Contact Dr Seemal Asif

Areas of expertise

  • Aerospace Manufacturing
  • Industrial Automation
  • Industrial Ergonomics and Human Factors

Background

Dr. Seemal Asif has over 14 years of experience in research development and delivery in the field of Automation, Robotics, and Systems Integration. Dr Asif is the Co-Investigator on a £1.3 million EPSRC-funded project (EP/V051180/1, 'Reconfigurable robotics for responsive manufacture - R3M'), a £4.8 million EPSRC-funded Made Smarter Innovation Project (EP/V062158/1) and ATI-funded Airbus project for Module -Positioning (AutoRamp; TRL: 5-7). I currently co-manage these projects from Cranfield University (CU) side and look after the research deliverables, providing research direction to Research Assistants, horizontally collaborating with research partners and developing the architecture for systems. The projects require collaboration and communication between academic and industry partners including Airbus, Rolls Royce, Spirit Aero and GKN.

Dr Asif has been involved in several projects sponsored by Airbus, EPSRC and Innovate UK. She has currently one ATI funded grant for 3D Xray Imaging and one Airbus funded project for the large structure positioning automation. She has been instrumental in setting up the Human-robot Interaction for gesture control. One of her research projects focuses on the Relatime Error Correction and Compensation for the Industrial Robots on an open Network. She has an interest in Swarm Intelligence and Hybrid communication. Her work for assembly and automation has been recognised and respected widely.

She has completed her Ph.D. in Robotics and Intelligent Automations at Cranfield University. Seemal received her MSc Software Engineering from the University of York in 2010 and then joined the Intelligent Automation group at the Centre for Structures, Assembly, and Intelligent Automation at Cranfield University as a Research Fellow. Seemal has worked for 4 years in the software engineering industry in an institutional environment where she had the opportunity to research supportive tools for the University. During this time, she worked on multiple projects at various levels from developer to project manager.

She is interested in researching automation, robotics, intelligent automation, machine learning, artificial intelligence, software engineering, formal methods, and control theory. Being naturally inclined towards academia, she finished her MSc Computer Science in 2009 and obtained Eureka Scholarship for the MSc Software Engineering in York. She is a gold medallist for both her Undergrad and Masters.

As part of Cranfield University, she developed the Flexible Cell Coordinator (FLEXA). Flexa was the Seventh Framework Programme (FP7) project with the involvement of companies like Volvo Aero, Rolls-Royce, Avio, MTU (Germany), etc. She teaches and supervises MSc and PhD students in Robotics, Machine Learning, and IoT and Artificial Intelligence.

She is registered as a Chartered Engineer (CEng) by British Engineering Council and recognized as a Fellow of the British Higher Education Academy (FHEA) in the UK and a member of the Institute of Engineering and Technology (IET).

Research opportunities

MSc by research and PhD opportunities are available in the following main areas:

Imitation Learning

Intelligent Robotic Hand

Automated Robotic Welding

Robotic inspection in confined spaces

Robot Swarm Communication Network - A Heterogeneous system

Applied AI and Machine Learning

If you are interested in any of those topics or you may have your own idea, please first discuss with Dr Seemal Asif (s.asif@cranfield.ac.uk) email to arrange the time.

Students are normally expected to identify their own source of funding, e.g. self-funding, an employer, or a nationally-funded scholarship. From time to time, we have funding for PhD scholarships - we always advertise these at https://www.cranfield.ac.uk/research/phd?Keyword=&Theme=aerospace

Current activities

Machine Learning

Internet of Things

System Integration

Artificial Intelligence

IoT 4.0 and 5.0

Robotics

Human-Robot Integration

Intelligent automation

Software Engineering, Design and Architecture

Machine Vision and Image Processing

Formal Methods

Research Students:

Mikel B. Viso (2023-2029)

Emmanuel Izuwa (2023-2029)

Fahad Khan (2023-2029)

Sami Alanazi (2022-2025)

Shifan Li (2020-2023)

Irene Bernardino Sanchez (2022-23)

Jingjing Huang (2022-23)

Hugo Marmonier (2022-23)

Jiaqi Li (2021-22)

AngelosDIMAKOS (2020-21)

AshishJAISWAL(2020-21)

ZhengweiJIN(2020-21)

LalithaORUGANTI(2020-21)

DanielWOODHALL(2020-21)

Robert Zoumboulis-Airey (2020-21)

Ohima Agans-oliha (2020-21)

Daniella Alvarado (2019-20)

Research Titles:

Sensor-Based Object Detection and Localisation for Robot Manipulator

Sensor-Based Object Tracking and Real-time Localisation for Robot Manipulator

FOD Detection and Prevention on Single Aisle Aircraft

Framework for a Flexible and Reconfigurable Robot Cell design

A Framework for Flexible Metrology System for Product Assembly

Model to predict Human Emotion for Adaptive and Smart Human Robot Collaboration in Automation and Manufacturing

Deep Fake its Detection and Societal impacts

Detecting Anomaly Traffic in IoT with Low Computation Overhead by Machine Learning Techniques

Artificial Robotic hand for customising applications

Framework of Robotic GMAW Process in Simulation

Framework for Robot Swarm Communication Network - A Heterogeneous system

Navigating in an unmapped environment with automatic obstacle avoidance

Imitation Learning for performing a task

Automated robotic welding station

Application of different Machine Learning techniques on a Robot to enable multi-purposeness

A Framework for Controlling Multiple Industrial Robots using Mobile Applications

Imitation Learning of Bionic Hand

Module Leader for:

Robotics Control

Artificial Intelligence

Machine Learning

Signal Analysis

Group Project - Applications of Computational Engineering Design (MSc CSTE - Computer Vision)

Clients

  • Airbus SE
  • Wootzano Ltd
  • Haybeesee Ltd

Publications

Articles In Journals