I am a Ph.D. student in Computer Engineering at USC, advised by Prof. Viktor K. Prasanna and Prof. Raj Kannan. I’m interested broadly in ML Systems, Memory-Bound Inference, and Sparse ML.
My full CV can be found here.
My areas of expertise are:

• Data prefetching, caching, and data locality (spatial/temporal)
• Performance modeling, parallel algorithm design, and scalability
• Hardware/software co-design for neural network inference

Publications

1. [CF ‘24] TabConv: Low-Computation CNN Inference via Table Lookups
   Neelesh Gupta*, Narayanan Kannan*, Pengmiao Zhang*, Viktor K. Prasanna
   Proceedings of the 21st ACM International Conference on Computing Frontiers (CF ‘24)
   

2. [JPDC] Net2Tab: Neural Network to Tables for Data Prefetching (In Review)
   Pengmiao Zhang, Neelesh Gupta, Rajgopal Kannan, Viktor K. Prasanna
   Transactions on Parallel and Distributed Systems (TPDS)
   

3. [IPDPS ‘24] Attention, Distillation, and Tabularization: Towards Practical Neural Network-Based Prefetching
   Pengmiao Zhang*, Neelesh Gupta*, Rajgopal Kannan, Viktor K. Prasanna
   38th IEEE International Parallel & Distributed Processing Symposium (IPDPS ‘24)
   

4. [HPEC ‘24] Benchmarking Edge AI Platforms for High-Performance ML Inference
   Rakshith Jayanth*, Neelesh Gupta*, Viktor K. Prasanna
   29th IEEE High Performance Extreme Computing Conference (HPEC ‘24)
   

5. [HPEC ‘23] PaCKD: Pattern-Clustered Knowledge Distillation for Compressing Memory Access Prediction Model
   Neelesh Gupta*, Pengmiao Zhang*, Rajgopal Kannan, Viktor K. Prasanna
   28th IEEE High Performance Extreme Computing Conference (HPEC ‘23)
   

6. [KDD-UC ‘22] Did your child get disturbed by an inappropriate advertisement on YouTube?
   Jeffrey Liu, Rajat Tandon, Uma Durairaj, Jiani Guo, Spencer Zahabizadeh, Sanjana Ilango, Jeremy Tang, Neelesh Gupta, Zoe Zhou, Jelena Mirkovic
   28th Proceeings of Knowledge Discovery and Data Mining Undergraduate Consortium (KDD-UC ‘22)
   

(Last update: Aug. 4, 2025)