Ananth N V R

Software Engineer

Bengaluru, Karnataka, India7 yrs 11 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in FPGA prototyping and SoC design.
Hands-on experience with high-level synthesis tools.
Strong background in image processing and machine learning.

Stackforce AI infers this person is a hardware design engineer with expertise in FPGA and SoC technologies.

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Skills

Core Skills

Fpga PrototypingSystem On A Chip (soc)Fpga SynthesisHardware Accelerated ImplementationImage Processing

Other Skills

ManagementResearchLeadershipMicrocontrollersField-Programmable Gate Arrays (FPGA)Signal ProcessingVerilogPythonCMatlabEmbedded SystemsDigital DesignsInternet of ThingsMSP430xilinx SDSoC

About

open to learn new technologies and interested in exploring and creating hardware architectures for next generation

Experience

7 yrs 11 mos

Total Experience

3 yrs 11 mos

Average Tenure

5 yrs

Current Experience

Nvidia

Sr ASIC engineer

May 2021 – Present · 5 yrs · Bengaluru, Karnataka, India

FPGA prototypingManagementResearchLeadershipImage ProcessingMicrocontrollers+15

Synopsys inc

2 roles

Applications Engineer 2

Jun 2020 – May 2021 · 11 mos

Applications Engineer for FPGA prototyping

FPGA prototyping

Applications Engineer 1

Jun 2018 – Jun 2020 · 2 yrs

Applications engineer for FPGA Synthesis and Prototyping in verification group(VG) at synopsys

FPGA SynthesisFPGA Prototyping

Robert bosch centre for cyber-physical systems @ iisc

Summer Intern

May 2017 – Jul 2017 · 2 mos · bangalore

worked on hardware accelerated implementation of optical flow algorithm in Zynq 7000 series based SoC design board.Used high level synthesis tools like Vivado HLS to get the RTL from C/C++ and used profiling/pragmas to make the compiler generate the optimal solution with the existing hardware.

hardware accelerated implementationoptical flow algorithmZynq 7000 serieshigh level synthesisVivado HLS

Indian institute of technology, gandhinagar

Summer Intern

May 2016 – Jul 2016 · 2 mos · gandhinagar

worked on object segmentation using machine learning techniques in image processing.Project includes edge detection using structured Random forests classifier followed by curve evolution technique to get the contour around the segmented object.This can be used in surveillance cameras to follow specific object once detected.

object segmentationmachine learningimage processingedge detectionstructured Random forests classifiercurve evolution technique