Harshavardhan Kamarthi

I’m Harsha. I’m a Machine Learning PhD student in Department of Computational Science and Engineering at Georgia Institute of Technology . I am affiliated with AdityaLab and am advised by Dr. B Aditya Prakash. I gratuated from Indian Institute of Technology Mardas and am fortunate to have worked with Dr. Balaraman Ravindran and Dr. Sutanu Chakraborti.

My research interests broadly revolves around the fields of Generative Modeling, Epidemic Forecasting, AI for public health, Reinforcement Learning and Deep Learning. My current research interests are:

  • Generative modeling for multi-source and time-series forecasting with focus on uncertainty quantification and calibration.
  • Spatio-temporal modeling with deep learning methods that are robust to noisy data
  • Epidemic modeling and forecasting
  • Reinforcement Learning in real-world including Network problems like graph exploration, influence maximization.

news

Oct 1, 2021 Our paper When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting on State-of-Art calibrated and explainable Epidemic forecasting is accepted at NeurIPS 2021!
Jan 1, 2021 Starting PhD in Machine Learning at Georgia Tech at AdityaLab advised by Dr B Aditya Prakash!
Jun 1, 2020 Awarded the Alumini Association Award for best Academic Record in Dept. of Computer Science, IIT Madras.
Jun 1, 2020 Awarded the Lakshmi Ravi Award for best Masters Thesis in Dept. of Computer Science, IIT Madras titled Learning policies for social network discovery with reinforcement learning. Very grateful to my Masters Advisor Dr. Balaraman Ravindran.

selected publications

  1. camul21
    CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting
    Kamarthi, Harshavardhan, Kong, Lingkai, Rodrı́guez, Alexander, Zhang, Chao, and Prakash, B Aditya
    ACM Web Conference (WWW) 2022
  2. back2future21
    Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future
    Kamarthi, Harshavardhan, Rodrı́guez, Alexander, and Prakash, B Aditya
    Preprint 2021
  3. epifnp21
    When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting
    Kamarthi, Harshavardhan, Kong, Lingkai, Rodrı́guez, Alexander, Zhang, Chao, and Prakash, B Aditya
    Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) 2021
  4. patrol20
    Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with Uncertainty
    Venugopal, Aravind, Bondi, Elizabeth, Kamarthi, Harshavardhan, Dholakia, Keval, Ravindran, Balaraman, and Tambe, Milind
    20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2020
  5. influence19
    Influence maximization in unknown social networks: Learning Policies for Effective Graph Sampling
    Kamarthi, Harshavardhan, Vijayan, Priyesh, Wilder, Bryan, Ravindran, Balaraman, and Tambe, Milind
    19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Nominated for Best Paper Award 2019