Shahrzad Gholami

Sr. Applied Research Scientist

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Publications

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- Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education
  
  Shahrzad Gholami, Daniel B. Mummert, Beth Wilson, Sarah Page, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks, Dale E. Fajardo, Karine D. Bojikian
  
  JAMA Ophthalmology | October 2025
  
  Publication DOI Project
- Bridging Gaps in Ophthalmology Education Through Large Language Models
  
  Shahrzad Gholami, Beth Wilson, Sarah Page, Daniel B. Mummert , Joseph Carr, Robert R. McNabb, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks, Dale E. Fajardo, Dale E. Fajardo
  
  AJO International | August 2025
  
  Publication PDF DOI Project
- Assessing the utility of machine learning for predicting food sufficiency: a case study in Malawi
  
  Andrew Tomes, Shahrzad Gholami, Conor Hennessy, Cecilia Bitz, Rahul Dodhia, Juan M. Lavista Ferres, C. Leigh Anderson
  
  Cambridge University Press | July 2025
  
  Publication
- Modeling protective meningococcal antibody responses and factors influencing antibody persistence following vaccination with MenAfriVac® using machine learning
  
  Md Nasir, Bill Weeks, Shahrzad Gholami, Anthony Marfin, Mark Alderson, Troy Leader, Brian Taliesin, Rahul Dodhia, Juan M. Lavista Ferres, Niranjan Bhat
  
  PLoS One | May 2025
  
  Publication DOI PDF
- Enhanced Macular Telangiectasia Type 2 Detection: Leveraging Self-Supervised Learning and Ensemble Models
  
  Shahrzad Gholami, Lea Scheppke, Meghana Kshirsagar, Yue Wu, Rahul Dodhia, Roberto Bonelli, Irene Leung, Ferenc B Sallo, Alyson Muldrew, Catherine Jamison, Tunde Peto, Juan M. Lavista Ferres, Bill Weeks, Martin Friedlander, Aaron Lee, Lowy Medical Research Institute
  
  Ophthalmology Science | January 2025
  
  Publication DOI Project
- Self-Supervised Learning for Improved Optical Coherence Tomography Detection of Macular Telangiectasia Type 2
  
  Shahrzad Gholami, Lea Scheppke, Meghana Kshirsagar, Yue Wu, Rahul Dodhia, Roberto Bonelli, Irene Leung, Ferenc B. Sallo, Alyson Muldrew, Catherine Jamison, Tunde Peto, Juan M. Lavista Ferres, Bill Weeks, Martin Friedlander, Aaron Y. Lee
  
  JAMA Ophthalmology | February 2024
  
  Publication Project
- Interpretable Ensemble-based Deep Learning Approach for Automated Detection of Macular Telangiectasia Type 2 by Optical Coherence Tomography
  
  Shahrzad Gholami, Lea Scheppke, Rahul Dodhia, Juan M. Lavista Ferres, Dr. Aaron Lee
  
  ICML Workshop on Interpretable Machine Learning in Healthcare (IMLH 2023), Short Paper | July 2023
  
  Publication PDF Project
- On the Deployment of Post-Disaster Building Damage Assessment Tools using Satellite Imagery: A Deep Learning Approach
  
  Shahrzad Gholami, Caleb Robinson, Anthony Ortiz, Siyu Yang, Jacopo Margutti, Cameron Birge, Rahul Dodhia, Juan M. Lavista Ferres
  
  International Workshop on Spatial and Spatiotemporal Data Mining (SSTDM 2022) | December 2022
  
  Publication PDF Project Project
- Novel data analytics identify predictors of quality-of-life trajectories in patients with AML or high-risk Myeloid Neoplasms
  
  Jordan Gauthier, Bianca Furtuna, ,Jacopo Mangiavacchi, Shahrzad Gholami, Juan M. Lavista Ferres, Rahul Dodhia, Amir T. Fathi,, Andrew M. Brunner, Aaron T. Gerds, Mikkael A. Sekeres, Bruno C. Medeiros, Eunice S. Wang, Paul J Shami, Kehinde Adekola, Selina M. Luger, Maria R. Baer, David A Rizzieri, Tanya Wildes, Jamie L. Koprivnikar, Julie Smith, Mitchell A. Garrison, Kiarash Kojouri, Frederick R. Appelbaum, Mary-Elizabeth M. Percival, Stephanie J. Lee, Mohamed L. Sorror
  
  Blood | November 2022
  
  Publication Project
- Food Security Analysis and Forecasting: A Machine Learning Case Study in Southern Malawi
  
  Shahrzad Gholami, Erwin Knippenberg, James Campbell, Daniel Andriantsimba, Anusheel Kamle, Pavitraa Parthasarathy, Ria Sankar, Cameron Birge, Juan M. Lavista Ferres
  
  Data & Policy | October 2022, Vol 4
  
  Publication Project
- Comparing Recurrent Convolutional Neural Networks for Large Scale Bird Species Classification
  
  Gaurav Gupta, Meghana Kshirsagar, Ming Zhong, Shahrzad Gholami, Juan M. Lavista Ferres
  
  Scientific Reports | August 2021
  
  Publication PDF Project Project Project
- Becoming Good at AI for Good
  
  Meghana Kshirsagar, Siyu Yang, Caleb Robinson, Shahrzad Gholami, Ivan Klyuzhin, Sumit Mukherjee, Md Nasir, Anthony Ortiz, Felipe Oviedo, Darren Tanner, Anusua Trivedi, Yixi Xu, Ming Zhong, Bistra Dilkina, Rahul Dodhia, Juan M. Lavista Ferres
  
  AAAI/ACM Conference on AI, Ethics, and Society (AIES'21) | April 2021
  
  Publication
- Where there’s Smoke, there’s Fire: Wildfire Risk Predictive Modeling via Historical Climate Data
  
  Shahrzad Gholami, Narendran Kodandapani, Jane Wang, Juan M. Lavista Ferres
  
  IAAI'21 | February 2021
  
  Publication PDF Project Project
- Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations
  
  Lily Xu, Shahrzad Gholami, Sara McCarthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Rohit Singh, Mustapha Nsubuga, Joshua Mabonga, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Tom Okello, Eric Enyel
  
  IEEE 36th International Conference on Data Engineering (ICDE'20) | April 2020
  
  Publication PDF
- Don’t Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge
  
  Shahrzad Gholami, Amulya Yadav, Long Tran-Thanh, Bistra Dilkina, Milind Tambe
  
  International Conference on Autonomous Agents and Multiagent Systems (AAMAS'19) | May 2019
  
  Publication PDF
- Adversary Models Account for Imperfect Crime Data: Forecasting and Planning against Real-world Poachers
  
  Shahrzad Gholami, Sara Mc Carthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, Joshua Mabonga, Tom Okello, Eric Enyel
  
  International Conference on Autonomous Agents and Multiagent Systems (AAMAS'18) | July 2018
  
  Publication PDF
- Taking It for a Test Drive: A Hybrid Spatio-Temporal Model for Wildlife Poaching Prediction Evaluated Through a Controlled Field Test
  
  Shahrzad Gholami, Benjamin Ford, Fei Fang, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, Joshua Mabonga
  
  Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD'17) | December 2017
  
  Publication PDF
- Cloudy with a Chance of Poaching: Adversary Behavior Modeling and Forecasting with Real-World Poaching Data
  
  Debarun Kar, Benjamin Ford, Shahrzad Gholami, Fei Fang, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba
  
  International Conference on Autonomous Agents and Multiagent Systems (AAMAS'17) | May 2017
  
  Publication PDF
- Protecting Wildlife under Imperfect Observation
  
  Thanh Hong Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Aggrey Rwetsiba, Rob Critchlow
  
  Workshops at the AAAI Conference on Artificial Intelligence | July 2016
  
  Publication
- Observer based Feedback Control of Biodynamical Model of Tumor Growth with Sampled Measurements
  
  Shahrzad Gholami, Aria Alasty, Hassan Salarieh
  
  European Control Conference (ECC) | July 2016
  
  Publication
- Keeping Pace with Criminals: An Extended Study of Designing Patrol Allocation against Adaptive Opportunistic Criminals
  
  Chao Zhang, Shahrzad Gholami, Debarun Kar, Arunesh Sinha, Manish Jain, Ripple Goyal, Milind Tambe
  
  Games | June 2016, Vol 7(3): pp. 1-27
  
  Publication
- CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection
  
  Thanh H Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Fred Wanyama, Fred Wanyama, Aggrey Rwetsiba, Rob Critchlow
  
  International Conference on Autonomous Agents & Multiagent Systems (AAMAS'16) | May 2016
  
  Publication PDF
- On the Control of Tumor Growth via Type-1 and Interval Type-2 Fuzzy Logic
  
  Shahrzad Gholami, Aria Alasty, Hassan Salarieh, Mehdi Hosseinian-Sarajehlou
  
  Journal of Mechanics in Medicine and Biology | October 2015, Vol 15(05)
  
  Publication

- Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education
  
  Shahrzad Gholami, Daniel B. Mummert, Beth Wilson, Sarah Page, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks, Dale E. Fajardo, Karine D. Bojikian
  
  JAMA Ophthalmology | October 2025
  
  Publication DOI Project
- Bridging Gaps in Ophthalmology Education Through Large Language Models
  
  Shahrzad Gholami, Beth Wilson, Sarah Page, Daniel B. Mummert , Joseph Carr, Robert R. McNabb, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks, Dale E. Fajardo, Dale E. Fajardo
  
  AJO International | August 2025
  
  Publication PDF DOI Project
- Assessing the utility of machine learning for predicting food sufficiency: a case study in Malawi
  
  Andrew Tomes, Shahrzad Gholami, Conor Hennessy, Cecilia Bitz, Rahul Dodhia, Juan M. Lavista Ferres, C. Leigh Anderson
  
  Cambridge University Press | July 2025
  
  Publication
- Modeling protective meningococcal antibody responses and factors influencing antibody persistence following vaccination with MenAfriVac® using machine learning
  
  Md Nasir, Bill Weeks, Shahrzad Gholami, Anthony Marfin, Mark Alderson, Troy Leader, Brian Taliesin, Rahul Dodhia, Juan M. Lavista Ferres, Niranjan Bhat
  
  PLoS One | May 2025
  
  Publication DOI PDF
- Enhanced Macular Telangiectasia Type 2 Detection: Leveraging Self-Supervised Learning and Ensemble Models
  
  Shahrzad Gholami, Lea Scheppke, Meghana Kshirsagar, Yue Wu, Rahul Dodhia, Roberto Bonelli, Irene Leung, Ferenc B Sallo, Alyson Muldrew, Catherine Jamison, Tunde Peto, Juan M. Lavista Ferres, Bill Weeks, Martin Friedlander, Aaron Lee, Lowy Medical Research Institute
  
  Ophthalmology Science | January 2025
  
  Publication DOI Project
- Self-Supervised Learning for Improved Optical Coherence Tomography Detection of Macular Telangiectasia Type 2
  
  Shahrzad Gholami, Lea Scheppke, Meghana Kshirsagar, Yue Wu, Rahul Dodhia, Roberto Bonelli, Irene Leung, Ferenc B. Sallo, Alyson Muldrew, Catherine Jamison, Tunde Peto, Juan M. Lavista Ferres, Bill Weeks, Martin Friedlander, Aaron Y. Lee
  
  JAMA Ophthalmology | February 2024
  
  Publication Project
- Interpretable Ensemble-based Deep Learning Approach for Automated Detection of Macular Telangiectasia Type 2 by Optical Coherence Tomography
  
  Shahrzad Gholami, Lea Scheppke, Rahul Dodhia, Juan M. Lavista Ferres, Dr. Aaron Lee
  
  ICML Workshop on Interpretable Machine Learning in Healthcare (IMLH 2023), Short Paper | July 2023
  
  Publication PDF Project
- Novel data analytics identify predictors of quality-of-life trajectories in patients with AML or high-risk Myeloid Neoplasms
  
  Jordan Gauthier, Bianca Furtuna, ,Jacopo Mangiavacchi, Shahrzad Gholami, Juan M. Lavista Ferres, Rahul Dodhia, Amir T. Fathi,, Andrew M. Brunner, Aaron T. Gerds, Mikkael A. Sekeres, Bruno C. Medeiros, Eunice S. Wang, Paul J Shami, Kehinde Adekola, Selina M. Luger, Maria R. Baer, David A Rizzieri, Tanya Wildes, Jamie L. Koprivnikar, Julie Smith, Mitchell A. Garrison, Kiarash Kojouri, Frederick R. Appelbaum, Mary-Elizabeth M. Percival, Stephanie J. Lee, Mohamed L. Sorror
  
  Blood | November 2022
  
  Publication Project
- Food Security Analysis and Forecasting: A Machine Learning Case Study in Southern Malawi
  
  Shahrzad Gholami, Erwin Knippenberg, James Campbell, Daniel Andriantsimba, Anusheel Kamle, Pavitraa Parthasarathy, Ria Sankar, Cameron Birge, Juan M. Lavista Ferres
  
  Data & Policy | October 2022, Vol 4
  
  Publication Project
- Comparing Recurrent Convolutional Neural Networks for Large Scale Bird Species Classification
  
  Gaurav Gupta, Meghana Kshirsagar, Ming Zhong, Shahrzad Gholami, Juan M. Lavista Ferres
  
  Scientific Reports | August 2021
  
  Publication PDF Project Project Project
- Becoming Good at AI for Good
  
  Meghana Kshirsagar, Siyu Yang, Caleb Robinson, Shahrzad Gholami, Ivan Klyuzhin, Sumit Mukherjee, Md Nasir, Anthony Ortiz, Felipe Oviedo, Darren Tanner, Anusua Trivedi, Yixi Xu, Ming Zhong, Bistra Dilkina, Rahul Dodhia, Juan M. Lavista Ferres
  
  AAAI/ACM Conference on AI, Ethics, and Society (AIES'21) | April 2021
  
  Publication
- Where there’s Smoke, there’s Fire: Wildfire Risk Predictive Modeling via Historical Climate Data
  
  Shahrzad Gholami, Narendran Kodandapani, Jane Wang, Juan M. Lavista Ferres
  
  IAAI'21 | February 2021
  
  Publication PDF Project Project
- Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations
  
  Lily Xu, Shahrzad Gholami, Sara McCarthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Rohit Singh, Mustapha Nsubuga, Joshua Mabonga, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Tom Okello, Eric Enyel
  
  IEEE 36th International Conference on Data Engineering (ICDE'20) | April 2020
  
  Publication PDF
- Don’t Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge
  
  Shahrzad Gholami, Amulya Yadav, Long Tran-Thanh, Bistra Dilkina, Milind Tambe
  
  International Conference on Autonomous Agents and Multiagent Systems (AAMAS'19) | May 2019
  
  Publication PDF
- Adversary Models Account for Imperfect Crime Data: Forecasting and Planning against Real-world Poachers
  
  Shahrzad Gholami, Sara Mc Carthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, Joshua Mabonga, Tom Okello, Eric Enyel
  
  International Conference on Autonomous Agents and Multiagent Systems (AAMAS'18) | July 2018
  
  Publication PDF
- Taking It for a Test Drive: A Hybrid Spatio-Temporal Model for Wildlife Poaching Prediction Evaluated Through a Controlled Field Test
  
  Shahrzad Gholami, Benjamin Ford, Fei Fang, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, Joshua Mabonga
  
  Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD'17) | December 2017
  
  Publication PDF
- Cloudy with a Chance of Poaching: Adversary Behavior Modeling and Forecasting with Real-World Poaching Data
  
  Debarun Kar, Benjamin Ford, Shahrzad Gholami, Fei Fang, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba
  
  International Conference on Autonomous Agents and Multiagent Systems (AAMAS'17) | May 2017
  
  Publication PDF
- Observer based Feedback Control of Biodynamical Model of Tumor Growth with Sampled Measurements
  
  Shahrzad Gholami, Aria Alasty, Hassan Salarieh
  
  European Control Conference (ECC) | July 2016
  
  Publication
- Keeping Pace with Criminals: An Extended Study of Designing Patrol Allocation against Adaptive Opportunistic Criminals
  
  Chao Zhang, Shahrzad Gholami, Debarun Kar, Arunesh Sinha, Manish Jain, Ripple Goyal, Milind Tambe
  
  Games | June 2016, Vol 7(3): pp. 1-27
  
  Publication
- CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection
  
  Thanh H Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Fred Wanyama, Fred Wanyama, Aggrey Rwetsiba, Rob Critchlow
  
  International Conference on Autonomous Agents & Multiagent Systems (AAMAS'16) | May 2016
  
  Publication PDF
- On the Control of Tumor Growth via Type-1 and Interval Type-2 Fuzzy Logic
  
  Shahrzad Gholami, Aria Alasty, Hassan Salarieh, Mehdi Hosseinian-Sarajehlou
  
  Journal of Mechanics in Medicine and Biology | October 2015, Vol 15(05)
  
  Publication
- Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education
  
  Shahrzad Gholami, Daniel B. Mummert, Beth Wilson, Sarah Page, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks, Dale E. Fajardo, Karine D. Bojikian
  
  JAMA Ophthalmology | October 2025
  
  Publication DOI Project
- Bridging Gaps in Ophthalmology Education Through Large Language Models
  
  Shahrzad Gholami, Beth Wilson, Sarah Page, Daniel B. Mummert , Joseph Carr, Robert R. McNabb, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks, Dale E. Fajardo, Dale E. Fajardo
  
  AJO International | August 2025
  
  Publication PDF DOI Project
- Modeling protective meningococcal antibody responses and factors influencing antibody persistence following vaccination with MenAfriVac® using machine learning
  
  Md Nasir, Bill Weeks, Shahrzad Gholami, Anthony Marfin, Mark Alderson, Troy Leader, Brian Taliesin, Rahul Dodhia, Juan M. Lavista Ferres, Niranjan Bhat
  
  PLoS One | May 2025
  
  Publication DOI PDF
- Enhanced Macular Telangiectasia Type 2 Detection: Leveraging Self-Supervised Learning and Ensemble Models
  
  Shahrzad Gholami, Lea Scheppke, Meghana Kshirsagar, Yue Wu, Rahul Dodhia, Roberto Bonelli, Irene Leung, Ferenc B Sallo, Alyson Muldrew, Catherine Jamison, Tunde Peto, Juan M. Lavista Ferres, Bill Weeks, Martin Friedlander, Aaron Lee, Lowy Medical Research Institute
  
  Ophthalmology Science | January 2025
  
  Publication DOI Project
- Self-Supervised Learning for Improved Optical Coherence Tomography Detection of Macular Telangiectasia Type 2
  
  Shahrzad Gholami, Lea Scheppke, Meghana Kshirsagar, Yue Wu, Rahul Dodhia, Roberto Bonelli, Irene Leung, Ferenc B. Sallo, Alyson Muldrew, Catherine Jamison, Tunde Peto, Juan M. Lavista Ferres, Bill Weeks, Martin Friedlander, Aaron Y. Lee
  
  JAMA Ophthalmology | February 2024
  
  Publication Project
- Interpretable Ensemble-based Deep Learning Approach for Automated Detection of Macular Telangiectasia Type 2 by Optical Coherence Tomography
  
  Shahrzad Gholami, Lea Scheppke, Rahul Dodhia, Juan M. Lavista Ferres, Dr. Aaron Lee
  
  ICML Workshop on Interpretable Machine Learning in Healthcare (IMLH 2023), Short Paper | July 2023
  
  Publication PDF Project
- Novel data analytics identify predictors of quality-of-life trajectories in patients with AML or high-risk Myeloid Neoplasms
  
  Jordan Gauthier, Bianca Furtuna, ,Jacopo Mangiavacchi, Shahrzad Gholami, Juan M. Lavista Ferres, Rahul Dodhia, Amir T. Fathi,, Andrew M. Brunner, Aaron T. Gerds, Mikkael A. Sekeres, Bruno C. Medeiros, Eunice S. Wang, Paul J Shami, Kehinde Adekola, Selina M. Luger, Maria R. Baer, David A Rizzieri, Tanya Wildes, Jamie L. Koprivnikar, Julie Smith, Mitchell A. Garrison, Kiarash Kojouri, Frederick R. Appelbaum, Mary-Elizabeth M. Percival, Stephanie J. Lee, Mohamed L. Sorror
  
  Blood | November 2022
  
  Publication Project
- On the Deployment of Post-Disaster Building Damage Assessment Tools using Satellite Imagery: A Deep Learning Approach
  
  Shahrzad Gholami, Caleb Robinson, Anthony Ortiz, Siyu Yang, Jacopo Margutti, Cameron Birge, Rahul Dodhia, Juan M. Lavista Ferres
  
  International Workshop on Spatial and Spatiotemporal Data Mining (SSTDM 2022) | December 2022
  
  Publication PDF Project Project
- Food Security Analysis and Forecasting: A Machine Learning Case Study in Southern Malawi
  
  Shahrzad Gholami, Erwin Knippenberg, James Campbell, Daniel Andriantsimba, Anusheel Kamle, Pavitraa Parthasarathy, Ria Sankar, Cameron Birge, Juan M. Lavista Ferres
  
  Data & Policy | October 2022, Vol 4
  
  Publication Project
- Comparing Recurrent Convolutional Neural Networks for Large Scale Bird Species Classification
  
  Gaurav Gupta, Meghana Kshirsagar, Ming Zhong, Shahrzad Gholami, Juan M. Lavista Ferres
  
  Scientific Reports | August 2021
  
  Publication PDF Project Project Project
- Where there’s Smoke, there’s Fire: Wildfire Risk Predictive Modeling via Historical Climate Data
  
  Shahrzad Gholami, Narendran Kodandapani, Jane Wang, Juan M. Lavista Ferres
  
  IAAI'21 | February 2021
  
  Publication PDF Project Project
- Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations
  
  Lily Xu, Shahrzad Gholami, Sara McCarthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Rohit Singh, Mustapha Nsubuga, Joshua Mabonga, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Tom Okello, Eric Enyel
  
  IEEE 36th International Conference on Data Engineering (ICDE'20) | April 2020
  
  Publication PDF
- Taking It for a Test Drive: A Hybrid Spatio-Temporal Model for Wildlife Poaching Prediction Evaluated Through a Controlled Field Test
  
  Shahrzad Gholami, Benjamin Ford, Fei Fang, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, Joshua Mabonga
  
  Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD'17) | December 2017
  
  Publication PDF
- Protecting Wildlife under Imperfect Observation
  
  Thanh Hong Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Aggrey Rwetsiba, Rob Critchlow
  
  Workshops at the AAAI Conference on Artificial Intelligence | July 2016
  
  Publication
- CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection
  
  Thanh H Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Fred Wanyama, Fred Wanyama, Aggrey Rwetsiba, Rob Critchlow
  
  International Conference on Autonomous Agents & Multiagent Systems (AAMAS'16) | May 2016
  
  Publication PDF

- Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education
  
  Shahrzad Gholami, Daniel B. Mummert, Beth Wilson, Sarah Page, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks, Dale E. Fajardo, Karine D. Bojikian
  
  JAMA Ophthalmology | October 2025
  
  Publication DOI Project
- Bridging Gaps in Ophthalmology Education Through Large Language Models
  
  Shahrzad Gholami, Beth Wilson, Sarah Page, Daniel B. Mummert , Joseph Carr, Robert R. McNabb, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks, Dale E. Fajardo, Dale E. Fajardo
  
  AJO International | August 2025
  
  Publication PDF DOI Project
- Assessing the utility of machine learning for predicting food sufficiency: a case study in Malawi
  
  Andrew Tomes, Shahrzad Gholami, Conor Hennessy, Cecilia Bitz, Rahul Dodhia, Juan M. Lavista Ferres, C. Leigh Anderson
  
  Cambridge University Press | July 2025
  
  Publication
- Modeling protective meningococcal antibody responses and factors influencing antibody persistence following vaccination with MenAfriVac® using machine learning
  
  Md Nasir, Bill Weeks, Shahrzad Gholami, Anthony Marfin, Mark Alderson, Troy Leader, Brian Taliesin, Rahul Dodhia, Juan M. Lavista Ferres, Niranjan Bhat
  
  PLoS One | May 2025
  
  Publication DOI PDF
- Enhanced Macular Telangiectasia Type 2 Detection: Leveraging Self-Supervised Learning and Ensemble Models
  
  Shahrzad Gholami, Lea Scheppke, Meghana Kshirsagar, Yue Wu, Rahul Dodhia, Roberto Bonelli, Irene Leung, Ferenc B Sallo, Alyson Muldrew, Catherine Jamison, Tunde Peto, Juan M. Lavista Ferres, Bill Weeks, Martin Friedlander, Aaron Lee, Lowy Medical Research Institute
  
  Ophthalmology Science | January 2025
  
  Publication DOI Project
- Self-Supervised Learning for Improved Optical Coherence Tomography Detection of Macular Telangiectasia Type 2
  
  Shahrzad Gholami, Lea Scheppke, Meghana Kshirsagar, Yue Wu, Rahul Dodhia, Roberto Bonelli, Irene Leung, Ferenc B. Sallo, Alyson Muldrew, Catherine Jamison, Tunde Peto, Juan M. Lavista Ferres, Bill Weeks, Martin Friedlander, Aaron Y. Lee
  
  JAMA Ophthalmology | February 2024
  
  Publication Project
- Novel data analytics identify predictors of quality-of-life trajectories in patients with AML or high-risk Myeloid Neoplasms
  
  Jordan Gauthier, Bianca Furtuna, ,Jacopo Mangiavacchi, Shahrzad Gholami, Juan M. Lavista Ferres, Rahul Dodhia, Amir T. Fathi,, Andrew M. Brunner, Aaron T. Gerds, Mikkael A. Sekeres, Bruno C. Medeiros, Eunice S. Wang, Paul J Shami, Kehinde Adekola, Selina M. Luger, Maria R. Baer, David A Rizzieri, Tanya Wildes, Jamie L. Koprivnikar, Julie Smith, Mitchell A. Garrison, Kiarash Kojouri, Frederick R. Appelbaum, Mary-Elizabeth M. Percival, Stephanie J. Lee, Mohamed L. Sorror
  
  Blood | November 2022
  
  Publication Project
- Food Security Analysis and Forecasting: A Machine Learning Case Study in Southern Malawi
  
  Shahrzad Gholami, Erwin Knippenberg, James Campbell, Daniel Andriantsimba, Anusheel Kamle, Pavitraa Parthasarathy, Ria Sankar, Cameron Birge, Juan M. Lavista Ferres
  
  Data & Policy | October 2022, Vol 4
  
  Publication Project
- Comparing Recurrent Convolutional Neural Networks for Large Scale Bird Species Classification
  
  Gaurav Gupta, Meghana Kshirsagar, Ming Zhong, Shahrzad Gholami, Juan M. Lavista Ferres
  
  Scientific Reports | August 2021
  
  Publication PDF Project Project Project
- Keeping Pace with Criminals: An Extended Study of Designing Patrol Allocation against Adaptive Opportunistic Criminals
  
  Chao Zhang, Shahrzad Gholami, Debarun Kar, Arunesh Sinha, Manish Jain, Ripple Goyal, Milind Tambe
  
  Games | June 2016, Vol 7(3): pp. 1-27
  
  Publication
- On the Control of Tumor Growth via Type-1 and Interval Type-2 Fuzzy Logic
  
  Shahrzad Gholami, Aria Alasty, Hassan Salarieh, Mehdi Hosseinian-Sarajehlou
  
  Journal of Mechanics in Medicine and Biology | October 2015, Vol 15(05)
  
  Publication
- Interpretable Ensemble-based Deep Learning Approach for Automated Detection of Macular Telangiectasia Type 2 by Optical Coherence Tomography
  
  Shahrzad Gholami, Lea Scheppke, Rahul Dodhia, Juan M. Lavista Ferres, Dr. Aaron Lee
  
  ICML Workshop on Interpretable Machine Learning in Healthcare (IMLH 2023), Short Paper | July 2023
  
  Publication PDF Project
- On the Deployment of Post-Disaster Building Damage Assessment Tools using Satellite Imagery: A Deep Learning Approach
  
  Shahrzad Gholami, Caleb Robinson, Anthony Ortiz, Siyu Yang, Jacopo Margutti, Cameron Birge, Rahul Dodhia, Juan M. Lavista Ferres
  
  International Workshop on Spatial and Spatiotemporal Data Mining (SSTDM 2022) | December 2022
  
  Publication PDF Project Project
- Becoming Good at AI for Good
  
  Meghana Kshirsagar, Siyu Yang, Caleb Robinson, Shahrzad Gholami, Ivan Klyuzhin, Sumit Mukherjee, Md Nasir, Anthony Ortiz, Felipe Oviedo, Darren Tanner, Anusua Trivedi, Yixi Xu, Ming Zhong, Bistra Dilkina, Rahul Dodhia, Juan M. Lavista Ferres
  
  AAAI/ACM Conference on AI, Ethics, and Society (AIES'21) | April 2021
  
  Publication
- Where there’s Smoke, there’s Fire: Wildfire Risk Predictive Modeling via Historical Climate Data
  
  Shahrzad Gholami, Narendran Kodandapani, Jane Wang, Juan M. Lavista Ferres
  
  IAAI'21 | February 2021
  
  Publication PDF Project Project
- Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations
  
  Lily Xu, Shahrzad Gholami, Sara McCarthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Rohit Singh, Mustapha Nsubuga, Joshua Mabonga, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Tom Okello, Eric Enyel
  
  IEEE 36th International Conference on Data Engineering (ICDE'20) | April 2020
  
  Publication PDF
- Don’t Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge
  
  Shahrzad Gholami, Amulya Yadav, Long Tran-Thanh, Bistra Dilkina, Milind Tambe
  
  International Conference on Autonomous Agents and Multiagent Systems (AAMAS'19) | May 2019
  
  Publication PDF
- Adversary Models Account for Imperfect Crime Data: Forecasting and Planning against Real-world Poachers
  
  Shahrzad Gholami, Sara Mc Carthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, Joshua Mabonga, Tom Okello, Eric Enyel
  
  International Conference on Autonomous Agents and Multiagent Systems (AAMAS'18) | July 2018
  
  Publication PDF
- Taking It for a Test Drive: A Hybrid Spatio-Temporal Model for Wildlife Poaching Prediction Evaluated Through a Controlled Field Test
  
  Shahrzad Gholami, Benjamin Ford, Fei Fang, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, Joshua Mabonga
  
  Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD'17) | December 2017
  
  Publication PDF
- Cloudy with a Chance of Poaching: Adversary Behavior Modeling and Forecasting with Real-World Poaching Data
  
  Debarun Kar, Benjamin Ford, Shahrzad Gholami, Fei Fang, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba
  
  International Conference on Autonomous Agents and Multiagent Systems (AAMAS'17) | May 2017
  
  Publication PDF
- Protecting Wildlife under Imperfect Observation
  
  Thanh Hong Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Aggrey Rwetsiba, Rob Critchlow
  
  Workshops at the AAAI Conference on Artificial Intelligence | July 2016
  
  Publication
- Observer based Feedback Control of Biodynamical Model of Tumor Growth with Sampled Measurements
  
  Shahrzad Gholami, Aria Alasty, Hassan Salarieh
  
  European Control Conference (ECC) | July 2016
  
  Publication
- CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection
  
  Thanh H Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Fred Wanyama, Fred Wanyama, Aggrey Rwetsiba, Rob Critchlow
  
  International Conference on Autonomous Agents & Multiagent Systems (AAMAS'16) | May 2016
  
  Publication PDF

Shahrzad Gholami

Publications

Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education

Bridging Gaps in Ophthalmology Education Through Large Language Models

Assessing the utility of machine learning for predicting food sufficiency: a case study in Malawi

Modeling protective meningococcal antibody responses and factors influencing antibody persistence following vaccination with MenAfriVac® using machine learning

Enhanced Macular Telangiectasia Type 2 Detection: Leveraging Self-Supervised Learning and Ensemble Models

Self-Supervised Learning for Improved Optical Coherence Tomography Detection of Macular Telangiectasia Type 2

Interpretable Ensemble-based Deep Learning Approach for Automated Detection of Macular Telangiectasia Type 2 by Optical Coherence Tomography

On the Deployment of Post-Disaster Building Damage Assessment Tools using Satellite Imagery: A Deep Learning Approach

Novel data analytics identify predictors of quality-of-life trajectories in patients with AML or high-risk Myeloid Neoplasms

Food Security Analysis and Forecasting: A Machine Learning Case Study in Southern Malawi

Comparing Recurrent Convolutional Neural Networks for Large Scale Bird Species Classification

Becoming Good at AI for Good

Where there’s Smoke, there’s Fire: Wildfire Risk Predictive Modeling via Historical Climate Data

Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations

Don’t Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge

Adversary Models Account for Imperfect Crime Data: Forecasting and Planning against Real-world Poachers

Taking It for a Test Drive: A Hybrid Spatio-Temporal Model for Wildlife Poaching Prediction Evaluated Through a Controlled Field Test

Cloudy with a Chance of Poaching: Adversary Behavior Modeling and Forecasting with Real-World Poaching Data

Protecting Wildlife under Imperfect Observation

Observer based Feedback Control of Biodynamical Model of Tumor Growth with Sampled Measurements

Keeping Pace with Criminals: An Extended Study of Designing Patrol Allocation against Adaptive Opportunistic Criminals

CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection

On the Control of Tumor Growth via Type-1 and Interval Type-2 Fuzzy Logic

Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education

Bridging Gaps in Ophthalmology Education Through Large Language Models

Assessing the utility of machine learning for predicting food sufficiency: a case study in Malawi

Modeling protective meningococcal antibody responses and factors influencing antibody persistence following vaccination with MenAfriVac® using machine learning

Enhanced Macular Telangiectasia Type 2 Detection: Leveraging Self-Supervised Learning and Ensemble Models

Self-Supervised Learning for Improved Optical Coherence Tomography Detection of Macular Telangiectasia Type 2

Interpretable Ensemble-based Deep Learning Approach for Automated Detection of Macular Telangiectasia Type 2 by Optical Coherence Tomography

Novel data analytics identify predictors of quality-of-life trajectories in patients with AML or high-risk Myeloid Neoplasms

Food Security Analysis and Forecasting: A Machine Learning Case Study in Southern Malawi

Comparing Recurrent Convolutional Neural Networks for Large Scale Bird Species Classification

Becoming Good at AI for Good

Where there’s Smoke, there’s Fire: Wildfire Risk Predictive Modeling via Historical Climate Data

Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations

Don’t Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge

Adversary Models Account for Imperfect Crime Data: Forecasting and Planning against Real-world Poachers

Taking It for a Test Drive: A Hybrid Spatio-Temporal Model for Wildlife Poaching Prediction Evaluated Through a Controlled Field Test

Cloudy with a Chance of Poaching: Adversary Behavior Modeling and Forecasting with Real-World Poaching Data

Observer based Feedback Control of Biodynamical Model of Tumor Growth with Sampled Measurements

Keeping Pace with Criminals: An Extended Study of Designing Patrol Allocation against Adaptive Opportunistic Criminals

CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection

On the Control of Tumor Growth via Type-1 and Interval Type-2 Fuzzy Logic

Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education

Bridging Gaps in Ophthalmology Education Through Large Language Models

Modeling protective meningococcal antibody responses and factors influencing antibody persistence following vaccination with MenAfriVac® using machine learning

Enhanced Macular Telangiectasia Type 2 Detection: Leveraging Self-Supervised Learning and Ensemble Models

Self-Supervised Learning for Improved Optical Coherence Tomography Detection of Macular Telangiectasia Type 2

Interpretable Ensemble-based Deep Learning Approach for Automated Detection of Macular Telangiectasia Type 2 by Optical Coherence Tomography

Novel data analytics identify predictors of quality-of-life trajectories in patients with AML or high-risk Myeloid Neoplasms

On the Deployment of Post-Disaster Building Damage Assessment Tools using Satellite Imagery: A Deep Learning Approach

Food Security Analysis and Forecasting: A Machine Learning Case Study in Southern Malawi

Comparing Recurrent Convolutional Neural Networks for Large Scale Bird Species Classification

Where there’s Smoke, there’s Fire: Wildfire Risk Predictive Modeling via Historical Climate Data

Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations

Taking It for a Test Drive: A Hybrid Spatio-Temporal Model for Wildlife Poaching Prediction Evaluated Through a Controlled Field Test

Protecting Wildlife under Imperfect Observation

CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection

Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education

Bridging Gaps in Ophthalmology Education Through Large Language Models

Assessing the utility of machine learning for predicting food sufficiency: a case study in Malawi

Modeling protective meningococcal antibody responses and factors influencing antibody persistence following vaccination with MenAfriVac® using machine learning

Enhanced Macular Telangiectasia Type 2 Detection: Leveraging Self-Supervised Learning and Ensemble Models

Self-Supervised Learning for Improved Optical Coherence Tomography Detection of Macular Telangiectasia Type 2

Novel data analytics identify predictors of quality-of-life trajectories in patients with AML or high-risk Myeloid Neoplasms

Food Security Analysis and Forecasting: A Machine Learning Case Study in Southern Malawi

Comparing Recurrent Convolutional Neural Networks for Large Scale Bird Species Classification

Keeping Pace with Criminals: An Extended Study of Designing Patrol Allocation against Adaptive Opportunistic Criminals

On the Control of Tumor Growth via Type-1 and Interval Type-2 Fuzzy Logic

Interpretable Ensemble-based Deep Learning Approach for Automated Detection of Macular Telangiectasia Type 2 by Optical Coherence Tomography

On the Deployment of Post-Disaster Building Damage Assessment Tools using Satellite Imagery: A Deep Learning Approach

Becoming Good at AI for Good

Where there’s Smoke, there’s Fire: Wildfire Risk Predictive Modeling via Historical Climate Data

Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations

Don’t Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge

Adversary Models Account for Imperfect Crime Data: Forecasting and Planning against Real-world Poachers

Taking It for a Test Drive: A Hybrid Spatio-Temporal Model for Wildlife Poaching Prediction Evaluated Through a Controlled Field Test