SWiF: A Simplified Workload-Centric Framework for FPGA-Based Computing. - David Ojika; Piotr Majcher; Wojciech Neubauer; Suchit Subhaschandra; Darin Acosta (FCCM, 2017)

Accelerating High-energy Physics Exploration with Deep Learning. - Dave Ojika; Darin Acosta; Ann Gordon-Ross; Andrew Carnes; Sergei Gleyzer (PEARC, 2017)

Research Opportunities in Heterogeneous Computing for Machine Learning. - Herman Lam; David Ojika (HPCS, 2018)

Accelerating Scientific Discovery with SCAIGATE Science Gateway. - Chao Jiang; David Ojika; Bhavesh Patel; Ann Gordon-Ross; Herman Lam (eScience, 2019)

PCS: A Productive Computational Science Platform. - David Ojika; Ann Gordon-Ross; Herman Lam; Shinjae Yoo; Younggang Cui; Zhihua Dong; Kirstin Kleese van Dam; Seyong Lee; Thorsten Kurth (HPCS, 2019)

Acceleration of Scientific Deep Learning Models on Heterogeneous Computing Platform with Intel® FPGAs. - Chao Jiang; Dave Ojika; Thorsten Kurth; Prabhat; Sofia Vallecorsa; Bhavesh Patel; Herman Lam (ISC Workshops, 2019)

Addressing the Memory Bottleneck in AI Model Training. - David Ojika; Bhavesh Patel; G. Anthony Reina; Trent Boyer; Chad Martin; Prashant Shah (CoRR, 2020)

Optimized FPGA-based Deep Learning Accelerator for Sparse CNN using High Bandwidth Memory. - Chao Jiang; David Ojika; Bhavesh Patel; Herman Lam (FCCM, 2021)

Towards Sustainable Energy-Efficient Data Centers in Africa. - David Ojika; Jayson Strayer; Gaurav Kaul (CoRR, 2021)

FSHMEM: Supporting Partitioned Global Address Space on FPGAs for Large-Scale Hardware Acceleration Infrastructure. - Yashael Faith Arthanto; David Ojika; Joo-Young Kim 001 (FPL, 2022)