 across behavioral and physiological prediction tasks.
• Applied hypothesis testing, nonparametric inference, correlation analysis, effect sizes, reliability analysis, and FDR correction to quantify experimental effects and assess relationships among behavioral and physiological variables.
• Built multimodal time-series analysis pipelines for EEG, ECG, HRV, and PPG data, performing signal preprocessing, smoothing, feature extraction, and participant-level model evaluation under noisy empirical conditions.
• Conducted a 90-participant randomized EEG study using behavioral and neurophysiological measurements to quantify attentional-arousal responses across interface modalities.
• Analyzed a 60-participant pre/post physiological study, extracting Mean RR, SDNN, PNS, and SNS measures to quantify changes in autonomic response.
• Used SHAP-based model interpretation to identify influential predictors and examine feature-level contributions to predictive model outputs.
• Evaluated model behavior under heterogeneous and noisy empirical data conditions, with research spanning human-AI interaction, cognitive workload, immersive systems, and multimodal time-series data.

Project Associate I at Indian Institute of Technology Mandi (2025 – 2026)

• Conducted quantitative research under the Indian Knowledge System & Mental Health Application, integrating behavioral, physiological, and immersive-system measurements across controlled experimental conditions.
• Contributed to 9+ research outputs across IEEE, Springer, HFES, and conference proceedings involving statistical analysis, machine learning, physiological measurement, and intelligent systems.
• Mentored 40+ B.Tech students and 4 interns in research methodology, quantitative analysis, and technical project development.

M.Tech (Research) in Intelligent Systems – Indian Institute of Technology Mandi (2024 – 2026)

M.A. in Clinical Psychology – The Maharaja Sayajirao University of Baroda (2022 – 2024)

B.A. in Humanities & Social Sciences – Government Meera Girls College, Udaipur (2019 – 2022)