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Physical AI Lab

Research Lab at Ben Gurion University

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PAI Lab's Vision & Mission

Vision & Mission

On the PAI Methodology

"The PAI methodology inherently combines the considerations of materials, design, and manufacturing. Robots developed using PAI may autonomously perform tasks and maintain homeostasis in unstructured environments by exploiting the physical and computational features of their bodies along with the computational abilities of their "brains". Akin to biological organisms, PAI robotics can either replace digital AI or synergistically complement it by interfacing to a "brain". Many small robots, or those with limited computational functionality, would not include a dedicated central "brain," and their body's computation will guide their performance. Similar to the principles of natural diversity, PAI synthesis refers to robotic systems of any functionality, shape, size, and habitat, with particular emphasis on integrating chemical, biological, and material based functionalities."

PAI Methodology

Physical Artificial Intelligence (PAI) refers to the theory and practice of synthesizing lifelike robots. This is achieved by using skills from the disciplines of materials science, mechanical engineering, computer science, chemistry and biology to evolve a fully-functional robot (in the illustration: robotic bee). The process incorporates the considerations of materials, structure, sensing and actuation, and results in a fully autonomous multi-functional robot.  Adopted from "Skills for Physical Artificial Intelligence", Aslan Miriyev, Mirko Kovac, Nature Machine Intelligence, 2, 658-660, 2020.

PAI as a Multidisciplinary Domain

"A number of disciplines are closely intertwined in the ambitious venture of creating PAI. Mainly, these are materials science, mechanical engineering, computer science, chemistry, and biology. Leading the paradigm shift from robots as an assembly of hard devices to PAI-comprised robots requires a combination of skills in these disciplines. The domains of each discipline indicate the great plurality and diversity of the desirable skills, leaving space for even more. However, such a broad range of skills for a single person is difficult to obtain today, and no systematic educational approaches exist to develop them."

PAI as a multidisciplinary domain

Physical Artificial Intelligence (PAI) is comprised of five main disciplines: materials science, mechanical engineering, computer science, biology and chemistry. Adopted from "Skills for Physical Artificial Intelligence", Aslan Miriyev, Mirko Kovac, Nature Machine Intelligence, 2, 658-660, 2020.

 

Scientific and Educational Activity and Mission

The PAI Lab has been created as a unique scientific and educational platform for research on the new domain of PAI. This multidisciplinary research lab involves in a single place research and facilities characteristic of all five above-mentioned fields to allow for dedicated research at the nexus of disciplines.

Research in the PAI Lab shapes the educational path for future generations of engineers, researchers, and scientists by developing skills in multiple disciplines for interdisciplinary work. PAI lab aims at educating engineers and researchers for the capability of tackling problems requiring multidomain vision and understanding.

 

The PAI Lab's mission is  to develop breakthrough approaches, methodology, and educational basis in physical AI via unveiling the scientific fundamentals of creating nature-like intelligent and collaborative robotic systems, allowing for symbiotic human-robot and nature-robot ecosystems. ​

PAI Cover Nature Machine Intelligence

Cover of Nature Machine Intelligence, Issue of November 2020.

Based on the "Hands of creation" image, showing human hands creating PAI by using skills from 5 disciplines. Image credit: Aslan Miriyev Mirko Kovac / Empa and Imperial College London; Cover design: Karen Moore.

People

People
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Dr. Aslan Miriyev

 

Director and Principal Investigator (PI), The PAI Lab

Senior Lecturer (Assistant Professor), Department of Mechanical Engineering

Webpage

Email

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Postdocs

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Dr. Sergey Nechausov

Ph.D. in Polymer Chemistry 

Email

Graduate students

Mr. Yuchen Wang

B.Sc. in Mechanical Design, Manufacturing and Automation

Email

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Mr. Yi Jiang

B.Sc. in Electrical Engineering

Email

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Mr. Mingyao Hou

B.Sc. in Computer Science and Technology

Email

Alumni

Ms. Yini Guo - Intern from The University of Oxford, Summer 2023

News

News

May 1, 2024

We are literally breaking walls now: The brand-new PAI lab will be built here after breaking and demounting the walls 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

February 6, 2024

The PAI Lab members attended a lecture on advanced bibliographic search. The lecture was provided by Mr. Eyal Ben-Yehuda from BGU's Aranne Library.

October 25, 2023

 

A new white paper, "Robotics and Autonomous Systems for Environmental Sustainability: Monitoring Terrestrial Biodiversity", co-authored by a broad international panel of experts, including Dr. Aslan Miriyev, has been published by the UK-RAS (Robotics and Autonomous Systems) Network. 

 

"Biodiversity is monitored in order to gain insights into the state of ecosystems across a diverse range of habitats globally." "The project behind this White Paper began with a literature review to identify the methods used by ecologists to monitor terrestrial biodiversity, and the major barriers they encounter in performing this work. This was followed by a consultation process involving online surveys and workshops during May and June 2023, in which over 120 international experts in biodiversity and RAS took part." The project highlights "where existing RAS capabilities are aligned with biodiversity monitoring requirements, how these capabilities could be extended, and the priorities for future RAS developments." 

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August 25, 2023

The 8-week internship of Yini Guo from the University of Oxford at our PAI Lab has concluded, leaving behind a trail of success and delightful memories from this summer.Throughout her time here, Yini contributed to advancing our multimaterial 3D printer during the workweek while also exploring the beauty of Israel during weekends and holidays.

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August 4, 2023

Our work has been presented at the International Congress on Rheology, held in Athens, Greece, between July 30 and August 4. The talk, entitled "Rheology of photopolymer compositions with dispersed carbon nanoparticles for vat photopolymerization of soft ionic actuators", was a part of the "Rheology for soft robotics and use of field-responsive materials" session.

General

Positions

Positions

PAI Lab welcomes talents. Suppose you are passionate about the ideas of PAI and about contributing to creating sustainable and symbiotic human-robot and nature-robot ecosystems. In that case, PAI Lab is the place for you.

Currently, we are seeking a postdoc and Ph.D. candidate with proven skills in both chemistry and robotics for funded positions.

Also, postdoc candidates in broader areas who have been awarded scholarships are welcome. Otherwise, candidates are encouraged to apply for various open postdoc scholarships (some of them listed here). Applying postdocs must have proven skills combining a strong knowledge of functional materials and their application in soft (synthetic and/or biohybrid) electromechanical systems.

To apply for a position, please contact Dr. Aslan Miriyev via email. Before you apply, please make sure you have checked and/or applied to any available sources of scholarships (internal and/or external). Please mention any scholarships you obtained or applied for in your position application email.

Importantly, please note that a successful candidate is expected to:

  • Be interested in (self-) learning and implementing skills and knowledge from disciplines other than your current major. PAI research is at the heart of the interdisciplinary nexus. In your research, you are expected to be open to the involved factors originating from various domains, be curious about the related interdisciplinary interfaces, and understand their interaction mechanisms.

  • Have excellent written and spoken English skills. This is an absolute prerequisite, as most of the information in today's scientific-technological world is in English. As a leader in your research vector, you are expected to understand the state of the art and formulate and communicate your research in English.

  • Have proven self-learning skills. We are surrounded by an infinite amount of information available from various sources. We need to find, self-learn, adapt and implement it to the needs of our research. The importance of this skill has constantly been increasing, and it is mandatory for multidisciplinary research. 

  • Have proven commitment and self-discipline. Studies and research require many efforts, which may all be a high priority and need to be done simultaneously. You are expected to commit to your tasks and duties and their timely delivery in the PAI Lab. Self-discipline is mandatory to efficiently distribute your time for fruitful work to fine details and avoid overloading yourself and your colleagues.

Contact us

Contact us

To contact the PAI lab, please email the Lab Director, Dr. Aslan Miriyev.

 

Email:

miriyev@bgu.ac.il

Physical Address: 

Ben-Gurion University of the Negev

Department of Mechanical Engineering

Marcus Family Campus

1 Ben-Gurion blvd.

Beer Sheva 8410501

Israel

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