Alexander Rodríguez
Ph.D. Candidate
School of Computational Science and Engineering
Georgia Institute of Technology
CODA Building S1349
756 W Peachtree St NW, Atlanta GA, 30308
CV: [PDF]
I am in the 2022-2023 academic job market for tenure-track positions.
I am a Ph.D. candidate in Computer Science at Georgia Tech, where I am fortunate to be advised by Prof. B. Aditya Prakash. I am interested in addressing technical challenges in machine learning and data mining motivated from disciplines facing pressing social needs, such as epidemiology and community resilience.
Our group is working several projects in response to the COVID pandemic. I'm leading our group's efforts in COVID forecasting with our model called DeepCOVID. Our forecasts are being featured by CDC and FiveThirtyEight. Check more details of our response to the pandemic at LINK.
Our research work on pandemic forecasting was awarded in several venues:
Preprints: (under review)
Note: * denotes equal contribution. Data-Centric Epidemic Forecasting: A Survey [arXiv]
A. Rodríguez*, H. Kamarthi*, P. Agarwal, J. Ho, M. Patel, S. Sapre, and B.A. Prakash.
PROFHIT: Probabilistic Robust Forecasting for Hierarchical Time-series [arXiv]
H. Kamarthi, L. Kong, A. Rodríguez, C. Zhang, B.A. Prakash
Selected publications:
Differentiable Agent-based Epidemiology [arXiv]
A. Chopra*, A. Rodríguez*, J. Subramanian, A. Quera-Bofarull, B. Krishnamurthy, B.A. Prakash, R. Raskar
International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023)
EINNs: Epidemiologically-Informed Neural Networks [arXiv]
A. Rodríguez, J. Cui, N. Ramakrishnan, B. Adhikari, B.A. Prakash
AAAI Conference on Artificial Intelligence (AAAI 2023)
Differentiable Agent-based Epidemiological Modeling for End-to-end Learning [arXiv]
A. Chopra*, A. Rodríguez*, J. Subramanian, B. Krishnamurthy, B.A. Prakash, R. Raskar
ICML 2022 Workshop AI for Agent-Based Modelling (AI4ABM @ ICML 2022). Oral presentation -- Best paper award.
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US [medRxiv]
Estee Cramer, et al. [collaborative effort of the COVID-19 Forecast Hub]
Proceedings of the National Academy of Sciences (PNAS). 2022.
Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future [arXiv]
H. Kamarthi, A. Rodríguez, B.A. Prakash
International Conference on Learning Representations (ICLR 2022)
CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting [arXiv]
H. Kamarthi, L. Kong, A. Rodríguez, C. Zhang, B.A. Prakash
The Web Conference (WebConf 2022)
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting [arXiv]
H. Kamarthi, L. Kong, A. Rodríguez, C. Zhang, B.A. Prakash
Neural Information Processing Systems (NeurIPS 2021)
Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19 [arXiv]
A. Rodríguez*, N. Muralidhar*, B. Adhikari, A. Tabassum, N. Ramakrishnan, B.A. Prakash
AAAI Conference on Artificial Intelligence (AAAI 2021)
Shorter version in NeurIPS 2020 Machine Learning in Public Health (MLPH) Workshop
DeepCOVID: An Operational Deep Learning-driven Framework for Explainable Real-time COVID-19 Forecasting [medRxiv]
A. Rodríguez, A. Tabassum, J. Cui, J. Xie, J. Ho, P. Agarwal, B. Adhikari, B.A. Prakash
AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI 2021)
Mapping Network States using Connectivity Queries [arXiv] NetReAct: Interactive Learning for Network Summarization [arXiv] Incorporating Expert Guidance in Epidemic Forecasting [arXiv]
Alexander Rodríguez, B. Adhikari, A. González, C.D. Nicholson, A. Vullikanti, B.A. Prakash
IEEE International Conference on Big Data 2020 (IEEE BigData 2020)
Shorter version in NeurIPS 2020 Artificial Intelligence and Humanitarian and Disaster Relief Workshop (AI + HADR @ NeurIPS 2020)
S.E. Amiri, B. Adhikari, J. Wenskovitch, A. Rodríguez, M. Dowling, C. North, B.A. Prakash
NeurIPS 2020 Human And Machine in-the-Loop Evaluation and Learning Strategies Workshop (HAMLETS @ NeurIPS 2020)
A. Rodríguez, B. Adhikari, N. Ramakrishnan, B.A. Prakash
ACM SIGKDD 2020 Epidemiology Meets Data Mining and Knowledge Discovery Workshop (epiDAMIK @ KDD 2020)
Last update: Mar. 2023