Can a conversation
be mistaken for you?
A two-phase study of suspicion, trust, and identity detection in conversational AI, using user-trained clones as a way to investigate human–agent interaction.
Explore the studyI’m Shriya, an HCI researcher and product practitioner working across the places where people, AI, and real-world systems meet.
Signals in conversation / 01I move between observing how people make sense of technology, shaping products around what they need, and building the operational systems that help teams use AI responsibly. The through-line is the same: make the work legible, test assumptions with people, and carry what we learn into the next decision.
Different settings, connected by a habit of turning ambiguity into something a team can inspect, test, and improve.
A two-phase study of suspicion, trust, and identity detection in conversational AI, using user-trained clones as a way to investigate human–agent interaction.
Explore the studyProduct work across a German Ports release-order flow and related operational features, from training and slot changes to dashboards and incident handling.
View contribution areasBuilding the foundations for useful, reviewable AI support: knowledge audits, modular content, team enablement, and a clear path for skills to be reviewed before sharing.
View contribution areasExploring “comicification”: redesigning surveys as sequential visual narratives, then bringing the format into workshops and public-facing research experiences.
See the projectA thesis project on suspicion, trust, and identity in conversations with people and AI agents.
Cloned Testing is a hybrid method for evaluating human–agent interaction using knowledge-garden-based user clones. The study asks how people decide who—or what—they are talking to, how suspicion changes as a conversation unfolds, and what signals shape that judgment.
The work is structured as two linked activities: people first train a conversational clone through persona role-play, then evaluate conversations with a human operator, a baseline AI, and a clone trained from their material. A mid-session switch makes identity judgments part of the interaction rather than a question asked only at the end.
Evaluation combines final identity guesses and confidence with time to decision, suspicion changes, switch detection, conversation traces, accuracy, and repair behavior. The aim is a method that makes those judgments observable and useful to designers of conversational systems.
Product and operations are where a good idea has to survive actual constraints, handoffs, and human habits.
Contributed to product initiatives for German port logistics, working across workflows used by companies and operational teams.
Helped structure how internal knowledge and AI support fit together, with attention to quality and clear ownership.
Co-founded Comic Survey Lab with Konstantina Marra to explore how sequential visuals can change the experience of answering research questions.
Computer science gave me a systems foundation; HCI gave me methods for understanding the people inside those systems.
AI support, knowledge systems, and internal enablement in a health-tech startup.
Product work for port-logistics workflows and operational tools, including release orders, training, slot handling, dashboards, and incident management.
Selected work and project details to be added.
Research methods, ubiquitous computing, usability engineering, physiological computing, visualization, and comics in East Asia.
Foundation in software engineering, databases, algorithms, AI/ML, graphics, and digital image processing.
Turn a broad concern into a decision, behavior, or experience that can be observed.
Map the people, information, and handoffs so everyone can see where friction lives.
Carry what research reveals into product choices, team processes, and the next test.