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MARVL

MULTI AGENT ROBOTICS &

VISION LEARNING LAB

Multi-Agent Robotics Vision and Learning (MARVL) Lab focuses on research in- mobile robotics,  multi-robot, coordination, planning and  scheduling, computer vision and machine learning.

 

The applications of  our research are in field robotics specifically with marine, ground and aerial robots working with humans.  

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unmanned

ground vehicles

  • Autonomous Urban Driving

  • Multi-Class mobility on demand

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RESEARCH

Marvl AUV

Marine robotics

  • Surface

  • Underwater Vehicles

  • Search and rescue

  • Monitoring

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aerial ROBOTICS

  • Human robot coordination

  • AI-Augmented Swarm Intelligence

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PUBLICATIONS

 
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LinkedIn

Twitter

Malika Meghjani

Graduate Student | Diver | Netflix

Dr. Malika Meghjani is an Assistant Professor in the Information Systems Technology and Design Pillar at Singapore University of Technology and Design (SUTD). She directs the Multi-Agent Robotics Vision and Learning (MARVL) Lab, with the focus on algorithm design for efficient, reliable and scalable robots that can work independently and collaboratively with humans. Her research interests are in planning under uncertainty, reinforcement learning, computer vision, deep learning, and game theory. The applications of her work are in field robotics ranging from marine robots specifically, underwater and surface vehicles to self-driving cars and other ground vehicles in unstructured environments. 

SCIENTIFIC TEAM

PHD 

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Github

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Twitter

Pamela

Graduate Student | Diver | Netflix

Dr. Malika Meghjani is an Assistant Professor in the Information Systems Technology and Design Pillar at Singapore University of Technology and Design (SUTD). She directs the Multi-Agent Robotics Vision and Learning (MARVL) Lab, with the focus on algorithm design for efficient, reliable and scalable robots that can work independently and collaboratively with humans. Her research interests are in planning under uncertainty, reinforcement learning, computer vision, deep learning, and game theory. The applications of her work are in field robotics ranging from marine robots specifically, underwater and surface vehicles to self-driving cars and other ground vehicles in unstructured environments. 

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Github

LinkedIn

Twitter

Loo Yi
Graduate Student | Diver | Netflix

Dr. Malika Meghjani is an Assistant Professor in the Information Systems Technology and Design Pillar at Singapore University of Technology and Design (SUTD). She directs the Multi-Agent Robotics Vision and Learning (MARVL) Lab, with the focus on algorithm design for efficient, reliable and scalable robots that can work independently and collaboratively with humans. Her research interests are in planning under uncertainty, reinforcement learning, computer vision, deep learning, and game theory. The applications of her work are in field robotics ranging from marine robots specifically, underwater and surface vehicles to self-driving cars and other ground vehicles in unstructured environments. 

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Github

LinkedIn

Twitter

Tan Yu Xiang

Graduate Student | Diver | Netflix

Dr. Malika Meghjani is an Assistant Professor in the Information Systems Technology and Design Pillar at Singapore University of Technology and Design (SUTD). She directs the Multi-Agent Robotics Vision and Learning (MARVL) Lab, with the focus on algorithm design for efficient, reliable and scalable robots that can work independently and collaboratively with humans. Her research interests are in planning under uncertainty, reinforcement learning, computer vision, deep learning, and game theory. The applications of her work are in field robotics ranging from marine robots specifically, underwater and surface vehicles to self-driving cars and other ground vehicles in unstructured environments. 

MASTERS

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Github

LinkedIn

Twitter

Pamela

Graduate Student | Diver | Netflix

Dr. Malika Meghjani is an Assistant Professor in the Information Systems Technology and Design Pillar at Singapore University of Technology and Design (SUTD). She directs the Multi-Agent Robotics Vision and Learning (MARVL) Lab, with the focus on algorithm design for efficient, reliable and scalable robots that can work independently and collaboratively with humans. Her research interests are in planning under uncertainty, reinforcement learning, computer vision, deep learning, and game theory. The applications of her work are in field robotics ranging from marine robots specifically, underwater and surface vehicles to self-driving cars and other ground vehicles in unstructured environments. 

man.png
linkedin.png
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Github

LinkedIn

Twitter

Loo Yi
Graduate Student | Diver | Netflix

Dr. Malika Meghjani is an Assistant Professor in the Information Systems Technology and Design Pillar at Singapore University of Technology and Design (SUTD). She directs the Multi-Agent Robotics Vision and Learning (MARVL) Lab, with the focus on algorithm design for efficient, reliable and scalable robots that can work independently and collaboratively with humans. Her research interests are in planning under uncertainty, reinforcement learning, computer vision, deep learning, and game theory. The applications of her work are in field robotics ranging from marine robots specifically, underwater and surface vehicles to self-driving cars and other ground vehicles in unstructured environments. 

woman.png
linkedin.png
linkedin.png
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Github

LinkedIn

Twitter

Pamela

Graduate Student | Diver | Netflix

Dr. Malika Meghjani is an Assistant Professor in the Information Systems Technology and Design Pillar at Singapore University of Technology and Design (SUTD). She directs the Multi-Agent Robotics Vision and Learning (MARVL) Lab, with the focus on algorithm design for efficient, reliable and scalable robots that can work independently and collaboratively with humans. Her research interests are in planning under uncertainty, reinforcement learning, computer vision, deep learning, and game theory. The applications of her work are in field robotics ranging from marine robots specifically, underwater and surface vehicles to self-driving cars and other ground vehicles in unstructured environments. 

man.png
linkedin.png
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Github

LinkedIn

Twitter

Loo Yi
Graduate Student | Diver | Netflix

Dr. Malika Meghjani is an Assistant Professor in the Information Systems Technology and Design Pillar at Singapore University of Technology and Design (SUTD). She directs the Multi-Agent Robotics Vision and Learning (MARVL) Lab, with the focus on algorithm design for efficient, reliable and scalable robots that can work independently and collaboratively with humans. Her research interests are in planning under uncertainty, reinforcement learning, computer vision, deep learning, and game theory. The applications of her work are in field robotics ranging from marine robots specifically, underwater and surface vehicles to self-driving cars and other ground vehicles in unstructured environments. 

RESEARCH STAFF

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Github

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Duong
Graduate Student | Diver | Netflix

Dr. Malika Meghjani is an Assistant Professor in the Information Systems Technology and Design Pillar at Singapore University of Technology and Design (SUTD). She directs the Multi-Agent Robotics Vision and Learning (MARVL) Lab, with the focus on algorithm design for efficient, reliable and scalable robots that can work independently and collaboratively with humans. Her research interests are in planning under uncertainty, reinforcement learning, computer vision, deep learning, and game theory. The applications of her work are in field robotics ranging from marine robots specifically, underwater and surface vehicles to self-driving cars and other ground vehicles in unstructured environments. 

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Github

LinkedIn

Twitter

Sahil
Graduate Student | Diver | Netflix

Dr. Malika Meghjani is an Assistant Professor in the Information Systems Technology and Design Pillar at Singapore University of Technology and Design (SUTD). She directs the Multi-Agent Robotics Vision and Learning (MARVL) Lab, with the focus on algorithm design for efficient, reliable and scalable robots that can work independently and collaboratively with humans. Her research interests are in planning under uncertainty, reinforcement learning, computer vision, deep learning, and game theory. The applications of her work are in field robotics ranging from marine robots specifically, underwater and surface vehicles to self-driving cars and other ground vehicles in unstructured environments.