Yinan Yu
My research focused on advancing personalized AI systems. Personalization involves adapting AI to the unique needs and contexts of individual users or entities, ensuring greater relevance and usability. This involves addressing several key challenges, including reducing data requirements to handle distribution shifts, minimizing model size for efficiency, developing specialized representation learning techniques to extract meaningful insights from highly personalized data, decentralizing and streamlining training processes, and establishing robust, scalable frameworks for data governance. My goal is to improve the usability of AI in real-world applications by developing systems that are efficient, adaptable, and scalable to meet diverse user needs and contexts.
Visar 45 publikationer
LLMs Can Check Their Own Results to Mitigate Hallucinations in Traffic Understanding Tasks
Sentiment and semantic analysis: Urban quality inference using machine learning algorithms
Semantic-Aware Representation of Multi-Modal Data for Data Ingress: A Literature Review
climateBUG: A data-driven framework for analyzing bank reporting through a climate lens
Domain generalization through meta-learning: a survey
Building efficient CNNs using Depthwise Convolutional Eigen-Filters (DeCEF)
Evaluating and Enhancing Trustworthiness of LLMs in Perception Tasks
BAUFER: A Baseline-Enabled Facial Expression Recognition Pipeline Trained With Limited Annotations
AirDnD-Asynchronous In-Range Dynamic and Distributed Network Orchestration Framework
Qually: A Quality Validation Toolbox for Automotive Perception Data Towards Trustworthy AI
Safety-driven data labelling platform to enable safe and responsible AI
AI-baserad segementering av fasader för att optimera renovering i en större skala
Kernel Subspace Learning for Pattern Classification
Adaptive margin slack minimization in RKHS for classification
Microwave technology in medical diagnostics and treatment
Detection of wood decay by microwaves
Pre-hospital care for stroke and trauma
Multiclass Ridge-adjusted Slack Variable Optimization Using Selected Basis for Fast Classification
Detection of Breathing and Heartbeat by Using a Simple UWB Radar System
Feature Reduction Based on Sum-of-SNR (SOSNR) Optimization
Microwave-Based Stroke Diagnosis Making Global Prehospital Thrombolytic Treatment Possible
A Unified Subspace Classification Framework Developed for Diagnostic System Using Microwave Signal
Microwave technology shows potential for detecting traumatic intracranial bleedings
Ridge-Adjusted Slack Variable Optimization for Supervised Classification
Stroke diagnostics with a microwave helmet
Parameter Design Tradeoff Between Prediction Performance and Training Time for Ridge-Svm
Microwave based diagnostics and treatment in practice
Kernel SODA: A Feature Reduction Technique Using Kernel Based Analysis
Several new ultra-wideband antenna systems for radio telescopes and industry sensor imaging process
The new UWB self-grounded Bow-Tie antennas and the applications in Different Systems
Compact UWB Indoor and Through-Wall Radar with Precise Ranging and Tracking
Using microwave technology for detecting traumatic intracranial bleedings – tests on a brain phantom
Development of a Compact UWB Radar System for Indoor Ranging and Tracking
Model reduction for inverse scattering problems
A new UWB radar system using UWB CMOS chip
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Visar 8 forskningsprojekt
AI-baserad telemonitorering och specialiserad hemsjukvård för hjärtsviktspatienter
AutoLang: Anpassning av LLM för programvaruutveckling inom fordonsindustrin
Förbättrad Säkerhet för Vulnerable Road Users (VRU:s) med Nedsatt Rörlighet
Digitala materialinventeringar för hållbar urban mining
Verification of Machine Learning Algorithms (Vermillion)