Research Professor — Sejong University
Departments: Computer Science & Information Security; Convergence Engineering for Intelligent Drone. Based in Seoul, South Korea. Leading applied AI in security, sensor fusion, and real‑time systems.
Hi, I'm Dr. Palash Yuvraj Ingle
Research Professor at Sejong University, Seoul. I build AI & Robotics systems for safety‑critical environments: video surveillance, IoT, SLAM, and LiDAR–camera fusion for autonomous vehicles.
About
Dr. Palash Yuvraj Ingle is a Research Professor in the Department of Computer Science and Information Security and Convergence Engineering for Intelligent Drone at Sejong University, Seoul, South Korea.
Key research areas
- Artificial intelligence for security — video surveillance and the Internet of Things (IoT).
- LiDAR technology and sensory fusion for autonomous vehicles.
- Robotics — autonomous systems, SLAM, and early humanoid manipulation/tele‑operation research.
Career summary
- Research Professor, Sejong University, Seoul, South Korea — Departments: Computer Science & Information Security; Convergence Engineering for Intelligent Drone (current).
- Postdoctoral Researcher, Sejong University, Seoul, South Korea — completed postdoctoral appointment.
- Assistant Professor, K.J. Somaiya College of Science & Commerce, Mumbai — prior academic position in India.
Educational background
- Ph.D. (Dual Ph.d. Degree) in Computer & Information Security and Convergence Engineering for Intelligent Drone — Sejong University, Seoul,
- M.Tech in Computer Science & Engineering — J.C. Bose University of Science & Technology (formerly YMCA),
- M.Sc. in Information Technology — Mumbai University,
- NET Qualified — National Eligibility Test (NET)
Research activity
His scientific contributions appear on IEEE Xplore, ORCID, ACM and ResearchGate. He has co‑authored work on video synopsis, real‑time object detection for surveillance, and blockchain‑based security for vehicles.
Work
Postdoctoral Researcher — Sejong University
Completed postdoctoral research focusing on video surveillance, IoT security, and LiDAR‑driven sensor fusion.
Assistant Professor — K.J. Somaiya College of Science & Commerce, Mumbai
Taught computer science and conducted early research before transitioning to a research‑focused role in South Korea.
Projects
Collaborative Intelligence for Disaster SLAM (CID‑SLAM)
Unified R&D track for fire/disaster response that combines visual‑inertial SLAM, multi‑sensor fusion (RGB, LiDAR, thermal, gas/smoke/flame/IR/temperature), and LLM‑aided narration for situational awareness. Goal: localize ignition points, co‑build maps, and generate actionable summaries for first responders.
- SLAM‑based Fire Localization — Fuse fire/object detection with SLAM + GPS to geo‑pin ignition locations and track fire spread. Repo/Design
- FireVerse3D (UE5 Simulations) — Procedural UE5 fire scenes to synthesize training data with domain randomization and sensor models. Dataset
- VisionInferNet — Xception+SE model (focal loss) for robust fire image classification; supports CID‑SLAM perception stack. Repo
- FireFormer — Transformer‑based multi‑sensor fusion using DST to output calibrated fire/no‑fire confidence. GitHub/Paper
- FireSentryV3 — CNN backbone for rapid image‑level fire triage on edge devices. GitHub
- FireNarrator — LLM pipeline that converts sensor/vision streams into concise incident synopses for human teams. Project
LiDAR Mapping in Autonomous Vehicle
Real‑time LiDAR mapping with loop‑closure and pose‑graph optimization. Produces occupancy/TSDF maps and drivable area layers for downstream planning.
Abnormal Video Synopsis
Detect anomalies in long surveillance streams and compose a brief synopsis ranked by anomaly score for rapid review.
Drone Video Synopsis
Compressed mission summaries from UAV footage via trajectory‑tube clustering fused with flight telemetry; outputs geo‑tagged highlight reels.
NeuroLink Drive (Autonomous Vehicle)
Learning module that links perception to low‑latency driving intent and path updates; explores sensor fusion and neural controllers in simulation.
Humanoid Robot
Research on locomotion control, perception, and tele‑operation; early work on whole‑body control and manipulation under uncertainty.
Publications
Journal Articles
- Real‑time abnormal object detection for video surveillance in smart cities — P.Y. Ingle, Y.G. Kim. Sensors 22(10):3862, 2022.
- DVS: A drone video synopsis towards storing and analyzing drone surveillance data in smart cities — P.Y. Ingle, Y.K. Kim, Y.G. Kim. Systems 10(5):170, 2022.
- Multiview abnormal video synopsis in real‑time — P.Y. Ingle, Y.G. Kim. Engineering Applications of Artificial Intelligence 123:106406, 2023.
- Video synopsis algorithms and framework: A survey and comparative evaluation — P.Y. Ingle, Y.G. Kim. Systems 11(2):108, 2023.
- Image enhancement and exposure correction using convolutional neural network — M. Parab, A. Bhanushali, P. Ingle, B.N. Pavan Kumar. SN Computer Science 4(2):204, 2023.
- Panoramic Video Synopsis on Constrained Devices for Security Surveillance — P.Y. Ingle, Y.G. Kim. Systems 13:110, 2025.
- Privacy‑Preserving Spatial Crowdsourcing Drone Services for Post‑Disaster Infrastructure Monitoring: A Conditional Federated Learning Approach — J. Akram, A. Akram, P. Ingle, R.H. Jhaveri, A. Anaissi, A. Akhundzada. IEEE JSTARS, 2025.
- Transparent and Trustworthy Blockchain‑Based Scheme for the Protection of Vehicular Soft Integrity in Shared Mobility — U. Ghani, M. Aslam, S. Ullah, T. Ahmad, A. Buriro, P. Ingle, R.H. Jhaveri. IEEE Transactions on Intelligent Transportation Systems, 2025.
- Multi‑Sensor Data Fusion Across Dimensions: A Novel Approach to Synopsis Generation Using Sensory Data — P.Y. Ingle, Y.G. Kim. Journal of Industrial Information Integration 100876, 2025.
- BreastCancerNet: Flask‑Enabled Attention‑Driven Hybrid Dual DNN Framework for Real‑Time Breast Cancer Prediction — A.J. Prakash, K.K. Patro, P. Ingle, J.J. Pujari, S. Routray, R.H. Jhaveri. Journal article, 2025.
Conference Papers
- A Comprehensive Study on LLM Agent Challenges — P. Ingle, M. Parab, P. Lendave, A. Bhanushali, P.K. BN. AAAI Spring Symposium Series, 2024.
- Innovative method for camouflaged wildlife segmentation in agricultural practices — M. Parab, P. Ingle. ICACC 2024, 2024.
- Integrated Interoperability Based Panoramic Video Synopsis Framework — P. Ingle, Y.G. Kim. ACM SAC, pp. 584–591, 2024.
- Adversarial Attack on 3D Fused Sensory Data in Drone Surveillance — A. Bhanushali, M. Parab, B.N.P. Kumar, P. Ingle. ICACC 2024, 2024.
- A Role‑based Access Control Framework for Video Synopsis in Airport Environment — P.Y. Ingle, G. Kang, J. Park, Y.G. Kim. KICS Conference Proceedings, 2023.
- Enhancing Cybersecurity in Internet of Vehicles: A Machine Learning Approach with Explainable AI for Real‑Time Threat Detection — T. Patel, R. Jhaveri, D. Thakker, S. Verma, P. Ingle. ACM SAC, pp. 2024–2031, 2025.
- Abnormal Object Detection‑based Video Synopsis Framework in Multiview Video — P.Y. Ingle, J.Y. Pyo, Y.G. Kim. Annual Conference of KIPS, pp. 213–216, 2022.
Preprints & Others
- MT3DNet: Multi‑Task learning Network for 3D Surgical Scene Reconstruction — M. Parab, P. Lendave, J. Kim, T.Q.D. Nguyen, P. Ingle. arXiv:2412.03928, 2024.
- Capability‑Based Multi‑Tenant Access Management in Crowdsourced Drone Services — J. Akram, A. Anaissi, A. Akram, Y. Djenouri, P. Ingle, R.H. Jhaveri. arXiv:2505.01048, 2025.
Awards & Honors
- Outstanding Research Award — Sejong University.
- Bronze Best Paper Award — IEEE Seoul Section.
- Paper Idea Award — Korea Information Processing Society (KIPS).