Kun

Kun Tu

contact

Email:
kuntu AT cs DOT umass DOT edu

Tel:
+1 (413) 545-1985

Address:
Rm CS326
Computer Science Buiding,
140 Governors Drive,
Univ. of Massachusetts,
Amherst, MA
01003-9264

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I am a Ph.D student in Biologically Inspired Neural and Dynamical Systems (Binds) Lab at University of massachesetts Amherst (UMass). My advisor is Professor Hava Siegelmann.

Current Project

I am now working with on an interesting project of cognictive system.

We are building a memory system which can reconsolidate info like human, after a memory recall or an input of repeated information. An adaptive inference engine is built so that our system can learn, remember knowledge of common sense and integrate the information to make reasonable conclusion accrodingly.

Additionally, natural language is used as input and output of our system so that it is more easy for our system to give feedback during a conversation with people.

Research Interests

My interest in computer science is mainly focuses on algorithms, machine learning, Inference Engine, Data Mining, Information Retrieval, bio-inspired computing system and bioinformatics

Previous work includes:

Academic Background

I pursued my undergraduate study in the Applied Mathematic Department in South China University of Technology and got my bachelor degree in 2003.

After that I continued my postgraduate study in the Computer Science Department at the same university.

Publications

K. Tu, M. Olsen, H. T. Siegelmann, CIM for Improved Language Understanding, The 10th International Symposium on Logical Formalization on Commonsense Reasoning, 2011 Poster

K. Tu, Hava Siegelmann, Memory Model for Text Reasoning, Northeast Student Conference on Artificial Intelligence, 2010

K. Tu, D. Cooper, H.T. Siegelmann , “Memory reconsolidation for natural language processing”, Cognitive Neurodynamics, 2009 365-372

Kun Tu, Zhifenghao and Chen Ming. PSO with improved strategy for Job-shop problem. Lecture Notes of Computer Science, Advances in Natural Computation. 4222/2006 :145-156

Zhifeng Hao, Han Huang, Xili Zhang and Kun Tu. A Time Complexity Analysis of ACO for Linear Functions, Lecture Notes in Computer Science, Simulated Evolution and Learning. 4247/2006:

Zhifeng hao, Kun Tu and Xiaowei Yang. Solving Multiple Sequence Alignment with position-based Genetic Algorithm. Dynamic of Continuous, Discrete and inpulsive System

Resume

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