Lucea AI was founded by Amy Daali, an accomplished AI expert with a deep background in AI and engineering. She is a 2x founder and a passionate advocate for gender equality in tech. She holds a Ph.D. in Engineering from the University of Texas. With over a decade of experience in engineering and biomedical imaging, she has deep technical skills in deep learning, computer vision, and advanced image and signal processing.
Her passion for AI and machine learning led her to establish Lucea AI, where she combines her technical expertise with her entrepreneurial spirit to help businesses move from AI uncertainty to AI that works, through clear roadmaps, custom-built automations, and teams trained to use them. Amy is also the founder of Moonshot 4 HER, a program that helps ambitious technical women turn their expertise into impactful companies and claim their space in technical entrepreneurship.
Amy is a sought-after thought leader and speaker on AI, machine learning, and data analytics. She has been a featured speaker at conferences and events including the Data Science Salon Conference, the Women in Data Science Conference, and IEEE conferences, and a guest on podcasts and events covering data science, analytics, machine learning, and artificial intelligence.
When she’s not thinking about AI or building something new, Amy is probably sipping a great cup of coffee and getting lost in a good book. She loves traveling, being outdoors, and is happiest at the beach or in the mountains. She also speaks five languages and is proudly left-handed.
Developed innovative deep learning models using Keras and GPU-enabled TensorFlow on extensive imagery datasets. Contributed to the design of the patent "Predictive mapping for routing telephone calls," which uses AI to route calls based on sentiment, experience, and performance scores related to the conversation topic.
Led the development and implementation of a real-time noise reduction technology, the Filtered-x Least Mean Square (FxLMS) algorithm, to enhance the acoustic environment of neonatal incubators and improve the well-being of premature infants.
Developed mathematical models to analyze different biomedical imaging modalities and predict cancer progression in glioblastoma patients.
Chaired the San Antonio chapter of the IEEE Engineering in Medicine and Biology Society, creating opportunities for members to engage in technical and professional conversations that transform the future of medicine and healthcare.
K. Williams, R. Medina III, M. A. Lopez, and A. Daali. U.S. Patent 11,750,744 B1, assigned to United Services Automobile Association (USAA). Granted September 5, 2023. Routes calls to the right representative using sentiment, experience, and performance scores tied to the conversation topic.
View patent →A. W. Daali. Ph.D. dissertation, The University of Texas at San Antonio. Advisor: Mo Jamshidi. Proposes the first PCA-based algorithm to noninvasively recognize and classify temporal stages of brain tumors from a large time series of MRI images during VB-111 virotherapy.
A. W. Daali, Y. Huang, and M. Jamshidi. IEEE International Conference on System of Systems Engineering (SoSE), 2013, pp. 273-278.
View on IEEE Xplore →The latest insights on AI agents, AGI, and the future of AI. Published on Substack.
Recent articles →Where AI meets women's health: the research, the companies, and the questions that deserve better answers. Published on Substack.
Read on Substack →One conversation is enough to know whether we can help.
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