Research Professor · Sejong University
I build AI and robotics systems for safety-critical environments: video surveillance, IoT, SLAM, and LiDAR–camera fusion for autonomous vehicles.
Profile
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.
Artificial intelligence for security
Video surveillance and the Internet of Things (IoT).
LiDAR and sensory fusion
Sensor fusion methods for autonomous vehicles and field robots.
Robotics
Autonomous systems, SLAM, and early humanoid manipulation and tele-operation research.
Ph.D. (Dual Degree) · Computer & Information Security and Convergence Engineering for Intelligent Drone
2023Sejong University, Seoul
M.Tech · Computer Science & Engineering
2019J.C. Bose University of Science & Technology (formerly YMCA)
M.Sc. · Information Technology
2016Mumbai University
NET Qualified · National Eligibility Test (NET)
India
Hardware
From an early unmanned ground vehicle to a gesture-controlled 3D-printed prosthetic hand and a disaster-response SLAM rover, these platforms mark a long-term hands-on path in robotics, assistive hardware, and field autonomy.
2016 · M.Sc. in Information Technology · Mumbai University
An early unmanned ground vehicle prototype developed for hazardous-object handling and remote operation. This project marked the beginning of my practical work in mobile robotics and robotic manipulation.
UGCV — Unmanned Ground Counter-IED Vehicle prototype developed during my M.Sc. research.
2019 · M.Tech. in Computer Science & Engineering · YMCA University
M.Tech project on an IoT-connected, 3D-printed prosthetic hand. Hand-gesture sensing was used both to support communication for mute and deaf users and to command finger motion on the prosthetic model.
Graduate hardware project: gesture recognition, IoT control, and a 3D-printed prosthetic hand prototype.
2026 · Research Professor · Sejong University
My latest rover platform for disaster-response research, designed around SLAM, field mobility, perception, and multi-sensor intelligence for real-world hazardous environments.
DisasterSLAM Rover — a modern disaster-response rover platform for SLAM, navigation, and intelligent environmental perception.
Appointments
Shipped
Two free web products — a cozy AI study companion and an in-browser video editor — available to use online without a purchase.
Your cozy AI study companion
A free study companion for tracking habits, running focus sessions, and planning coursework — with Nooki as an AI partner for staying consistent.
Free online video editor, AI tools & game studio
Browser-first video editing with trim, captions, silence removal, and local export. Free tools run on your device — no credit card — plus optional AI, a game studio, and a design studio.
Research
Current work spans disaster-response SLAM, LiDAR mapping, video synopsis, and environment-centric robot safety.
Unified R&D track for fire and 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.
RepoFireVerse3D (UE5 Simulations)
Procedural UE5 fire scenes to synthesize training data with domain randomization and sensor models.
VisionInferNet
Xception+SE model (focal loss) for robust fire image classification; supports the CID-SLAM perception stack.
FireFormer
Transformer-based multi-sensor fusion using DST to output calibrated fire/no-fire confidence.
DatasetFireSentryV3
CNN backbone for rapid image-level fire triage on edge devices.
FireNarrator
LLM pipeline that converts sensor and vision streams into concise incident synopses for human teams.
ProjectIntellectual property
Official Korean certificates of patent, software copyright, and NIPA Software Asset Bank registration, held by the Industry–Academy Cooperation Foundation of Sejong University. Open a certificate to view it, or download the signed PDF.
Certificate of Patent
Korean patent
Registered Korean patent on generating a three-dimensional video synopsis of abnormal objects in surveillance footage.
Certificate of Patent
Korean patent
Registered Korean patent on detecting abnormal objects and composing a compact video synopsis.
Code
Public research code and datasets spanning disaster robotics, fire perception, avatar generation, and sensor fusion.
Account: github.com/palashngl
Writing
22 selected papers across journals, conferences, and preprints. Search by title, author, or venue.
1.
Real-time abnormal object detection for video surveillance in smart citiesP.Y. Ingle, Y.G. Kim
Sensors 22(10):3862, 2022
2.
DVS: A drone video synopsis towards storing and analyzing drone surveillance data in smart citiesP.Y. Ingle, Y.K. Kim, Y.G. Kim
Systems 10(5):170, 2022
3.
Multiview abnormal video synopsis in real-timeP.Y. Ingle, Y.G. Kim
Engineering Applications of Artificial Intelligence 123:106406, 2023
4.
Video synopsis algorithms and framework: A survey and comparative evaluationP.Y. Ingle, Y.G. Kim
Systems 11(2):108, 2023
5.
Image enhancement and exposure correction using convolutional neural networkM. Parab, A. Bhanushali, P. Ingle, B.N. Pavan Kumar
SN Computer Science 4(2):204, 2023
6.
Panoramic Video Synopsis on Constrained Devices for Security SurveillanceP.Y. Ingle, Y.G. Kim
Systems 13(2):110, 2025
7.
Privacy-Preserving Spatial Crowdsourcing Drone Services for Post-Disaster Infrastructure Monitoring: A Conditional Federated Learning ApproachJ. Akram, A. Akram, P. Ingle, R.H. Jhaveri, A. Anaissi, A. Akhundzada
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025
8.
Transparent and Trustworthy Blockchain-Based Scheme for the Protection of Vehicular Soft Integrity in Shared MobilityU. Ghani, M. Aslam, S. Ullah, T. Ahmad, A. Buriro, P. Ingle, R.H. Jhaveri
IEEE Transactions on Intelligent Transportation Systems, 2025
9.
Multi-Sensor Data Fusion Across Dimensions: A Novel Approach to Synopsis Generation Using Sensory DataP.Y. Ingle, Y.G. Kim
Journal of Industrial Information Integration 46:100876, 2025
10.
BreastCancerNet: Flask-Enabled Attention-Driven Hybrid Dual DNN Framework for Real-Time Breast Cancer PredictionA.J. Prakash, K.K. Patro, P. Ingle, J.J. Pujari, S. Routray, R.H. Jhaveri
IEEE Journal of Biomedical and Health Informatics, 2025
Recognition
Outstanding Paper Award
The 23rd IEEE International Conference on Dependable, Autonomic and Secure Computing
Outstanding Paper Award
Korean Society of Information Technology (KIIT)
Outstanding Research Award
Sejong University
Bronze Best Paper Award
IEEE Seoul Section
Paper Idea Award
Korea Information Processing Society (KIPS)
Outreach
Get in touch
For research collaboration, talks, or student inquiries, the fastest route is email.
