Applied AI R&D

Hi,

I’m a Computer Vision and Machine Learning specialist currently based out of warm Dallas, Texas (I was previously a Bay area native).

I have been in the AI industry for over 12 years now, have enjoyed being a spectator as well as an enabler, working on emerging trends (computer vision, deep learning era, self-driving vehicles, IoT, Generative AI and LLM’s). It has been a delightful ride so far watching the field of computer vision blossom and spread it’s web across industries. What we are witnessing today is just the beginning, and I am excited for what is yet to come! (And probably AI will figure out combating climate change issues someday.)

I have a background in Electronics, Telecommunication and Computer Science Engineering. I have adventurously worn multiple hats during my career- IC, Technical Lead, Researcher, Manager, early stage startup engineer < 5 engineers, interim Technical Product Manager. I have experience working with multidisciplinary teams from various backgrounds and skill-sets; small, agile startup teams, corporate cultures, mid-size and post-IPO companies. Though I have had my share of fun at diverse work cultures and team sizes, my dream tribe remains a small high-impact team spinning out quick MVP’s with tangible, iterative, customer feedback loops.

I value curiosity, humility, knowledge-sharing and mature coding practices and believe that a good attitude surpasses intelligence any day for a functional & high-performing team.

My work life frequently focuses on solving problems in the following domains:

  • Practical AI applications in connected vehicle technology (privacy, safety, distraction control)
  • Intersection of computer vision and edge computing
  • Machine learning based recommender systems
  • NLP: Information Retrieval, Semantic context based search, Vector search
  • IoT security applications and automation (smart home, shared spaces)
  • machine unlearning theory for privacy preserving model generation
  • facial analysis and tracking
  • person identity abstraction, encapsulation and tracking in surveillance
  • scene understanding and ontology abstraction
  • semantic visual understanding and reasoning systems
  • theoretical computer vision algorithms
  • image retrieval for recommendation systems
  • privacy-preserving AI and federated learning applications

Other areas I enjoy exploring in my spare time are applications of computer vision in medical imaging, climate change and traditional ML applications.

Professional Updates

  • August 2023: AI Ethics Reviewer for NeurIPS 2023, ensuring submissions follow principles of ResponsibleAI.
  • 2023: Elevated to Senior IEEE Member
  • June 2023: Reviewer for IEEE ITSC, 2023
  • July 2023: Invited to serve as Industry Expert judge at Golden Bridge Awards
  • 2023: Invited to serve on reviewer committee for multiple Machine learning projects at NASA’s FDL-X summer research sprint, co-organized by NASA, Trillium Technologies, Google Cloud, NVIDIA
  • July 2023: Invited to serve as Panelist and Session Moderator at NASA’s Frontier Development Lab on the ML talk ‘Machine Learning Theory and Integration’
  • March 2023: A Generative AI project I closely worked on was showcased at New York International Autoshow (NYIAS)
  • May 2023: Invited to serve as Judge for Pass It On awards (PIO) at GHC 2023.
  • September 2022: Patent application filed by Latch Inc for a new product vertical I led and managed as principal investigator while at Latch
  • 2020 : Invited to serve as Judge for Pass It On awards (PIO) at GHC 2020. I helped the team review projects grants of women in STEM and help advance women in computing
  • March 2019 : Served on two committees (Data Science and Poster Session) at GHC conference, review speaker and paper applications.
  • March 2018: Artificial Intelligence Committee member at GHC conference, review speaker and paper applications.
  • June 2017: Patent application granted ‘Real time Driving Difficulty Categorization’
  • 2017: Two patents filed for Road Scene and In-vehicle Situation Understanding
  • November 2016: Invited by ITSC to serve as Session Chair for Driver Assistance Systems track IV at ITSC, Rio de Janeiro, Brazil
  • November 2016: Invited by ITSC to serve as Session Chair for Driver Assistance Systems track II at ITSC, Rio de Janeiro, Brazil
  • September 2016: Invited to serve as AI judge for IoT Hackathon at SJSU graduate college of engineering.
  • May 2016: Patent application filed by Toyota Motor Corporation (on driver distraction and in-car hand movement analysis)
  • August 2016: Paper accepted to IEEE ITSC 2016, Rio de Janeiro, Brazil
  • March 2016: Two patent applications on driver distraction analysis and road scene understanding, filed by Toyota Motor Corporation
  • 2016-Present: Reviewer for multiple SAE World Congress conference publications
  • 2016: Paper accepted at SAE World Congress, Detroit
  • 2015: Paper accepted at IEEE ITSC (Intelligent Transportation Systems) conference, Spain
  • June 2015: Technical Committee Judge for Innovation Series hosted by US Department of Veteran Affairs. Helped review prosthetic design robotics projects aimed to improve mobility of veterans
  • April 2015: Interviewed by Sirius XM on Empowering Women in Tech, where I discussed my experiences as a woman in STEM and how automotive industries and connected technology can help provide focused assistance using AI to women, mothers and pregnant women.
  • February 2014: Patent application filed by Toyota Motor Corporation ‘Real time Driving Difficulty Categorization’
  • November 2012: Paper accepted at Uncertainty in Artificial Intelligence Conference, Washington.
  • August 2012: Patent application filed by Toyota Motor Corporation on road scene understanding and driving score generation
  • May 2012: Joined Toyota’s Infotechnology Centre (US) as a Computer Vision Researcher in their Intelligent Systems Division(comprising of roboticists, AI, ML and Systems experts).
  • September 2011: Assisted my team at Disney Imagineering R&D present 3D Volumetric Display prototype at Emerging Technologies showcase at SIGGRAPH 2011, Vancouver, Canada
  • 2011: Selected as a Disney Imagineer at their R&D headquarters for summer of 2012 through an aptitude challenge and interview, where I directly apprenticed under Dr. Lanny Smoot in Disney’s Glendale labs.
  • 2010: Image Processing Research Assistantship at NSF ERC for Reconfigurable Manufacturing Systems, implementing research paper for TRINA(Toyota) collaborative project, under the guidance of Professor Yoram Korem.
  • 2009: Admitted to Computer Science Department at University of Michigan, Ann Arbor to specialize in Intelligent System Masters track.
  • 2006-2008: Selected from all engineering divisions as part of a 10 person team to work on a two-year industrial research project for Konkan Railway Corporation Limited where I investigated machine learning techniques to detect faulty point machine systems and trigger real-time warning alerts to control station to prevent mishaps.

I do pro-bono consultations, mentoring and reviewing. If you wish to reach me, you can do so via email or LinkedIn (links on the left).