Devesh Walawalkar

Devesh Walawalkar

Artificial Intelligence Researcher

Flawless AI

About Me

I am an avid researcher in field of Artificial Intelligence, Deep Learning and Computer Vision. My research interests include Object Detection, facial analysis (Detection, Identification, Landmarking etc.), 2D/3D Instance Segmentation, Deep Learning model compression, Self-Supervised Learning and Scene Understanding. I also specialize in compute resource constrained real time inference of Deep Learning based Computer Vision models for various mobile devices like Nvidia AI embedded systems, Apple iphone, drones etc.

I currently work full time as a Lead Research Engineer at an exciting Hollywood AI startup called Flawless AI. I spend my time researching and building core Computer Vision AI systems for the movie/TV series domain at my startup as well as working on personal research projects.


  • Artificial Intelligence
  • Computer Vision
  • Facial Analysis
  • Pattern Recognition


  • MSc in Electrical and Computer Engineering

    Carnegie Mellon University, USA

  • BSc in Electronics Engineering

    Veermata Jijabai Technological Institute, India

Recent News

April, 2024:
Served as official reviewer for ECCV 2024 and ICPR 2024
March, 2024:
Filed 1 US patent
May, 2023:
Filed 2 US patents. Links 1,2
Aug, 2022:
Joined Flawless AI as Research Engineer!
Aug, 2020:
1 paper accepted at ECCV 2020.
Feb, 2020:
1 paper published in WIREs Journal.
Jan, 2020:
1 paper accepted at ICASSP 2020.
Jan, 2020:
Joined Honeywell as ML Research Engineer!
May, 2019:
Completed Masters studies in ECE from Carnegie Mellon University.
Feb, 2019:
Tech article on MedAL paper published.
Dec, 2018:
Received Best Overall Paper Award at ICMLA 2018.



Research Engineer

Flawless AI

Aug 2022 – Present Los Angeles, CA
  • Conducting lead research on AI based facial analysis tech (Face detection, Face identification, Face motion tracking etc.).
  • Developing core AI systems for character facial analysis for movie/TV show domain.
  • Conducting research on data efficient techniques for Neural Face Rendering algorithms.

Machine Learning Research Engineer

Honeywell Robotics

Jan 2020 – Jul 2022 Pittsburgh, PA
  • Researched on Deep Learning architectures for various Computer Vision tasks.
  • Facilitated AI application knowledge across various Honeywell Robotics teams.
  • Successfully built complex Robotics AI based Perception system software.

Lead Deep Learning Researcher

Cylab, Carnegie Mellon University

Sep 2018 – Dec 2019 Pittsburgh, PA
  • Worked in Professor Marios Savvides’s lab at CMU Cylab
  • Led a team of Deep learning researchers and iOS app developers to create a proprietary iOS application for driver drowsiness detection.
  • Led real time object detection for edge application based projects funded by US DTRA.
  • Researched a novel framework for Knowledge Distillation based Deep Learning based model compression.

Summer Research Intern

Cylab, Carnegie Mellon University

Jun 2018 – Aug 2018 Pittsburgh, PA
  • Interned in Professor Marios Savvides’s lab at CMU Cylab
  • Researched on computationally efficient yet accurate Computer Vision architectures for performing various facial biometrics tasks which include face detection, face landmarking and face pose estimation.

Graduate Research Assistant

Carnegie Mellon University

Jan 2018 – May 2018 Pittsburgh, PA
  • Worked as research assistant to Professor Asim Smailagic in ECE dept, CMU
  • Researched onnovel active machine learning techniques being applied for medical imaging analysis.
  • Invented a new active machine learning technique to query the most important unlabeled images that the trained model is uncertain about. Technique was developed in context of training CNN models to detect diabetic retinopathy in eye color fundus images.


Artificial Intelligence

Computer Vision


Image Processing





Project Management




Human Driver Drowsiness Detection

Artifical Intelligence based iOS application for detecting driver drowsiness

Real Time Object Detection on Jetson Xavier

Research on compressing state-of-the-art algorithms for edge AI applications

Forecasting Path from Expert Demonstrations

Research on path forecasting for self driving vehicle using CARLA simulator

Deep Audio-Visual Model for Speech Recognition

Research on infusing attention mechanism for combined Deep Audio-Visual Models

Contact Me

  • 1221 2nd St, 4th Flr, Los Angeles, CA 90403

Live site visitor locations