Michail Maniadakis

About

Michail Maniadakis is a researcher whose work spans two richly interconnected domains: robotic systems for waste management and cognitive modeling of time perception. His most impactful contributions lie in advancing AI-driven robotic technologies for recyclable waste sorting, with his 2021 paper on vision-based categorization systems accumulating an impressive 157 citations — a testament to the urgency and relevance of sustainable automation in industrial settings. Complementing this applied focus, his 2020 work on robotic pick-and-toss mechanisms (44 citations) and investigations into vacuum-based grasping further demonstrate his hands-on approach to solving real-world recycling challenges. Equally distinctive is Maniadakis's sustained inquiry into temporal cognition, exploring how the sense of time underpins intelligent behavior in both biological organisms and artificial agents. His 2011 paper arguing for temporal cognition as a cornerstone of intelligent systems (40 citations) and his 2014 review of time models in cognitive science (30 citations) have shaped discussions at the intersection of neuroscience and robotics. Earlier work on coevolutionary agent-based brain modeling reveals a career-long commitment to bio-inspired computation. Across disciplines, Maniadakis consistently bridges fundamental cognitive science with practical robotic engineering, offering tools and frameworks relevant to researchers in AI, automation, and human-robot collaboration.

Research Focus

Key Achievements

Top Papers

1. 1
   Robotic Waste Sorting Technology: Toward a Vision-Based Categorization System for the Industrial Robotic Separation of Recyclable Waste

   157 citations · 2021
2. 2
   Robotic Pick-and-Toss Facilitates Urban Waste Sorting

   44 citations · 2020
3. 3
   Temporal Cognition: A Key Ingredient of Intelligent Systems

   40 citations · 2011
4. 4
   Time models and cognitive processes: a review

   30 citations · 2014
5. 5
   Modelling brain emergent behaviours through coevolution of neural agents

   21 citations · 2005
6. 6
   On the Use of Vacuum Technology for Applied Robotic Systems

   19 citations · 2020
7. 7
   Agent-Based Brain Modeling by Means of Hierarchical Cooperative Coevolution

   14 citations · 2009
8. 8
   Time-informed task planning in multi-agent collaboration

   14 citations · 2016
9. 9
   Hierarchical Cooperative CoEvolution Facilitates the Redesign of Agent-Based Systems

   12 citations · 2006
10. 10
    Intelligent robotic system for urban waste recycling

    11 citations · 2022

Key Collaborators

Contact & Links