Publications


Textbook (Published) & Related Interview

  1. Bhatia, Udit, Auroop R Ganguly, and Stephen Flynn. Book Interview: Critical Infrastructures Resilience: Policy and Engineering Principles. Vol. 6. 3. Mary Ann Liebert, Inc., publishers 140 Huguenot Street, 3rd Floor New Rochelle, NY 10801 USA, 2018, pp. 173–175 Link
  2. Ganguly, Auroop R, Udit Bhatia, and Stephen E Flynn. Critical Infrastructures Resilience: Policy and Engineering Principles. Routledge, 2018. Link


Textbook Projects (In progress): Peer-Reviewed & under contract

  1. Bhatia, Udit, and Auroop R Ganguly. Time Series and Geospatial Data Science: An Interdisciplinary Methods Perspective [Publisher: Springer]. Link
  2. Ganguly, Auroop R, Udit Bhatia, and Carlos Nobre. Climate Science and Engineering Adaptation [Publisher:Springer]. Link


Journal Artcles (Published)

  1. Clark, Kevin, Udit Bhatia, Evan A Kodra, and Auroop R Ganguly. ‘Resilience of the US National Airspace System Airport Network’. In: IEEE Transactions on Intelligent Transportation Systems (2018). Link
  2. Clark, Kevin, Udit Bhatia, Matthias Ruth, and Auroop R Ganguly. ‘Developing policies which optimize long-term service for vulnerable infrastructure. Transportation Policy; In review’. In: Transportation Policy (2018). Link
  3. Bhatia, Udit, Devashish Kumar, Evan Kodra, and Auroop R Ganguly. ‘Network science based quantification of resilience demonstrated on the Indian Railways Network’. In: PloS one 10.11 (2015), e0141890. Link


Journal Artcles (In review)

  1. Bhatia, Udit and Auroop R Ganguly. Reducing the irreducible uncertainty in return periods of 21st-century precipitation extremes. 2018. Link
  2. Bhatia, Udit, Tarik Gouhier, and Auroop R Ganguly. Universal and Generalizable Restoration Strategies for Degraded Ecological Networks: In review. 2018. Link
  3. Bhatia, Udit, Lina Sela, and Auroop R Ganguly. Complementary Value of Network Science and Optimization to Post-Perturbation Infrastructures Recovery: In review. 2018 Link
  4. Fard, Babak, Hanieh Hassanzadeh, Mary E Warner, Udit Bhatia, and Auroop R Ganguly. Integrated climate risk assessment: A practical application for informing action plan to heatwave threat to public health. Climate Risk Management: In review. 2018. Link


United Nations Assessment Report

  1. Ganguly, Auroop R, Evan Kodra, Udit Bhatia, Mary Elizabeth Warner, Kate Duffy, Banerjee Arindam, and Sangram Ganguly. Understanding and interpreting data for climate adaptation and mitigation. Climate 2020, United Nations Association of the United Kingdom., 2018. Link


Peer-reviewed Conference Proceedings

  1. Bhatia, Udit, Samrat Chatterjee, Auroop R Ganguly, Mahantesh Halappanavar, Jianxi Gao, Kevin Clark, Matthew Oster, Ramakrishna Tipireddy, and Rober Brigantic. ‘Aviation Transportation, Cyber Threats, and Network-of-Networks: Modeling Perspectives for Translating Theory to Practice(Accepted: to appear)’. In: 2018 IEEE International Symposium on Technologies for Homeland Security (IEEE HST). 2018. Link
  2. Bhatia, Udit, and Auroop R Ganguly. ‘Extreme Values from Spatiotemporal Chaos: Precipitation Extremes and Climate Variability (Accepted: to appear)’. In: 2018 Seventh Workshop in ICDM, Data Mining in Earth System Science. 2018. Link
  3. Bhatia, Udit, and Auroop Ganguly. ‘The Resilience of Natural-Engineered-Human-Systems’. In: International Conference on Sustainable Infrastructures. (Excellent Youth Paper Award Candidate). 2016. Link


Peer-reviewed Book Chapters & Encyclopedia Articles

  1. Bhatia, Udit, and Auroop R Ganguly. ‘Network Science Perspectives on Engineering Adaptation to Climate Change and Weather Extremes’. In: Large-Scale Machine Learning in the Earth Sciences. Chapman and Hall/CRC, 2017, pp. 19–30. Link
  2. Bhatia, Udit, Devashish Kumar, Evan Kodra, and Auroop R Ganguly. ‘Water Complexity and Physics Guided Data Mining’. In: vol. 1. Anthem Press, 2017, p. 155. Link
  3. Moskos, Catherine, Hayden Henderson, Lindsey Bressler, Udit Bhatia Devashish Kumar, Evan Kodra, and Auroop R Ganguly. ‘Informing Climate Adaptation with Earth System Models and Big Data.’ In: Encyclopedia of GIS. Springer, 2017. Link
  4. Vandal, Thomas, Udit Bhatia , and Auroop R Ganguly. ‘Statistical Downscaling in Climate with State-of-the-Art Scalable Machine Learning’. In: Large-Scale Machine Learning in the Earth Sciences. Chapman and Hall/CRC, 2017, pp. 55–72. Link