Deep Reinforcement Learning in High Frequency Trading. - Prakhar Ganesh; Puneet Rakheja (CoRR, 2018)

Abstractive Summarization of Spoken and Written Conversation. - Prakhar Ganesh; Saket Dingliwal (CoRR, 2019)

Literature Survey on Finding Influential Communities in Large Scale Networks. - Prakhar Ganesh; Saket Dingliwal; Rahul Agarwal (CoRR, 2019)

Assessing and Mitigating Impact of Time Delay Attack: Case Studies for Power Grid Controls. - Xin Lou; Cuong Tran 006; Rui Tan 001; David K. Y. Yau; Zbigniew T. Kalbarczyk; Ambarish Kumar Banerjee; Prakhar Ganesh (IEEE J. Sel. Areas Commun., 2020)

Free Lunch for Co-Saliency Detection: Context Adjustment. - Lingdong Kong; Prakhar Ganesh; Tan Wang; Junhao Liu 001; Yao Chen 008; Le Zhang (CoRR, 2021)

Compressing Large-Scale Transformer-Based Models: A Case Study on BERT. - Prakhar Ganesh; Yao Chen 008; Xin Lou; Mohammad Ali Khan; Yin Yang 001; Hassan Sajjad 001; Preslav Nakov; Deming Chen; Marianne Winslett (Trans. Assoc. Comput. Linguistics, 2021)

Learning-Based Simultaneous Detection and Characterization of Time Delay Attack in Cyber-Physical Systems. - Prakhar Ganesh; Xin Lou; Yao Chen 008; Rui Tan 001; David K. Y. Yau; Deming Chen; Marianne Winslett (IEEE Trans. Smart Grid, 2021)

HiKonv: High Throughput Quantized Convolution With Novel Bit-wise Management and Computation. - Xinheng Liu; Yao Chen 008; Prakhar Ganesh; Junhao Pan; Jinjun Xiong; Deming Chen (ASP-DAC, 2022)

YOLO-ReT: Towards High Accuracy Real-time Object Detection on Edge GPUs. - Prakhar Ganesh; Yao Chen 008; Yin Yang 001; Deming Chen; Marianne Winslett (WACV, 2022)

On The Impact of Machine Learning Randomness on Group Fairness. - Prakhar Ganesh; Hongyan Chang; Martin Strobel 001; Reza Shokri (FAccT, 2023)

Model Multiplicity for Responsible AI. - Prakhar Ganesh (AIES (2), 2024)

An Empirical Investigation into Benchmarking Model Multiplicity for Trustworthy Machine Learning: A Case Study on Image Classification. - Prakhar Ganesh (WACV, 2024)

Towards More Realistic Extraction Attacks: An Adversarial Perspective. - Yash More; Prakhar Ganesh; Golnoosh Farnadi (CoRR, 2024)

Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in ML. - Prakhar Ganesh; Usman Gohar; Lu Cheng; Golnoosh Farnadi (CoRR, 2024)

The Data Minimization Principle in Machine Learning. - Prakhar Ganesh; Cuong Tran 007; Reza Shokri; Ferdinando Fioretto (FAccT, 2025)

The Curious Case of Arbitrariness in Machine Learning. - Prakhar Ganesh; Afaf Taïk; Golnoosh Farnadi (CoRR, 2025)

Say It Another Way: Auditing LLMs with a User-Grounded Automated Paraphrasing Framework. - Cléa Chataigner; Rebecca Ma; Prakhar Ganesh; Afaf Taïk; Elliot Creager; Golnoosh Farnadi (CoRR, 2025)

SoK: Data Minimization in Machine Learning. - Robin Staab; Nikola Jovanovic 001; Kimberly Mai; Prakhar Ganesh; Martin T. Vechev; Ferdinando Fioretto; Matthew Jagielski (CoRR, 2025)