{"id":1329,"date":"2026-09-17T12:28:38","date_gmt":"2026-09-17T12:28:38","guid":{"rendered":"https:\/\/ivory-network.eu\/?page_id=1329"},"modified":"2026-09-17T12:32:37","modified_gmt":"2026-09-17T12:32:37","slug":"dc12-research-journal","status":"publish","type":"page","link":"https:\/\/ivory-network.eu\/index.php\/dc12-research-journal\/","title":{"rendered":"DC12 Research Journal"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.23.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221; theme_builder_area=&#8221;post_content&#8221;][et_pb_row _builder_version=&#8221;4.23.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221; theme_builder_area=&#8221;post_content&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.23.1&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221; theme_builder_area=&#8221;post_content&#8221;][et_pb_code 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-->.ip-partner{display:flex;align-items:center;justify-content:flex-start;gap:8px;min-height:32px}.ip-partner span{line-height:24px;white-space:nowrap}.ip-partner img{width:54px;height:26px;object-fit:contain;display:block;flex:0 0 54px}.ip-affiliations{gap:16px;flex-wrap:wrap}.ip-affiliations>div{padding-right:16px}<!-- [et_pb_line_break_holder] -->.ivory-profile .ip-hero h1{text-align:justify;text-align-last:left}<!-- [et_pb_line_break_holder] --><\/style>\n<p><!-- [et_pb_line_break_holder] --><\/p>\n<div class=\"ivory-profile\">\n<div class=\"ip-crumb\">Home \u203a Our People \u203a Doctoral Candidates \u203a DC12 \u2013 Muhammad Shahid<\/div>\n<div class=\"ip-grid\">\n<aside class=\"ip-sidebar\"><img decoding=\"async\" class=\"ip-photo\" src=\"https:\/\/ivory-network.eu\/wp-content\/uploads\/2024\/09\/DC12-Muhammad-Shahid-logo.png\" alt=\"Muhammad Shahid\"><\/p>\n<div class=\"ip-panel\">\n<h3><img decoding=\"async\" class=\"ip-icon-img\" src=\"https:\/\/ivory-network.eu\/wp-content\/uploads\/2026\/09\/education-icon.png\" alt=\"\">Education<\/h3>\n<pee>M.Eng in Computer Science and Technology<!\u2013- [et_pb_br_holder] -\u2013>Hefei University of Technology<!\u2013- [et_pb_br_holder] -\u2013>Focus: Machine Learning and Computer Vision<\/pee>\n<hr>\n<h3><img decoding=\"async\" class=\"ip-icon-img\" src=\"https:\/\/ivory-network.eu\/wp-content\/uploads\/2026\/09\/links-icon.png\" alt=\"\">Links<\/h3>\n<p><a class=\"ip-link\" href=\"https:\/\/scholar.google.com\/citations?user=odhTVC4AAAAJ&#038;hl=en\" target=\"_blank\" rel=\"noopener noreferrer\">Google Scholar <span aria-hidden=\"true\">\u2197<\/span><\/a><a class=\"ip-link\" href=\"https:\/\/orcid.org\/0009-0002-0442-3556\" target=\"_blank\" rel=\"noopener noreferrer\">ORCID <span aria-hidden=\"true\">\u2197<\/span><\/a><a class=\"ip-link\" href=\"https:\/\/www.linkedin.com\/in\/mohammad-shahid-781a8a16a\/\" target=\"_blank\" rel=\"noopener noreferrer\">LinkedIn <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div>\n<\/aside>\n<p><main><\/p>\n<div class=\"ip-hero\"><span class=\"ip-tag\">DC12<\/span><\/p>\n<h1>Multi-Modal Fusion for Road Infrastructure Analysis: An AI-Driven Framework for Heterogeneous Data<\/h1>\n<div class=\"ip-name\">Muhammad Shahid<\/div>\n<div class=\"ip-slogan\">Safer mobility<!\u2013- [et_pb_br_holder] -\u2013>for a brighter<!\u2013- [et_pb_br_holder] -\u2013>tomorrow<\/div>\n<\/div>\n<div class=\"ip-affiliations\">\n<div class=\"ip-partner\"><img decoding=\"async\" src=\"https:\/\/ivory-network.eu\/wp-content\/uploads\/2023\/11\/LOGO-FPZ_final.png\" alt=\"Faculty of Transport and Traffic Science (FPZ) logo\"><\/div>\n<div class=\"ip-partner\"><img decoding=\"async\" src=\"https:\/\/ivory-network.eu\/wp-content\/uploads\/2023\/11\/iRAP-logo-TRAN.png\" alt=\"iRAP logo\"><\/div>\n<div>\u2667 \u00a0 Work Package 6<!\u2013- [et_pb_br_holder] -\u2013><span class=\"ip-muted\">AI for Proactive Infrastructure Safety Management<\/span><\/div>\n<\/div>\n<section class=\"ip-panel ip-glance\">\n<h2><span class=\"ip-icon ip-teal\">\u25ce<\/span>Research at a glance<\/h2>\n<pee>My research focuses on automated road safety assessment and infrastructure analysis utilizing heterogeneous road datasets, situated at the intersection of deep multimodal learning, video understanding, and trustworthy artificial intelligence. Recently, my work has advanced from standard visual classifiers toward multimodal Vision-Language Models (VLMs), teaching these systems to visually interpret road environments and generate structured safety records for a more flexible and holistic understanding of complex scenes. A core priority of my methodology is ensuring these models are dependable for real-world deployment; to achieve this, I design solutions that prevent invalid predictions, provide reliable confidence scores, and enable seamless human-in-the-loop workflows where ambiguous scenes are automatically flagged for expert review. Furthermore, my research tackles the inherent noise of real-world infrastructure data by adaptively prioritizing rare, high-risk safety hazards while intelligently filtering out human labelling inconsistencies without discarding valuable visual evidence.<\/pee><\/section>\n<section class=\"ip-panel ip-objectives\">\n<h2><svg class=\"ip-target-icon\" viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" aria-hidden=\"true\"><circle cx=\"12\" cy=\"12\" r=\"9\"\/><circle cx=\"12\" cy=\"12\" r=\"5.5\"\/><circle cx=\"12\" cy=\"12\" r=\"2\"\/><\/svg>Research objectives<\/h2>\n<ul>\n<li><strong>Advance Automated Road Safety Auditing through Vision-Language Models:<\/strong> Transition road infrastructure assessment from rigid, closed-set classifiers to multimodal Vision-Language Models (VLMs), enabling the automated generation of comprehensive and structured records directly from road survey imagery.<\/li>\n<li><strong>Develop Robust Spatio-Temporal Video Modeling Frameworks:<\/strong> Design deep learning architectures that effectively capture both persistent infrastructure characteristics (e.g., lane configurations and medians) and transient, localized features (e.g., roadside hazards).<\/li>\n<li><strong>Tackle Extreme Data Imbalance and Imperfect Real-World Annotations:<\/strong> Formulate adaptive optimization strategies and field-level noise-filtering techniques that prioritize rare, safety-critical hazards over common classes while systematically mitigating human labeling inconsistencies without sacrificing usable visual data.<\/li>\n<li><strong>Integrate Heterogeneous Geospatial Data for Cross-Regional Generalizability:<\/strong> Combine complementary data sources, such as street-level RGB video, 3D LiDAR point clouds, and GIS mapping data, to resolve visual and depth ambiguities, ensuring the developed models generalize reliably across diverse, international road networks.<\/li>\n<li><strong>Establish Trustworthy AI Systems:<\/strong> Incorporate reliable confidence estimation into multimodal models to enable practical \u201chuman-in-the-loop\u201d deployments, allowing the AI to autonomously process high-confidence road segments while systematically escalating ambiguous, high-risk cases for expert human review.<\/li>\n<\/ul>\n<\/section>\n<section class=\"ip-section\">\n<div class=\"ip-section-title\">\n<h2><svg class=\"ip-heading-icon\" aria-hidden=\"true\" viewBox=\"0 0 32 32\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\"><path d=\"M5 8H2v22h22v-3M9 2h15l6 6v18H9zM23 2v7h7M13 13h13M13 18h13M13 22h8\"\/><\/svg>Publications<\/h2>\n<\/div>\n<div class=\"ip-table-wrap\">\n<table>\n<thead>\n<tr>\n<th>Title<\/th>\n<th>Authors<\/th>\n<th>Venue<\/th>\n<th>Year<\/th>\n<th>Link<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Multi-scale spatio-temporal feature aggregation for road safety attributes classification from videos<\/td>\n<td>Shahid, M., \u0160evrovi\u0107, M., Hassani, A., Olyslagers, M.<\/td>\n<td>IEEE Access<\/td>\n<td>2026<\/td>\n<td class=\"ip-muted\">\u2013<\/td>\n<\/tr>\n<tr>\n<td>A Spatio-Temporal Multi-Task Framework for iRAP Road Attribute Classification from Street-Level Videos<\/td>\n<td>Shahid, M., \u0160evrovi\u0107, M., Olyslagers, M., Hassani, A.<\/td>\n<td>ACAI 2025 (IEEE)<!\u2013- [et_pb_br_holder] -\u2013><span class=\"ip-muted\">pp. 1\u20136<\/span><\/td>\n<td>2025<\/td>\n<td class=\"ip-muted\">\u2013<\/td>\n<\/tr>\n<tr>\n<td>Optimizing Car Collision Detection Using Large Dashcam-Based Datasets: A Comparative Study of Pre-Trained Models and Hyperparameter Configurations<\/td>\n<td>Shahid, M., Greguri\u0107, M., Hassani, A., \u0160evrovi\u0107, M.<\/td>\n<td>Applied Sciences<!\u2013- [et_pb_br_holder] -\u2013><span class=\"ip-muted\">15(13), 7001<\/span><\/td>\n<td>2025<\/td>\n<td class=\"ip-see\"><a href=\"https:\/\/doi.org\/10.3390\/app15137001\" target=\"_blank\" rel=\"noopener noreferrer\" aria-label=\"Publication link\">\u2197<\/a><\/td>\n<\/tr>\n<tr>\n<td>Auditing iRAP\u2019s ViDA Risk Engine: A Two-Stage Surrogate Learning and Orthogonalized Heterogeneity Framework for Modelled Road Safety<\/td>\n<td>Shahid, M.<!\u2013- [et_pb_br_holder] -\u2013><span class=\"ip-muted\">Co-author, with Hassani, A., Abramovi\u0107, B., \u0160evrovi\u0107, M.<\/span><\/td>\n<td>Infrastructures<!\u2013- [et_pb_br_holder] -\u2013><span class=\"ip-muted\">Vol. 11, No. 129<\/span><\/td>\n<td>2026<\/td>\n<td class=\"ip-see\"><a href=\"https:\/\/doi.org\/10.3390\/infrastructures11040129\" target=\"_blank\" rel=\"noopener noreferrer\" aria-label=\"Publication link\">\u2197<\/a><\/td>\n<\/tr>\n<tr>\n<td>EfficientNet-Swin Transformer for Automated iRAP Road Safety Attribute Extraction in Low- and Middle-Income Countries<\/td>\n<td>Shahid, M.<!\u2013- [et_pb_br_holder] -\u2013><span class=\"ip-muted\">Co-author, with Hassani, A., Rozi, O., \u0160evrovi\u0107, M.<\/span><\/td>\n<td>ICTR 2025<\/td>\n<td>2025<\/td>\n<td class=\"ip-muted\">\u2013<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/section>\n<section class=\"ip-section\">\n<div class=\"ip-section-title\">\n<h2><svg class=\"ip-heading-icon\" aria-hidden=\"true\" viewBox=\"0 0 32 32\" fill=\"currentColor\"><circle cx=\"18\" cy=\"6\" r=\"5\"\/><path d=\"M9 17v-2c0-5 18-5 18 0v2zM3 19h28v4H3zM10 24h15l-2 8H12z\"\/><path d=\"M5 19v-6l3-4\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\"\/><circle cx=\"8\" cy=\"9\" r=\"2.5\"\/><\/svg>Conference contributions<\/h2>\n<\/div>\n<div class=\"ip-table-wrap\">\n<table>\n<thead>\n<tr>\n<th>Title<\/th>\n<th>Conference<\/th>\n<th>Date<\/th>\n<th>Link<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Ensemble Learning for Multi-Task Road Safety Attributes Classification<\/td>\n<td>hEART Conference (14th Symposium of the European Association for Research in Transportation)<!\u2013- [et_pb_br_holder] -\u2013><span class=\"ip-muted\">Paris, France<\/span><\/td>\n<td>Sep\u2013Oct 2026<\/td>\n<td class=\"ip-muted\">\u2013<\/td>\n<\/tr>\n<tr>\n<td>Impact of Camera\u2013LiDAR Data Fusion on Road Attribute Identification Using Deep Learning: An Empirical Investigation<\/td>\n<td>8th IRTAD International Conference<!\u2013- [et_pb_br_holder] -\u2013><span class=\"ip-muted\">Athens, Greece<\/span><\/td>\n<td>Apr 2026<\/td>\n<td class=\"ip-muted\">\u2013<\/td>\n<\/tr>\n<tr>\n<td>A Spatio-Temporal Multi-Task Framework for iRAP Road Attribute Classification from Street-Level Videos<\/td>\n<td>8th International Conference on Algorithms, Computing and Artificial Intelligence (ACAI)<!\u2013- [et_pb_br_holder] -\u2013><span class=\"ip-muted\">Nanjing, China<\/span><\/td>\n<td>Dec 2025<\/td>\n<td class=\"ip-muted\">\u2013<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/section>\n<section class=\"ip-section\">\n<div class=\"ip-section-title\">\n<h2><span class=\"ip-icon\">\u2708<\/span>Secondments &amp; collaborations<\/h2>\n<\/div>\n<div class=\"ip-table-wrap\">\n<table>\n<thead>\n<tr>\n<th>Host organisation<\/th>\n<th>Period<\/th>\n<th>Purpose<\/th>\n<th>Status<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Verne (P3M)<\/td>\n<td class=\"ip-muted\">\u2013<\/td>\n<td class=\"ip-muted\">\u2013<\/td>\n<td class=\"ip-muted\">\u2013<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/section>\n<p><\/main><\/div>\n<\/div>\n<p>[\/et_pb_code][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":8,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"footnotes":""},"class_list":["post-1329","page","type-page","status-publish","hentry"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.0.1 - aioseo.com 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