I'm a PhD candidate majoring in Computer Science at Georgia State University, USA. I work with Prof. Zhipeng Cai at the INSPIRE Center and am co-advised by Prof. Daniel Takabi. 

My research focuses on Privacy-preserving Machine Learning. I enjoy working on problems related to security and privacy in machine learning. For the last couple of years, I've had the opportunity to work on interesting research projects supported by Microsoft and the National Science Foundation, intersecting lattice-based cryptography, vision transformers, and large language models (LLMs).

Prior to joining GSU, I was a faculty member at the National Institute of Technology in India. 

Before that, I spent two beautiful years as a Master's student (focused on Information Security) at the Dept of Computer Science & Engineering at the Indian Institute of Technology.

When I am not researching or spending time with my family, I spend my free time playing drums, traveling, and reading books. 

Publications:

• Javad Rafiei Asl, Prajwal Panzade, Eduardo Blanco, Daniel Takabi, Zhipeng Cai. RobustSentEmbed: Robust Sentence Embeddings Using Adversarial Self-Supervised Contrastive Learning. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL Findings) 2024 (supported by Microsoft and NSF).

• Golnoush Haddadian, Prajwal Panzade, Daniel Takabi, Min Kim. Evaluating private artificial intelligence (AI) curriculum in computer science (CS) education: Insights for advancing student-centered CS learning. The 18th International Conference of the Learning Sciences/Computer-Supported Collaborative Learning (ICLS/CSCL-2024) (supported by NSF).

• Prajwal Panzade, Daniel Takabi and Zhipeng Cai. I Can’t See It But I Can Fine-tune It: On Encrypted Fine-tuning of Transformers using Fully Homomorphic Encryption. PPAI-24@The 38th Annual AAAI Conference on Artificial Intelligence 2024 (supported by Microsoft and NSF). 

• Prajwal Panzade, Daniel Takabi and Zhipeng Cai. MedBlindTuner: Towards Privacy-preserving Fine-tuning on Biomedical Images with Transformers and Fully Homomorphic Encryption. W3PHIAI-24@The 38th Annual AAAI Conference on Artificial Intelligence 2024 (supported by Microsoft and NSF).

• Prajwal Panzade, Daniel Takabi and Zhipeng Cai. Privacy-preserving Machine Learning using Functional Encryption: Opportunities and Challenges. IEEE Internet of Things Journal (IF: 10.6) (supported by Microsoft and NSF).

• Haddadian G, Takabi D, Panzade P, Kim M. A Design Study of Problem-centered Instruction (PCI) for Private Artificial Intelligence (AI) Curriculum Development. Association for Educational Communications and Technology Conference 2023 (supported by NSF). 

• Prajwal Panzade and Daniel Takabi. FENet: Privacy-preserving Neural Network Training with Functional Encryption. IWSPA @ ACM CODASPY 2023 (supported by Microsoft and NSF).  

• Ghazvinian P, Podschwadt R, Panzade P, Rafiei MH, Takabi D. Poster: Packing-aware Pruning for Efficient Private Inference based on Homomorphic Encryption. IEEE Symposium on Security & Privacy 2023

• Prajwal Panzade and Daniel Takabi. Poster: Privacy-preserving Neural Network with Functional Encryption. IEEE Symposium on Security & Privacy 2022

• Prajwal Panzade and Daniel Takabi. SoK: Privacy Preserving Machine Learning using Functional Encryption: Opportunities and Challenges. 

• Prajwal Panzade and Daniel Takabi. Towards Faster Functional Encryption for Privacy-preserving Machine Learning. IEEE International Conference on Trust, Privacy, and Security in Intelligent Systems, and Applications, Dec 2021. IEEE (supported by Microsoft and NSF).

• Prakash CS, Panzade PP, Maheshkar S, Om H. Detection of Copy-move forgery using AKAZE and SIFT keypoint extraction. Journal of Multimedia Tools and Applications. May 2019. Springer. 

• Panzade PP, Prakash CS, Maheshkar S. Copy-move forgery detection by using HSV preprocessing and keypoint extraction. In Parallel, Distributed and Grid Computing (PDGC), 2016 Fourth International Conference on 2016 Dec 22 (pp. 264-269). IEEE.

• Geethika S, Sai Sree I, Pranathi A, Prajwal P, Advertisements and Multimedia Recommendation based on Age, Gender and Emotion (AMRAGE). ICCCMLA 2019: International Conference on Cybernetics, Cognition, and Machine Learning Applications. Springer. 

Professional Services:

• Network and Distributed System Security (NDSS) Symposium 2025 - Artifact Evaluation Committee

• IEEE Symposium on Security and Privacy 2024 - Posters Program Committee

• IEEE Transactions on Computers - Reviewer

• CAI @ IEEE TrustComm 2023 -Technical Program Committee

• IEEE Symposium on Security and Privacy 2024 (IEEE S&P) - Web Chair

• Network and Distributed System Security (NDSS) Symposium 2024 - Artifact Evaluation Committee

• Privacy Enhancing Technologies Symposium 2024 (PETS) - Artifact Review Committee

• IEEE Symposium on Security and Privacy 2023  (IEEE S&P) - Web Chair

• Member of the Board of Studies at Government College of Engineering Amravati

Honors and Awards:

• Award for Contribution to the Organizing Committee of IEEE Symposium on Security & Privacy 2024

• Travel Grant Award - PPAI-24@The 38th Annual AAAI Conference on Artificial Intelligence 2024

• Travel Grant Award - IEEE Symposium on Security & Privacy 2022 

• 5th place - World-level Crypto Hackathon organized by FENTEC GROUP under the EU H2020 project in conjunction with the International Association for Cryptologic Research Real World Crypto Symposium 2021

• Registration Grant Award- IEEE Symposium on Security and Privacy 2021 

• Registration Grant Award- ACM Conference on Computer and Communications Security (CCS) 2020 

• Registration Grant Award- 41st  IEEE Symposium on Security and Privacy 2020