- Raj Parihar, Meta
- Fanny Nina Paravecino, Microsoft
- Satyam Srivastava, D-Matrix
- Tao (Terry) Sheng, Oracle
- Kushal Datta, Nvidia
- Ananya Pareek, Apple
- Sushant Kondguli, Meta
- Michael Goldfarb, Waymo
- Prerana Maslekar, Microsoft
Raj Parihar link
Dr. Raj Parihar is a Technical Lead Manager at Meta in the Infra Silicon ASIC group. Previously, he was the Chief AI Architect at d-Matrix and help defined the flagship product Corsair. Prior to that, Dr. Parihar was part of Microsoft Silicon Engineering and Solutions (SES) group and worked on future generation of Brainwave systems and at Cadence/Tensilica, he was involved in architectural exploration and performance analysis of neural network AI processor DNA 100. He also contributed to the microarchitectural enhancements (next generation branch predictors and cache prefetchers) of P-series Warrior cores at MIPS/ImgTech. His work on Cache rationing won the best paper award at ISMM’16. Dr. Parihar received his Doctorate and Masters from University of Rochester, NY and his Bachelors from Birla Institute of Technology & Science, Pilani, India.
Michael Goldfarb link
Michael Goldfarb is a Staff Engineer at Waymo working on HW/SW architecture for machine learning. Previously he was at Qualcomm Research where he contributed to many important features of the AI 100 accelerator. For a short time Michael was at NVIDIA on various projects in the Compute Architecture group for high performance training, specifically compilers, kernels and architecture for deep learning. Prior to that, he was at Qualcomm Research where he worked on optimizing AI/ML applications for Snapdragon powered devices and developed new accelerator architectures for low power on device inference. His research interests are in machine learning, compilers, parallel programming and accelerator architecture. Michael received his Masters and Bachelors degrees from Purdue University (West Lafayette, IN).
Satyam Srivastava link
Dr. Satyam Srivastava is the Chief AI Software Architect at d-Matrix Corporation. He works on building the software stack for new AI accelerators. In his prior role at Intel he worked on enabling machine learning and media systems on Intel compute architectures. His interests include machine learning, visual computing, and compute accelerators. Dr. Srivastava obtained his Doctorate degree from Purdue university (West Lafayette, IN) and Bachelor’s degree from Birla Institute of Technology and Science, Pilani (India).
Tao (Terry) Sheng link
Dr. Tao Sheng is a Director of Machine Learning at Oracle Cloud. He has been working on multiple cutting-edge projects in the research areas of Computer Vision and Neutral Language Understanding for more than 12 years. Prior to Oracle, he worked with Amazon, Qualcomm and Intel. He has published more than ten US and International patents and ten research papers.
Kushal Datta link
Dr. Kushal Datta is Sr. Product Manager of communications and IO libraries for AI, data analytics and HPC at Nvidia. Previously, at Intel Data Center Group, he invented new techniques to expedite deep learning model training and inference on Xeon architecture. His interests include creating new tools and methods to improve overall wall clock time of complex AI and scientific applications on large scale systems. He has published over twenty academic papers, several white papers and blogs. He holds five granted U.S. patents. He received his Ph.D. in ECE from University of North Carolina at Charlotte and Bachelors in Computer Science from Jadavpur University, India.
Ananya Pareek link
Ananya Pareek is a System Architect at Apple. Currently working on optimizing hardware platforms from a performance-power tradeoff perspective. Previously he has worked at Samsung on CPU core pipeline and ISA extensions for enabling faster ML computations. His interests are in developing hardware platforms for ML/Deep Learning, HW/SW codesign, and modeling systems for optimization. He received his M.S. degree from the University of Rochester, NY, and B.Tech. from Indian Institute of Technology Kanpur, India.
Fanny Nina Paravecino link
Fanny Nina-Paravecino is currently a Principal Research Eng Manager at Microsoft AI Frameworks, where she leads an interdisciplinary team in Microsoft Azure operating at the intersection of high-performance computing and artificial intelligence (AI) to deliver the fastest AI execution at the cloud scale.
Prerana Maslekar link
Prerana Maslekar is a Silicon Verification Engineer in Silicon Engineering Group at Microsoft. She works on ensuring design correctness for hardware deployed in Azure cloud. Prior to this, she worked on verification of sensors used in microsoft devices. Prerana has a masters from The University of Texas at Austin in the track of Architecture, Computer Systems and Embedded Systems. Her interests lie in Accelerator architecture, ML accelerator hardware, security attacks exploiting architecture flaws and data center architectures.
Sushant Kondguli link
Dr. Sushant Kondguli is a Graphics Architect at Meta Reality Labs Research where his research focuses on low power architectures for on-head rendering devices. Prior to that, Dr. Kondguli was a Mobile GPU architect at the Advanced Computing Lab of Samsung where he helped develop the XClipse GPU architecture used in Samsung’s flagship galaxy smartphones. He received in PhD and B.Tech. degrees from University of Rochester and IIT Kharagpur, respectively.