Imperial College London
MSc in AI Applications and Innovation (MSc AI2)
Deep Learning
Master the fundamentals and advanced methodologies of deep learning, connecting theory to real-world issues. Gain skills to contribute to ongoing advances and research in the dynamic Deep Learning field.
​
​
Lab Session
​Week 5: Colab and setup deep learning environment
Week 6: CNN-based Pytorch Practical Project Implementation
Week 7: RNN and ResNet-based Pytorch Project Implementation
Week 8: Transformer-based Pytorch Project Implementation
Week 9: Individual Project - Coursework Development
Week 10: Individual Project - Coursework Development
Lecture Session
1. Introduction of Deep Learning
2. Foundations of Deep Learning
3. Architectures: CNNs for image processing
4. Architectures: RNNs for sequence data
5. Architectures: GNNs for graph data
6. Generative Models
7. Transformers for NLP.​
8. Practical Applications
Imperial College London
MSc in Biomedical Engineering
(Computational Stream)
My Role: Individual Project Module Co-Lead
Available Projects (Example):​
Title: Machine Learning-Based Tactile Perception for Biomedical Robotics
Tactile perception is a fundamental element of biomedical robotics, as it enables robotic systems to interact gently with biological tissues, manipulate objects precisely for improved control. The integration of tactile sensors with machine learning (ML) techniques presents significant potential for advancing applications such as robotic prosthetics, surgical systems, and rehabilitation or assistive devices. This project focuses on developing ML-driven tactile perception systems to enhance the capabilities of biomedical robotic systems.
​
Research Problem:
Despite notable advancements in robotics and sensor technologies, the real-time processing and interpretation of tactile data remain challenging due to:
-
The high dimensionality and inherent noise in tactile sensor data.
-
The complexity of mapping tactile feedback to specific actions or outcomes.
-
The absence of generalizable ML models capable of adapting to diverse biomedical scenarios.
This project addresses these challenges by designing ML algorithms to interpret tactile data and implement control strategies that support adaptive and autonomous robotic behavior.
Imperial College London
MEng in Biomedical Engineering
(Undergraduate Courses)
Explore the principles of mechanics and electronics and the mathematical connections between the two. Gain practical experience working in electronics and mechanics labs and uncover how these concepts can be used to study bioengineering problems.
​
​
Course Introduction:
Understanding Operational Amplifiers
This course is designed to provide a comprehensive understanding of operational amplifiers (op-amps), which are fundamental building blocks in the design of analogue circuits. Through hands-on experiments, students will explore the versatility and limitations of op-amps, gaining practical skills essential for circuit design and analysis.
Key Objectives of the Course
-
Versatility of Op-Amps:
Demonstrate how op-amps serve as powerful and adaptable components in various circuit configurations. -
Understanding Limitations:
Highlight the imperfections and constraints of op-amps to prepare students for real-world applications. -
Practical Circuit Implementation:
Enable students to implement circuits they design using SPICE simulation software, bridging theoretical knowledge and practical application. -
​
Final Target: Stethoscope Design
As the culminating project for this course, students will apply their knowledge of op-amps and circuit design principles to develop a functional electronic stethoscope. The stethoscope will be designed to amplify biological sounds, such as heartbeats and lung functions, by employing op-amp circuits for signal amplification and filtration.
Key Features of the Stethoscope Design:
-
Amplification Circuit: Use op-amps to amplify low-intensity sounds from the human body.
-
Frequency Filtering: Design filters to isolate specific sound frequencies (e.g., heart sounds, lung sounds).
-
Output Interface: Incorporate a headphone jack or speaker for sound output.
University of Bristol
Biorobotics and Biosystem
Please see the detailed information:
https://www.bristol.ac.uk/study/postgraduate/2022/eng/msc-biorobotics/
Programme Overview
​
The next frontier in robotics will take inspiration from biology to design robots that are soft, smart, green, and social. From microrobots for cancer treatment, to swarms powering warehouses, soft grippers for manufacturing, and new material interfaces for prosthetics, biorobots will provide solutions to today’s global challenges. State-of-the-art robots will in turn power scientific discovery, allowing for the study of living systems in their natural habitats from robots automating experiments in the lab, to artificial fish studying pollution in the deep sea.
​
This programme brings together life scientists and engineers in an interdisciplinary environment where solutions are co-created with stakeholders in mind. For the life scientists, this will open new horizons powered by Robotics and AI, skills in high demand in today’s job market. For the engineers, this will go beyond a typical robotics training, towards reinventing the way robots are designed and used with bioinspiration at heart.
​
This unique combination of biology and engineering will develop core professional skills including working across disciplines and responsible open-ended innovation. The programme centres around a common core in fundamental robotics and life sciences, followed by dedicated taught and project-based biorobotics units that will walk you through latest research and applications, with a hands on understanding of how to build these systems yourself, and demonstrations of how they can be used for good.
Careers
​
Biorobotics MSc students will be at the frontier of bio-inspired robotics. This will make them attractive for the broader robotics and AI industry. Their cross-disciplinary understanding of life sciences will further mean they can work in the life science sector looking to embed robotics and AI in their work flow. Their unique view on robotics and life sciences will also ensure they are well-suited to work in and found start-ups, continue with academic research or work with NGOs interested in deploying robots for good.
Unit Information
This class brings together life scientists and engineers in an interdisciplinary environment where solutions are imagined with stakeholders in mind. The aim is for students to learn a common language, and the inspirations and techniques needed to design, build and deploy novel biorobotic solutions in the real-world. From microrobots for cancer treatment, to swarms monitoring wildlife, or soft robots for prosthetics, they will engineer solutions to today’s global challenges.
Classes will alternate between short lecture introductions to bio-inspirations useful for a new generation of robotics solutions (e.g. synthetic biology, animal behaviour, material science, biomechanics, medicine), and hands-on demonstrations by experts of their robot technologies that are either bio-inspired (soft robots, swarm robots, tactile robots), or are used to aid in the exploration of life-sciences (e.g. monitoring wildlife, automatic scientific discovery, microrobots).
​
Your learning on this unit
By the end of the class, students should be able to:
-
Exploit knowledge and a common language in both disciplines (life sciences and robotics) to design cross-disciplinary solutions in biorobotics.
-
Generate new ideas of bio-inspired technologies for robotics and new robotics applications for life-sciences.
-
Design examples of biorobotics with stakeholder relevance.
-
Assess the societal/environmental impact of their technologies.
How you will learn
The unit will be taught through online or in-person short lectures introducing key concepts in life-sciences that may serve as an inspiration or challenge for robotics, and hands-on demonstrations (which can also be filmed and put-online) of roboticists walking through how their robots works (programming, hardware), and how it is deployed. Breakout sessions (in-person or online) will allow students to reflect on the material, brainstorm new ideas, assess stakeholder relevance, and ethical and societal implications.
How you will be assessed
-
Assessment 1 (30%) Demonstrate knowledge and a common language in both disciplines (life sciences and robotics) to design cross-disciplinary solutions in biorobotics through a blog post explaining an area new to you.
-
Assessment 2 (35%): Pretend to be a consultant, and produce a series of ideas for biorobotics solutions for a given stakeholder challenge (mind map or other similar visual presentation of ideas), highlight ethical/societal issues and mitigations (short video).
-
Assessment 3 (35%): Online test demonstrating key knowledge of Biorobotics concepts.
Group Project in Biorobotics
Unit Information
This group project aims to develop the student’s interest in and knowledge and understanding of Biorobotics. Students will work in cross-disciplinary groups to solve a global challenge provided by a stakeholder (academia, industry, government, NGO).
Biorobotic solutions will be imagined and implemented by the students using skills gained on the Biorobotics programme. Social and ethical considerations will be embedded throughout the project.
​
​
​
​
​
​
​
​
​
Your learning on this unit
On successful completion of the unit students will:
-
Liaise with academic, industry, and non-profit stakeholders to capture key project drivers and requirements.
-
Identify the state-of-the-art in biorobotics related to a specific challenge.
-
Construct and evaluate biorobotic solutions.
-
Systematically identify aspects of contextual analysis for the deployment of a new technology: political, economic, social, technological, legal, environmental (PESTLE) and ethical.
-
Synthesize conclusions and recommendations for future project directions.
How you will learn
This unit is primarily experiential. All projects will be supervised by the unit director, with a mix of short lectures, guided activities, and open time to progress the project within a weekly timetabled session.
How you will be assessed
-
Assessment 1 (20%) - Project pitch: Exploration of application areas / grand challenges. Selection of a challenge to work on for term 2 and outline of a project plan (2 pages).
-
Assessment 2 (20%) - State-of-the-art: presentation of the latest research in the field of the chosen project (blog post).
-
Formative peer assessment - Robots and society: Ethical and societal dimension of the project proposed (2 pages).
-
Assessment 4 (30%) - Demonstration: Live prototype demonstration (short video).
-
Assessment 5 (30%) - Project presentation: Presentation of the project to the stakeholder in a short video (short video).
Biosystems and Biorobotics
2022 Biorobotics Cohort
