S

Siddharth Aravindan

CTO

Bengaluru, Karnataka, India9 yrs 7 mos experience
Highly Stable

Key Highlights

  • Ph.D. in Reinforcement Learning from NUS.
  • Expertise in Computer Vision and Machine Learning.
  • Experience at leading tech companies like Samsung and NVIDIA.
Stackforce AI infers this person is a Computer Vision and Machine Learning expert in the tech industry.

Contact

Skills

Core Skills

Computer VisionMachine LearningReinforcement LearningDeep LearningProgramming

Other Skills

3D VisionAugmented Reality (AR)JavaLinuxPythonPython (Programming Language)SQLTensorFlow

About

Computer Vision Researcher at Samsung R&D India - Bangalore Previously - Ph.D. in Reinforcement Learning from the National University of Singapore

Experience

Samsung r&d institute india

Chief Engineer

Apr 2023Present · 2 yrs 11 mos · Bengaluru, Karnataka, India · Hybrid

Computer Vision3D VisionAugmented Reality (AR)Machine Learning

National university of singapore

4 roles

Research Fellow

Promoted

Mar 2022Mar 2023 · 1 yr

LinuxProgrammingMachine LearningReinforcement LearningTensorFlowDeep Learning+1

Course Instructor

Jun 2021Jan 2022 · 7 mos

ProgrammingMachine LearningPython (Programming Language)

Graduate Teaching Assistant

Jan 2018May 2021 · 3 yrs 4 mos

ProgrammingMachine LearningReinforcement LearningDeep LearningPython (Programming Language)

PHD Researcher

Aug 2017Aug 2022 · 5 yrs

LinuxProgrammingMachine LearningReinforcement LearningTensorFlowDeep Learning+1

Nvidia

Artificial Intelligence Researcher

Jul 2018Jun 2019 · 11 mos · Singapore

LinuxProgrammingMachine LearningReinforcement LearningTensorFlowDeep Learning+1

Amazon.com

Software Develeopment Engineer

Jun 2014Jul 2015 · 1 yr 1 mo · Hyderabad Area, India

  • Worked on several software development projects that resolved major business requirements while coordinating from team members across various teams at Amazon.
LinuxSQLProgramming

Rwth aachen university

Intern

May 2013Jul 2013 · 2 mos · Aachen, Germany

  • Successfully designed and implemented a parallelized code for the core of Support Vector Machines on a Coarse Grained Reconfigurable Architecture (CGRA). Many specialized instructions such as minimum and maximum of two floating point numbers were included in the basic functions an ALU could perform, as this increased the efficiency. The basic architecture was also modified a little for its implementation. Kernels such as dot product and (dot product)^k were also successfully implemented on the same architecture. The work was guided by Prof. Anupam Chattopadhyay.
Programming

Education

National University of Singapore

Doctor of Philosophy - PhD — Computer Science

Aug 2017Aug 2022

Indian Institute of Technology, Bombay

Master of Technology - MTech — Computer Science and Engineering

Jan 2015Jan 2017

Indian Institute of Technology, Patna

Bachelor of Technology - BTech — Computer Science and Engineering

Jan 2010Jan 2014

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