HopeLoom AI Interview
An open-source AI interview simulation platform with real-time AI interviewers, multi-LLM support, WebSocket communication, and separate modes for candidate practice, company screening, and invited candidate interviews.
A curated view of public projects, selected private case studies, collaboration work, publications, and patent-backed applied systems.
AI systems spanning real-time interaction, agent orchestration, multimodal understanding, and practical user workflows.
An open-source AI interview simulation platform with real-time AI interviewers, multi-LLM support, WebSocket communication, and separate modes for candidate practice, company screening, and invited candidate interviews.
An AI education platform focused on personalized technical learning support, structured practice, and mentor-style guidance for programming concepts.
At Kyoso, developing an AI agent platform for designers and creators that combines brand context, market research, OCR, multimodal LLMs, Graph RAG, tool use, memory, and deep-research workflows to support creative ideation and on-brand visual concepting.
A collaborative AI presentation-generation project that turns documents into slide decks with document parsing, AI content planning, real-time collaboration, and PowerPoint export workflows.
Selected proprietary work is presented as case studies, with technical scope described at a public-safe level.
Led LLM agent development for system applications such as intelligent image editing and color recommendation tools, combining open models, tool use, and user-context understanding.
Designed a RAG-based research agent for report creation with smart editing, multi-source merging, automated visualization, and model routing across reasoning and generation models.
Built an LLM-based browser automation agent that interprets recorded workflows, reasons over HTML, identifies target elements, and executes actions across websites.
Integrated gesture recognition models with LLM function calling to interpret stylus gestures and map them to application actions in creative tablet workflows.
Healthcare work includes wearable biomarker modeling, medical imaging, firmware-adjacent systems, and patent-backed device pipelines.
Machine learning work for heart-risk and renal-risk monitoring using smartwatch biomarker data at General Prognostics.
Algorithm work for efficient sampling strategies in medical and wearable data pipelines.
Firmware-adjacent work supporting smartwatch-based sensing and health-data collection workflows.
CNN-based binary classification using RGB and near-infrared image inputs, with YACS configuration, TensorBoard logging, and evaluation artifacts.
Robotic and IoT-enabled medical device work for remote HbA1c testing from finger-prick blood samples, including embedded and mobile integration.
Code related to exudate segmentation in retinal fundus images for diabetic retinopathy detection.
Computer vision work spanning VR eye tracking, pupil estimation, retinal imaging, scene perception, and human-computer interaction.
Research and deployment of gaze tracking methods for VR, desktop, and mobile settings, including RGB/IR camera pipelines and accuracy improvements.
CNN architecture for estimating pupil centers from infrared smartphone eye images, including image enhancement experiments and mean pixel error analysis.
Semantic-segmentation approach to lane detection using BDD100K images, generated labels, model outputs, and feature-map visualizations.
Computer-vision project for emotion classification experiments and model evaluation.
Selected publications and patent-backed systems connected to the project areas above.