Krishneel Chaudhary

  • エンジニア

Krishneel Chaudhary

  • 食品加工
  • 建設

In 2010, I completed my bachelors degree in Computer Science from The University of the South Pacific in Fiji. In 2011 I was awarded the MEXT scholarship to further my education in Japan. I joined Arai Lab in Osaka University in 2012 and completed my Masters degree in 2014. My Master thesis research focused on Computer Vision and Machine Learning, espically on object tracking using classical methods. After graduation I joined JSK (Inaba) Lab in The University of Tokyo for PhD. I completed my PhD in 2017 and continued working in JSK Lab as a Postdoctoral researcher. My PhD thesis focused on the idea of automation of object annotation task. Using end-to-end learning techniques, I was able to annotate unknown in-hand object via sequential observation of human actions. Moreover, during my PhD I worked on number of international robotics challenges; 2014 Tomato picking challenge (Japan), 2015 DARPA disaster robotic challenge (USA) and 2017 MBZIRC drone challenge (UAE). On all these projects, I worked on image processing related tasks. As a Postdoctoral researcher, I worked with Toyota on their HSR project where I wrote alogithms to increase HSR’s autonomous capabilities. After completing my Postdoc, I joined DeepX.


In this era of intelligence, large number of task are still executed with manual labour and machines are unable to make decisions. What make this complex and why these problems are not solved yet? In the past, one of the biggest loophole in research and development was lack of interdisciplinary synergy. To achieve automation systemic and seamless integration of smart software and hardware is fundamentally most important. While both hardware and software has matured over the years, smart software solution is still lacking. With mission of automate anything and everything, DeepX has set the goals that would bridge the biggest gap i.e. intelligence software.



  • Deep Learning - Data driven solutions to problems
  • Image processing and computer vision - 2D, 2.5D and 3D sensing
  • Deep reinforcement learning
  • Automation- Integration of intelligent alogrithms on robots


  • Snowboarding (although I am seriously bad it)

  • Fishing