Piyush Jha

Ph.D. Student at Georgia Institute of Technology

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Peer-reviewed Journals | Piyush Jha

Peer-reviewed Journals

  1. Piyush Jha, Rashi Kumar, and Vineet Sahula (2023). Filtering and extended vocabulary based translation for low-resource language pair of Sanskrit-Hindi. ACM Transactions on Asian and Low-Resource Language Information Processing, ACM, Vol. 22, Issue 4, pp. 1-15.

  2. Janaki B. Mohapatra, Piyush Jha, Madan Kumar Jha, and Sabinaya Biswal (2021). Efficacy of machine learning techniques in predicting groundwater fluctuations in agro-ecological zones of India. Science of the Total Environment, Elsevier, Vol. 785. (Impact Factor: 10.753)

  3. Gaurav Bhatt, Piyush Jha, and Balasubramanian Raman (2019). Representation learning using step-based deep multi-modal autoencoders. Pattern Recognition, Elsevier, Vol. 95, pp. 12-23. (Impact Factor: 8.518)

Peer-reviewed International Conferences (Full Paper)

  1. Prithwish Jana, Piyush Jha, Haoyang Ju, Gautham Kishore, Aryan Mahajan, and Vijay Ganesh (2024). Attention, compilation, and solver-based symbolic analysis are all you need. European Conference on Artificial Intelligence (ECAI) 2024. 19-24 October 2024, Santiago de Compostela, Spain.

  2. Zhengyang Lu, Stefan Siemer, Piyush Jha, Joel Day, Florin Manea, and Vijay Ganesh (2024). Layered and staged monte carlo tree search for SMT strategy synthesis. International Joint Conference on Artificial Intelligence (IJCAI) 2024. 3-9 August 2024, Jeju, South Korea.

  3. Joseph Scott, Guanting Pan, Piyush Jha, Elias Khalil, and Vijay Ganesh (2023). Pierce: A testing tool for neural network verification solvers. International Conference on Verified Software: Theories, Tools, and Experiments (VSTTE) 2023. 23-24 October 2023, Ames, USA.

  4. Rashi Kumar, Piyush Jha, and Vineet Sahula (2019). An augmented translation technique for low resource language pair: Sanskrit to Hindi translation. International Conference on Algorithms, Computing and Artificial Intelligence (ACAI), ACM. 20-22 December 2019, Sanya, China.

  5. Gaurav Bhatt, Piyush Jha, and Balasubramanian Raman (2017). Common representation learning using step-based correlation multi-modal CNN. Asian Conference on Pattern Recognition (ACPR) 2017, IEEE. 26-29 November 2017, Nanjing, China.

Peer-reviewed International Conferences (Short Paper)

  1. Piyush Jha, Arnav Arora, and Vijay Ganesh (2025). LLMStinger: jailbreaking LLMs using RL fine-tuned LLMs (Student Abstract). Association for the Advancement of Artificial Intelligence (AAAI) 2025. Accepted for poster and oral presentation.

  2. Piyush Jha and Werner Dietl (2024). OppropBERL: A GNN and BERT-style reinforcement learning-based type inference. IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) 2024. 12-15 March 2024, Rovaniemi, Finland.

  3. Piyush Jha, Joseph Scott, Jaya Sriram Ganeshna, Mudit Singh, and Vijay Ganesh (2024). BertRLFuzzer: a BERT and reinforcement learning based fuzzer (Student Abstract). Association for the Advancement of Artificial Intelligence (AAAI) 2024. 20-27 February 2024, Vancouver, Canada.

  4. Zhengyang Lu, Piyush Jha, Stefan Siemer, Florin Manea, Joel Day, and Vijay Ganesh (2023). Reinforcement learning empowers SMT solver. Doctoral Program at International Conference on Principles and Practice of Constraint Programming (CP) 2023. 27-31 August 2023, Toronto, Canada.

Peer-reviewed International Short Articles

  1. Simran Jain and Piyush Jha. Deepfakes in India: regulation and privacy. South Asia Center at London School of Economics, The London School of Economics and Political Science (LSE), 21 May 2020.

Peer-reviewed Tutorial Papers

  1. John Lu, Chris Cameron, Piyush Jha, Kevin Leyton-Brown, and Vijay Ganesh (2025). Machine learning for solvers. Association for the Advancement of Artificial Intelligence (AAAI) 2025. Accepted as a tutorial.

Pre-prints

  1. Piyush Jha, Prithwish Jana, Pranavkrishna Suresh, Arnav Arora, and Vijay Ganesh. RLSF: Reinforcement Learning via Symbolic Feedback. arXiv preprint, May 2024.

  2. Chunxiao Li, Charlie Liu, Jonathan Chung, Zhengyang Lu, Piyush Jha, and Vijay Ganesh. A Reinforcement Learning based Reset Policy for CDCL SAT Solvers. arXiv preprint, April 2024.

  3. Piyush Jha, Zhengyu Li, Zhengyang Lu, Curtis Bright, and Vijay Ganesh. AlphaMapleSAT: An MCTS-based Cube-and-Conquer SAT Solver for Hard Combinatorial Problems. arXiv preprint, January 2024.

  4. Vineel Nagisetty, Laura Graves, Guanting Pan, Piyush Jha, and Vijay Ganesh. CGDTest: A Constrained Gradient Descent Algorithm for Testing Neural Networks. arXiv preprint, April 2023.