World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
9442
World Ranking
5642
National Ranking
2570

Overview

Milind R. Naphade is affiliated with Nvidia in the United States. Their research focuses primarily on computer science, with specific contributions in computer vision and pattern recognition, radiological and ultrasound technology, civil and structural engineering, safety, risk, reliability and quality, and artificial intelligence.

Their work covers a variety of topics within these fields, including:

  • Advanced Neural Network Applications
  • Human Pose and Action Recognition
  • Generative Adversarial Networks and Image Synthesis
  • Occupational Health and Safety Research
  • Infrastructure Maintenance and Monitoring
  • Traffic and Road Safety
  • Video Surveillance and Tracking Methods

Milind R. Naphade has published research in several venues. The most frequent publication outlets include:

  • arXiv (Cornell University)
  • Journal of Computing in Civil Engineering

Notable recent papers authored or co-authored by Milind R. Naphade include:

  • "Video-Based Motion Trajectory Forecasting Method for Proactive Construction Safety Monitoring Systems" (2020), Journal of Computing in Civil Engineering
  • "PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data" (2020), arXiv (Cornell University)
  • "LLM Surgery: Efficient Knowledge Unlearning and Editing in Large Language Models" (2024), arXiv (Cornell University)
  • "Training Dynamics Underlying Language Model Scaling Laws: Loss Deceleration and Zero-Sum Learning" (2025), arXiv (Cornell University)

The scientist has collaborated frequently with peers including Xiaodong Yang, Yue Yao, Liang Zheng, Tom Gedeon, and Shuai Tang, indicating ongoing engagement in collaborative research efforts.

Best Publications

  • Large-scale concept ontology for multimedia

    M. Naphade;J.R. Smith;J. Tesic;Shih-Fu Chang

  • Smarter Cities and Their Innovation Challenges

    M Naphade;G Banavar;C Harrison;J Paraszczak

  • CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification

    Zheng Tang;Milind Naphade;Ming-Yu Liu;Xiaodong Yang

  • A probabilistic framework for semantic video indexing, filtering, and retrieval

    H.R. Naphide;T.S. Huang

  • IBM Research TRECVID-2003 Video Retrieval System.

    Arnon Amir;Marco Berg;Shih-Fu Chang;Winston H. Hsu

  • IBM Research TRECVID-2005 Video Retrieval System

    Arnon Amir;Janne Argillander;Murray Campbell;Alexander Haubold

  • Probabilistic multimedia objects (multijects): a novel approach to video indexing and retrieval in multimedia systems

    M.R. Naphade;T. Kristjansson;B. Frey;T.S. Huang

  • Semantic Indexing of Multimedia Content Using Visual, Audio, and Text Cues

    W. H. Adams;Giridharan Iyengar;Ching-Yung Lin;Milind Ramesh Naphade

  • Multimedia semantic indexing using model vectors

    J.R. Smith;M. Naphade;A. Natsev

  • Factor graph framework for semantic video indexing

    M. Ramesh Naphade;I.V. Kozintsev;T.S. Huang

  • A high-performance shot boundary detection algorithm using multiple cues

    M.R. Naphade;R. Mehrotra;A.M. Ferman;J. Warnick

  • Novel scheme for fast and efficent video sequence matching using compact signatures

    Milind Ramesh Naphade;Minerva M. Yeung;Boon-Lock Yeo

  • On the detection of semantic concepts at TRECVID

    Milind R. Naphade;John R. Smith

  • PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data

    Zheng Tang;Milind Naphade;Stan Birchfield;Jonathan Tremblay

  • Extracting semantics from audio-visual content: the final frontier in multimedia retrieval

    M.R. Naphade;T.S. Huang

  • Learning the semantics of multimedia queries and concepts from a small number of examples

    Apostol (Paul) Natsev;Milind R. Naphade;Jelena TešiĆ

  • Simulating Content Consistent Vehicle Datasets with Attribute Descent.

    Yue Yao;Liang Zheng;Xiaodong Yang;Milind Naphade

  • IBM Research TRECVID-2006 Video Retrieval System

    Murray Campbell;Alexander Haubold;Shahram Ebadollahi;Dhiraj Joshi

  • Method and apparatus for active annotation of multimedia content

    Sankar Basu;Ching-Yung Lin;Milind Naphade;John Smith

  • Method for content-based temporal segmentation of video

    James Warnick;Ahmet M. Ferman;Bilge Gunsel;Milind R. Naphade

  • IBM Research TRECVID 2004 Video Retrieval System.

    Arnon Amir;Janne Argillander;Marco Berg;Shih-Fu Chang

Frequent Co-Authors

John R. Smith
John R. Smith IBM (United States)
Apostol Natsev
Apostol Natsev Google (United States)
Ching-Yung Lin
Ching-Yung Lin National Chi Nan University
Belle L. Tseng
Belle L. Tseng Apple (United States)
Thomas S. Huang
Thomas S. Huang University of Illinois at Urbana-Champaign
Sambit Sahu
Sambit Sahu IBM (United States)
Xiaodong Yang
Xiaodong Yang Nvidia (United Kingdom)
Arnon Amir
Arnon Amir IBM (United States)
Chung-Sheng Li
Chung-Sheng Li PricewaterhouseCoopers (United Kingdom)
Chalapathy Neti
Chalapathy Neti IBM (United States)

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