Faculty

Latha Poonamallee is Professor of Management & Socio-Tech Innovation at Parsons School of Design, The New School, and founding director of the Management & Social Justice Collective, an interdisciplinary lab advancing justice-centered approaches to management, technology, and organizational design. She directs the undergraduate program in Management, Leadership, and Entrepreneurship at Parsons. Her research examines how digital technologies, especially AI, reshape power, authority, and accountability in organizations and public systems. Drawing on theories of management, organizations, and innovation and using contemplative traditions, she develops governance frameworks that foreground ethics, judgment, and responsibility in high-stakes contexts such as healthcare and social infrastructure. Alongside her social science scholarship, she maintains an active record in applied AI, with peer-reviewed work in medical imaging and international patents. A serial entrepreneur, she has founded AI-driven health technology ventures translating research into clinically validated systems. She is a recipient of the Biospectrum India Woman Entrepreneur of the Year Award and was named among Outlook’s Top 20 Indian Women Redefining Leadership.

Ph.D. in Organizational Behavior, Case Western Reserve University

M.B.A., Pondicherry University

B.A. and M.A., University of Madras.

Books

Poonamallee, L., Howard, A. & Joy, S. (2023, edited): Managing for Social Justice: Harnessing Management Theory and Practice for Collective Good, NY: Palgrave Macmillan.

Poonamallee, L. (2021). Expansive Leadership: Cultivating Mindfulness to Lead Self and Others in a Changing World, New York, Routledge.

Poonamallee, L. Scillitoe, J.L. & Joy, S (2020, edited). Socio-tech Innovation: Harnessing Technology for Social Good, NY: Palgrave MacMillan

Peer-Reviewed Publications

Management

Scillitoe, J., Zell, D., Poonamallee, L., & Turner, K. (2025). AI as Co-Creator: Fostering Social Equity Towards Social Sustainability in Entrepreneurial Development for Women and Minority Entrepreneurs. Sustainability, 17(21), 9613. https://doi.org/10.3390/su17219613

Poonamallee, L. (2025). Countering Climate Fear with Mindfulness: A Framework for Sustainable Behavioral Change. Sustainability, 17(14), 6472. https://doi.org/10.3390/su17146472

Poonamallee, L. (2024). Social Mindfulness Adoption and Functional Use in a Classroom Context: A Qualitative Developmental Model. SAM Advanced Management Journal.

Poonamallee, L. & Joy, S. (2023). Intra-Stakeholder Heterogeneity Strategy to Prevent Mission Drift in Social Enterprise: Story of a Social Venture in Kenya. SAM Advanced Management Journal, Vol 88 Ed (1): 61-75. https://journal.samnational.org/archive/vol88ed01/vol88ed01r05/

Poonamallee, L., & Joy, S. (2022). Rousing Collective Compassion at Societal Level: Lessons from Newspaper Reports on Asian Tsunami in India. IIM Kozhikode Society & Management Review. Sage Publications. https://doi.org/10.1177/22779752211010554

Joy, S., Poonamallee, L., & Scillitoe, J. (2021) What to be (or Not to be): Understanding legal structure choices of social enterprises from a resource dependence perspective. Journal of Social Entrepreneurship. https://doi.org/10.1080/19420676.2021.1995030

Applied AI 

Agrawal, D., Joshi, Sharawari, & Poonamallee, L. (2024). Automated Midline Shift Detection and Quantification in Traumatic Brain Injury: A Comprehensive Review. Indian Journal of Neurotrauma. https://www.thieme-connect.com/products/ejournals/pdf/10.1055/s-0043-1777676.pdf

Agrawal, D., Poonamallee, L, Joshi, S. (2024). 3D CNN-based Automated Detection of Midline Shift in Traumatic Brain Injury Cases from Head CT scans. Journal of Neurosciences in Rural Practice.doi:10.25259/JNRP_490_2023

Agrawal, D., Poonamallee, L., & Joshi, S. (2023). Automated Detection of Intercranial Hemorrhage from Head CT Scans applying Deep Learning Techniques in Traumatic Brain Injuries: A Comparative Review. Indian Journal of Neurotrauma, 20(02): 081-088. DOI: 10.1055/s-0043-1770770

Agrawal, D., Poonamallee, L., Joshi, S. & Bahel, V. (2023). Automated Intracranial Hemorrhage Detection in Traumatic Brain Injury Using 3D CNN. Journal of Neurosciences in Rural Practice. 14(4): 615-621. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10696364/