>Part of Apps team responsible for delivering reference designs for Zynq Ultrascale+ & Versal Devices.> Video Machine Learning Reference Example Designs for AV, Automotive Segments.> Speech Recognition on edge.> Exploring Deep Learning based LIDAR algorithm deployment on Xilinx Devices.> HW software co-design and optimal Partitioning of Application between ARM, FPGA & AI Engines.> Application Mapping on heterogeneous Architectures> Automation of… Show more >Part of Apps team responsible for delivering reference designs for Zynq Ultrascale+ & Versal Devices.> Video Machine Learning Reference Example Designs for AV, Automotive Segments.> Speech Recognition on edge.> Exploring Deep Learning based LIDAR algorithm deployment on Xilinx Devices.> HW software co-design and optimal Partitioning of Application between ARM, FPGA & AI Engines.> Application Mapping on heterogeneous Architectures> Automation of Design & test Methodologies & setting up regressions.> Customization of Embedded Linux for Xilinx SoC> Reference designs for PCIe, MIPI & HDMI Video Interfaces> Experienced with Pre-production boards bring-up.> Debugging System Level Customer Issue Show less

Part of the System's team, responsible for development and up-gradation of VCU & RFSOC Reference designs.> Working on VCU (Video Codec Unit) Reference Designs targeted for Zynq Ultrascale+ Devices.>Exploring & working to optimize Machine learning Algorithms for AI Engine on Xilinx Versal Devices.

Working of Hardware Implementation of Deep Learning. In general my work includes> Exploring popular architectures of Convolutional Neural Networks>Exploring state of the art Existing FPGA & ASIC accelerators for inference> Exploiting sparsity and network pruning for Energy efficiency> Proposing Novel Architectures and implementing in Verilog HDL> Extracting model data and parameters from pre-implemented models in caffeCurrently I am working on a novel… Show more Working of Hardware Implementation of Deep Learning. In general my work includes> Exploring popular architectures of Convolutional Neural Networks>Exploring state of the art Existing FPGA & ASIC accelerators for inference> Exploiting sparsity and network pruning for Energy efficiency> Proposing Novel Architectures and implementing in Verilog HDL> Extracting model data and parameters from pre-implemented models in caffeCurrently I am working on a novel architecture focused on energy efficiency of CNN. In future, I plan to work in Hardware-software co-design for efficient implementation of CNN & Accelerating the training of CNN of specialized Hardware. I plan to use High level languages such as C/C++ or openCL for next work with HLS Tool. > Implementation of essential communication blocks on WARPLab, a MATLAB based flow for Proof of concept & in verilog for FPGA based Implementation. > Implemented a hardware efficient, in-place FFT Architecture in verilog. Show less

Built an MVP for a online food and grocery delivering platform, managed web development team and overlooked at developing operations team.Shutdown as we couldn't raise funds to continue

I was part of Patent Licensing and technology commercialisation Team and have been involved with various kind of projects including Infringement Analysis, Identification of potential licensee,Preparing Evidence of Use (EoU) / Claim chart, Patent Ranking, File Wrapper Analysis, SWOT Analysis, Product Listing and Market Research.