Research Assistant @ The National Laboratory of Pattern Recognition, Institute of Automation,Chinese Academy of Sciences
Bachelor’s Degree, Computer Science @
Beijing University of Technology
Accomplished, results-oriented professional experienced in the execution of in-depth research projects to initiate the design, programming, and implementation of complex artificial intelligence systems. Strong skills in modeling and developing frameworks, including machine learning, computer vision, pattern recognition, and multimedia. Proven ability to lead projects from initial concept through completion. Extensive experience worked in top academic institutes and
Accomplished, results-oriented professional experienced in the execution of in-depth research projects to initiate the design, programming, and implementation of complex artificial intelligence systems. Strong skills in modeling and developing frameworks, including machine learning, computer vision, pattern recognition, and multimedia. Proven ability to lead projects from initial concept through completion. Extensive experience worked in top academic institutes and top industrial research institute.
Research Assistant @ Understanding human action from videos with middle level features casting into implemented systematic framework for action recognition. From September 2015 to Present (2 months) Research Assistant @ Institute of Deep Learning (IDL), Baidu From April 2015 to July 2015 (4 months) Beijing City, ChinaResearch Assistant @ Spearheaded the design of a multi-modal model capable of mining multimedia data entities from the internet, utilizing results to create a knowledge graph comprised of entity nodes and relations.
Developed a Convolutional Neural Network and initiated network training using the info from knowledge graph.
Enabled semantic search capabilities of graph to retrieve nodes and multi-modal information related to images, Natural Language Processed text, and Point of Interest.
Integrated an image retrieval system through the use of Locality-Sensitive Hashing (LSH) across multiple levels features. From October 2013 to March 2015 (1 year 6 months) Research Assistant @ I mainly focused on Image Segmentation and Scene Understanding problems for nearly 3 years.
Conceptualized and developed a machine learning framework to combine top-down and bottom-up segment approaches.
Labeled indoor scenes on the Cornell RGB-D indoor scene dataset semantically by casting the Conditional Random Field Model into the Discriminative Model; implemented training of the model using latent structural SVM learning framework, Cutting-Plane Training with Concave-Convex Procedure (CCCP).
Created a generalized Segment-Forest Model (SFM) with the ability to simultaneously segment and label all semantic parts of an object.
Gained recognition of research initiatives through published international conference papers related to RGB-D scene understanding, image segmentation, and interactive segmentation. From 2011 to 2013 (2 years) Beijing City, ChinaResearch Assistant @ I joined AI & Robots Laboratory and participated for several national top AI championships.
Secured 3rd place in RoboCup Competition for the design of a real-time Intelligent Robot Control System with a visional system enabling the detection and position tracking of robots and balls; developed expert system and statistical approaches for framework integration.
Earned 2nd place in the National Machine Game Championship by constructing a complete database comprised of all chessboard possibilities using statistical framework, parallelism, and Genetic Algorithm while maximizing speed of game tree and optimizing scoring within search algorithms.
Designed and built an Autonomous Control Robot containing an RGB-D visional system, electronic controls, robotic skeleton, and real-time operating system to win 1st place in the Imagine Cup competition. From 2010 to 2011 (1 year) Beijing City, China
Master's Degree, Computer Science @ Carnegie Mellon University From 2015 to 2016 Bachelor’s Degree, Computer Science @ Beijing University of Technology From 2009 to 2013 Haoqi Fan is skilled in: Computer Vision, Pattern Recognition, Multimedia, Machine Learning, C, Matlab, Python, C++, Linux, Java, Programming, Computer Science, Algorithms, Artificial Intelligence, LaTeX, Image Processing
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