Research Scientist, AI · Meta

Ashish Jaiswal

Research Scientist at Meta working on AI for content understanding in Facebook Feed and Notifications.
PhD in Computer Science (UT Arlington, 2023). 15+ publications, 3k+ citations.

3k+

Citations

15+

Publications

h-index 10

Google Scholar

About

I am a Research Scientist at Meta on the Facebook Feed & Notifications AI team. My work focuses on content understanding using large language models — building pipelines that generate signals for content categorization, quality assessment, and retrieval across Facebook.

I completed my PhD in Computer Science at UT Arlington in 2023, specializing in self-supervised learning, multimodal fusion, and human-computer interaction. My research has been cited 3k+ times across 15+ publications.

Large Language Models Agentic AI Content Understanding Knowledge Distillation Self-supervised Learning Computer Vision Human-Computer Interaction

News and Updates

  • Joined Meta as Research Scientist, AI Systems — Facebook Feed & Notifications AI team
  • Successfully defended PhD dissertation at UT Arlington
  • Session Chair and Presenter at HCII 2023, Copenhagen, Denmark
  • Interned at Meta - Audio Video Understanding team (Reels trends system)
  • Received John S. Schuchman Outstanding Doctoral Student Award, UT Arlington
  • Started PhD in Computer Science at the University of Texas at Arlington
  • Graduated with B.E. in Electronics & Communication Engineering, Tribhuvan University, Nepal

Research Vision

At Meta, I work on applied LLM research for content understanding at scale: fine-tuning models, building agentic workflows, and generating content signals for Feed and Notifications ranking.

During my PhD, I focused on self-supervised learning, multimodal fusion, and cognitive state assessment. My work spanned contrastive representation learning, sensor-based fatigue detection (fMRI, EEG, IMU), VR-based cognitive evaluation, and assistive robotics — with applications in healthcare and human-computer interaction.

Selected Publications

View full list on Google Scholar ->
  1. Jaiswal, A., Babu, A.R., Zadeh, M.Z., Banerjee, D., Makedon, F. “A Survey on Contrastive Self-supervised Learning.” Technologies 9(1), 2020. 2,304 citations [pdf]
  2. Jaiswal, A., Zadeh, M.Z., Hebri, A., Babu, A.R., Makedon, F. “A Smart Sensor Suit (SSS) to Assess Cognitive and Physical Fatigue with Machine Learning.” HCII, 2023. 28 citations [pdf]
  3. Jaiswal, A., Babu, A.R., Zadeh, M.Z., Makedon, F., Wylie, G. “Detecting Cognitive Fatigue in Subjects with Traumatic Brain Injury from FMRI Scans Using Self-Supervised Learning.” PETRA, 2023. 15 citations [pdf]
  4. Jaiswal, A., Hebri, A., Pavel, H.R., Zadeh, M.Z., Makedon, F. “SmartFunction: An Immersive VR System to Assess Attention Using Embodied Cognition.” PETRA, 2023. 3 citations [pdf]
  5. Jaiswal, A., Nale, G., An, Q., Pavel, H.R., Karim, E., Acharya, S., Makedon, F. “An Assistive Robotic System for Cognitive State Assessment in Spinal Cord Injury.” PETRA, 2024. 1 citation [pdf]
  6. Doolani, S., Wessels, C., Kanal, V., Jaiswal, A., et al. “A Review of Extended Reality (XR) Technologies for Manufacturing Training.” Technologies 8(4), 2020. 502 citations [pdf]
  7. Karim, E., Pavel, H.R., Nikanfar, S., Jaiswal, A., et al. “Examining the Landscape of Cognitive Fatigue Detection: A Comprehensive Survey.” Technologies 12(3), 2024. 40 citations [pdf]
  8. Farahanipad, F.*, Nambiappan, H.R.*, Jaiswal, A., Kyrarini, M., Makedon, F. “HAND-REHA: Dynamic Hand Gesture Recognition for Game-based Wrist Rehabilitation.” PETRA, 2020. 19 citations [pdf]
  9. Kapoor, R., Jaiswal, A., Makedon, F. “Light-weight Seated Posture Guidance System with Machine Learning and Computer Vision.” PETRA, 2022. 24 citations [pdf]
  10. Zadeh, M.Z., Babu, A.R., Jaiswal, A., Kyrarini, M., Makedon, F. “Self-Supervised Human Activity Recognition by Augmenting Generative Adversarial Networks.” PETRA, 2021. 20 citations [pdf]

Experience

Research Scientist, AI Systems — Meta, Menlo Park, CA

Jan 2024 – Present

  • Facebook Feed & Notifications AI Team
  • Build LLM-based pipelines for content understanding: categorization, quality assessment, and premium content retrieval
  • Fine-tune and distill language models to generate signals for Feed and Notifications ranking

Graduate Research & Teaching Assistant — UT Arlington, Heracleia HCC Lab

Aug 2019 – Dec 2023

  • Research in self-supervised learning, multimodal AI, and cognitive state assessment — 15+ publications, 3k+ citations
  • Built ML pipelines for physiological and visual data (fMRI, EEG, IMU, video) to assess cognitive fatigue and human activity
  • Graduate Lecturer for Human-Computer Interaction (CS 5369/6369); TA for C, Java, Linux, Digital Circuits, and Raspberry Pi Labs

Software Engineering Intern, ML (PhD) - Meta, Menlo Park, CA

May 2022 - Aug 2022

  • Audio Video Understanding Team - built Reels trends visualization system
  • Unsupervised clustering, NLP topic assignment, search indexing API

Scientific Applications Programmer - SocialEyes NP

Apr 2019 - Jul 2019

  • CV + transfer learning for retinal disease detection

Software Engineer - Insight Workshop

Apr 2018 - May 2019

  • Built core systems for healthcare and enterprise clients

Machine Learning Engineer Trainee - Insight Workshop

Dec 2017 - Apr 2018

Secretary, Robotics Club - Kathmandu Engineering College

Jun 2015 - Jul 2018

Innovator - National Innovation Center, Nepal

Oct 2016 - Sep 2017

  • Medical drone stabilization using LQR, customized GPS flight controller

Education

PhD, Computer Science - University of Texas at Arlington

Aug 2019 - Dec 2023

Focus: Computer Vision, Machine Learning, Human-Computer Interaction

B.E., Electronics and Communication Engineering - Kathmandu Engineering College

Nov 2014 - Oct 2018

Focus: Embedded Systems, Robotics, Computer Science

Projects

Understanding Cognitive Fatigue from fMRI Scans

Jul 2020

Deep RNN to predict fatigue in TBI subjects from 3D fMRI scans.

GitHub

Reels Video Trends System

Aug 2022

Unsupervised clustering + NLP to visualize trending topics in Facebook/Instagram Reels.

KrishiSathi - AgriTech Platform

Jan-Aug 2018

Web portal for farmers with ML and IoT for crop analysis.

GitHub

Semi-Autonomous Solar Panel Cleaning Robot

Dec 2017-May 2018

Won Best Engineering Award at Robocon Nepal 2018.

GitHub

GRE Vocab Wallpaper

Jul 2018

Python script that changes desktop wallpaper with GRE vocab every minute.

GitHub

Hexacopter Drone for Precision Agriculture

Sep-Dec 2016

Custom flight controller, finalist at international KrishakCopter drone competition.

YouTube

Awards

Research and Academic Awards

  • 2023 HCII 2023 Session Chair and Presenter - Copenhagen, Denmark
  • 2023 Dissertation Fellowship Award - UT Arlington Office of Graduate Studies
  • Apr 2022 John S. Schuchman Outstanding Doctoral Student Award - UT Arlington
  • 2022 Doctoral Consortium Winner - PETRA 2022, Corfu, Greece
  • 2021 Doctoral Consortium Winner - PETRA 2021, Greece
  • 2020 Graduate L3/Harris Award for Innovation - UT Arlington
  • 2018 AI Scholar - Fusemachines (Practical Hands-on AI and Deep Learning)
  • 2018 AI Fellowship - Fusemachines / Columbia Micromasters Program

Competitions and Certifications

  • 2021 Codepath Advanced Software Engineering Certification, Fall 2021
  • 2018 Winner - Datathon (Data Analysis Competition), Fusemachines Nepal
  • 2018 Best Engineering Award - IOE Robocon Nepal 2018
  • 2018 Certifications: Columbia Micromasters - AI (CSMM.101x), ML (CSMM.102x), Robotics (CSMM.103x)
  • 2018 Certification - Neural Networks and Deep Learning, deeplearning.ai (Coursera)
  • 2018 Tech Diversity Scholarship (Code for Nepal) - Web Development with Python
  • 2016 1st Runner-up - KrishakCopter International Drone Competition
  • 2015 1st Runner-up - Robodrift 3.0, Kathmandu Engineering College
  • 2014 Full Scholarship - B.E. Electronics and Communication Engineering