Research in SNU Biointelligence Lab

Our research focuses on brain-inspired computational intelligence technologies, i.e. biointelligence. We use mathematical modeling, computer simulations, and cognitive experiments to build models of cognitive information processing at the molecular, neural, and whole-brain scales. These evolutionary computational models are then used to develop human-competitive learning and inference machines for solving real-world problems in artificial intelligence and cognitive brain science.

Cognitive Computation Language-Vision Translation Cognitive Memory Games Learning to Talk
Learning and Evolution Hypernetworks for Learning and Memory Probabilistic Graphical Models Bayesian Evolutionary Computation
Molecular Inference Molecular Machine Learning In Vitro Molecular Theorem Proving Molecular Evolutionary Computing

Current Projects

	BabyMind Project Infant-Mimic Neurocognitive Developmental Machine Learning from Interaction Experience with Real World
	StarLab Project Cognitive Agents That Learn Everyday Life
	DeepAction Deep Learning of TV Viewer Activities
	DeepClone Cloning Humans for Scheduling Personal Service Robots
	CogHRI Cognitive Communication as Moving Target Tracking
	Molecular AI Intelligent Nanobio Agents That Learn

Completed Projects

• Molecular ML: Bio-Inspired Human-Level Machine Learning (2012~2015)
• Videome: Cognitive Machine Learning from Digital Videos (2011~2015)
• mLife: Identifying Human Mobile Behaviors in Context (2010~2015)
• RoboMotion: Learning to Generate Robot Motions from Human Activity Sequences (2011~2013)
• BrainNet: Uncovering the Hyperedges of Cortical Brain Graphs (2010~2013)
• DietAdvisor: A Smart Phone Agent That Recommends Meals and Exercises (2011~2012)
• MARS: A Multimodal Associative Recommendation System (2009 ~ 2010)
• Xtran: Crossmodal Translation of Language and Vision (2008~2010)
• MMG:Cognitive Learning and the Multimodal Memory Game (2007 ~ 2010)
• E-Learn: Personalized e-Learning with Bayesian Networks (2009 ~ 2010)
• Lavatar: Learning Avatars in Virtual Worlds (2009)
• MEC (Phase 3): DNA Computing Algorithms for Molecular Diagnosis (2006 ~ 2009)
• SKT: Hypernetwork Models for Language Learning (2007 ~ 2008)
• MLScene: Learning and Inference from Camera Scene Data (2007)
• ProMiR: Probabilistic Prediction of microRNA (2004~2007)
• MEC: Molecular Evolutionary Computing (Phases I and II, 2000 ~ 2006)
• HyperSNP: Hypergraph Modeling for Large-Scaling Data Analysis (2007~2008)
• AptaCDSS II: A Clinical Decision Assistant System with Knowledge Discovry - A Post AptaCDSS System (2006 ~ 2007)
• DNAChipBench (NRL Project): Intelligent Design and Analysis Technology for DNA Chips (2002~2007)
• LGCore: Machine Learning Technologies for Performance Prediction of Digital Appliances (2006)
• AptaCDSS: A diagnosis support system for cardiovascular disease using aptamer chip (2005-2006)
• SysBio: In silico modeling and network construction of chromosomal replication and segregation (2003-2005)
• LaText: Text mining based on latent variable models (2001 ~ 2004)
• BrainGene: DNA data mining for the analysis of expression patterns of vertebrate brain development-specific genes (rat) (2001 ~ 2003)
• MrHumor: A personalized Internet agent that recommends humors and jokes (2002 ~ 2002)
• AngioProt: Development of a prediction algorithm for angiogenesis-related molecules (2001 ~ 2002)
• MicroGene: Microbial gene identification using probabilistic graphical models (2001 ~ 2002)
• ProClass: Protein classification based on molecular sequence and text information (2000 ~ 2001)
• BioText: Information extraction from biological texts based on Markov models (2000)
• DMDM: DNA microarray data mining using unsupervised learning techniques (2000)
• LEONN: Learning and evolution of neural networks (1998 ~ 2001)
• FACT: Text filtering and classification from large-scale document collections (1998 ~ 2001)
• EOS: Online learning of robot behaviors with evolvable hardware (1998~ 2000)
• NetMining: Network intrusion detection using active datamining techniques (1998 ~ 2000)
• eClerk: A learning agent for recommending products at a virtual shopping mall (1998 ~ 1999)
• NACST: Nucleic acid computing simulation toolbox (1998 ~ 1999)
• ScaiTrec: SCAI at Text REtrieval Conference (TREC) (1998 ~ )
• STAR: Statistical learning for ambiguity resolution (1998)
• WAIR: Intelligent learning agents for personalized information retrieval on the Web (1997 ~ 1998)
• ECTOP: Evolutionary computing theory for optimization (1997)
• MACS: Evolving homing and herding behaviors of multiple robotic agents (1996 ~ 1999)
• AGIPT: Adaptive genetic programming systems for flexible information processing (1996 ~ 1998)
• ALENN: Active learning evolutionary neural networks (1996)
• GAMAR: Genetic algorithms for multicast routing (1995 ~ 1997)
• SIFOGA: Statistical inference as a foundation of genetic algorithms (1993 ~ 1996)

This page is maintained by Byoung-Tak Zhang (btzhang@bi.snu.ac.kr).
Last update: October 3, 2013.