Aimee Phan

Aimee Phan writes fiction that explores the Vietnamese American experience and the lasting effects of war. Her work focuses on families separated by conflict and the complex relationships between Vietnam and the United States. Phan's debut collection "We Should Never Meet" examines the lives of Vietnamese children adopted by American families after the fall of Saigon in 1975. The stories trace connections between birth mothers, adoptive families, and the children caught between two cultures. She teaches creative writing at California College of the Arts and has received fellowships from the National Endowment for the Arts and the Bread Loaf Writers' Conference. Her stories have appeared in literary journals including TriQuarterly and Land-Grant College Review. Phan's writing draws from historical events, particularly Operation Babylift, which evacuated thousands of Vietnamese children to the United States during the final days of the Vietnam War. Her fiction examines how political decisions affect individual lives across generations.

Readers respond positively to Phan's exploration of Vietnamese American identity and adoption themes. Many appreciate her ability to present multiple perspectives on complex family situations created by war and displacement. Readers note that her stories avoid simple resolutions and instead present the ongoing struggles of characters navigating between cultures. Some readers find emotional depth in Phan's portrayal of birth mothers who gave up children and adoptive families trying to understand their children's backgrounds. Others praise her research into Operation Babylift and how she incorporates historical details into personal narratives. Critical readers point to uneven pacing in some stories and feel certain characters lack full development. A few mention that the collection's structure makes it difficult to track connections between stories. Some readers want more direct resolution to the family conflicts presented, though others appreciate the ambiguous endings that reflect real-life complexity.