Welcome to my corner of the web! I am a cognitive scientist, roboticist and an AI researcher. My research is a multidisciplinary attempt to connect cognitive science, AI and robotics to understand the brain's way of governing behaviours and design intelligent machines that assist us in understanding our own intelligence.

Explore this website to know more about my work, research projects,  and views.  And yes I would love to learn from you, so do send your comments

Latest Updates

April 2020 - Creative AI is coming!
 @  Paper Submitted! Creative  Problem-Solving in Robots using  Constructive  Episodic Simulations.   
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Jan 2020 - News!! Paper on Aesop's Fable Causal Learning accepted
ICLR 2020 A  Causal Learning by a Robot with Semantic-Episodic Memory in an Aesop's Fable Experiment, International Conference on Learning and Representation, (ICML), Addis Ababa  arXiv:2003.00274 https://arxiv.org/abs/2003.00274    
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Dec 2019 - A big milestone!
Completed a monster 135-page description and modeling of Cross-situational Word Learning!
 Word-Object Learning via Visual Exploration in Space (WOLVES):  A  Neural  Process  Account of  Cross-Situational  Word  Learning.  https://doi.org/10.31219/osf.io/kxycs in review Psychological Review      

Connecting  Looking to Learning in infants, submitted  Psyc Review (2020)

"WOLVES Model"

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July 2019 - Exciting News!!!
Our Article titled  " Muscle-less motor synergies and actions without movements.  From motor neuroscience to embodied cognition"  published by  Physics of  Life  Reviews     
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July 2018 - News!!!!!!   Paper accepted at CogSci Conference
@ Madison Wisconsin. The paper presents simulations of 3 empirical word-learning experiments using our model WOLVES.  A dynamic neural field model of memory, attention and cross-situational word learning.
Read the full paper here
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14 Apr 2018 - Wooh!
Our paper on Spatial Planning and Cooperation ACCEPTED in Cognitive  Computation!!
 Title: Goal-directed  reasoning  and  cooperation  in  robots  in  shared workspaces:  An  internal  simulation-based  neural  framework

Goal-directed  reasoning  and  cooperation  in  robots  in  shared workspaces:  An  internal  simulation-based  neural  framework, Cognitive Computation (2018)

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Jan 2018 - Paper on human-robot collaboration accepted at BICA
@ The article uses action imagination to recall robot's past experiences. The present context enables the system to infer the consequences of both its own actions/goals and observed actions/goals of the human partner (by analogy).
Read the paper here.
Title:  Joint Goal Human-Robot collaboration-From Remembering to Inferring
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11 August 2017- Presenting a keynote at  SSM College, Srinagar
Memory Clouds for Future Robots” at Workshop on AI and Cloud Computing
@  National workshop on cloud computing and the IoT 
Topic: Memory Clouds for Future Robots”
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15 May 2017- I am at Leiden, the Netherlands!
@  Lorentz Center attending a 5-day Workshop on “Perspectives on Developmental Robotics”
Excellent experience and quite some discussions!
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11 May 2017- Presenting my first work on child development!
@  International Conference, “Stop me if you think you've heard this one before”: Novelty, Repetition and the Brain, 
UEA, Norwich UK
Topic: Influence of novelty on early word learning in cross-situational scenarios
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Exciting! BBC covers our Aesop's Fable work in  “Science  in Action” Programme
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Update
09 Nov 2016 - I  just moved to UEA to join the Developmental Dynamics Lab. Check my official page here
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Eureka!!! 
07 Jul 2016-A humanoid just inferred Archimedes Principle! believe it?
You heard that right, we did it again!
Our work on Causality and Learning of Physical Law Inferencing accepted in Royal Society Interface
Video (left) below shows the experiments on corvids that we recreated with iCub (right).

Aesop's Fable experiment for causal learning in robots, Article in ROYAL SOC. INTERFACE (2016)

"Humanoid infers Archimedes' Principle"

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A compilation of some of our DARWIN robot demonstrations at Profactor
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28 April 2016
Thesis Defended! 
The central premise of the thesis is that cognition is constructive manipulation of memory.  Based on this, it proposes a novel brain guided perspective on the design of cognitive architectures for cumulatively developing systems. Set up in the context of several experiments from animal and infant cognition reenacted on the iCub humanoid, the thesis proposed a principled framework for cumulative learning of actions, skills, affordances and cause-effect relations through multiple streams (imitation, exploration, linguistic inputs).

I recently defended my PhD 

"Towards a Brainlike MΞMϽRY for Cognitive Robots" 

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Some exciting news!
07 Dec 2015- Our paper on Neural Body Schema Based Motor Control Work accepted in Autonomous Robots
Edit: Link to the article and video below

Article published in Autonomous Robots (2016)

"Towards a learnt neural body schema for dexterous coordination of action in humanoid and industrial robots"

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Update: Our paper on learning of force-motion relationships accepted in BICA Journal & Conference 
These pushing experiments apply force on objects to learn object affordances and predict the physical motion of novel objects. 
Link to the paper is here
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Here goes our first update
24 July 2015- I am in Gaudi's beautiful city of Barcelona!
@ the Living Machines Conference 2015, presenting my work on
How  iCub  Learns  to  Imitate  Use  of  a  Tool  by  Recycling  the  Past Knowledge Learnt During Drawing
Edit: Link to article is here http://dx.doi.org/10.1007/978-3-319-22979-9_33

iCub Learning to use a tool through imitating a teacher's actions

We go live!

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© 2020 by Ajaz A. Bhat

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