Undergraduate Teaching 2025-26

2025-26

2025-26

Not logged in. More information may be available... Login via Raven / direct.

Engineering Tripos Part IIA, 3F8: Inference, 2025-26

Leader

Prof. Richard E. Turner

Lecturer

Prof. Richard E. Turner

Lab Leader

Dr C Steinruecken

Timing and Structure

Lent Term.

Prerequisites

3F3 Statistical Signal Processing

Aims

The aims of the course are to:

  • Provide a thorough introduction into the topic of statistical inference including maximum-likelihood and Bayesian approaches
  • Introduce inference algorithms for regression, classification, clustering and sequence modelling
  • Introduce basic concepts in optimisation and dynamic programming

Objectives

As specific objectives, by the end of the course students should be able to:

  • Understand the use of maximum-likelihood and Bayesian inference and the strengths and weaknesses of both approaches.
  • Implement methods to solve simple regression, classification, dimensionality reduction, clustering and sequence modelling problems.
  • Implement simple optimisation methods (gradient and coordinate descent, stochastic gradient descent) and dynamic programming (Kalman filter or forward algorithm).

Content

Introduction to inference (2L)

  • Revision of maximum likelihood and Bayesian estimation
  • Revision of Bayesian decision theory
  • Outline of the course

Regression (3L)

  • What are regression problems
  • Revision of properties of Gaussian probability density
  • Maximum likelihood and Bayesian fitting of Gaussians
  • Linear regression and non-linear regression

Classification (2L)

  • Classification problems
  • Logistic regression probabilistic model
  • Training logistic regression using optimisation
  • Stochastic optimisation methods
  • Non-linear feature expansions for logistic regression​​

Dimensionality Reduction (2L)

  • What is dimensionality reduction
  • Principal component analysis as minimising reconstruction cost
  • Principal component analysis as inference​

Clustering (3L)

  • What is clustering
  • The k-means algorithm
  • Gaussian Mixture Models
  • The Expectation Maximisation (EM) Algorithm

Sequence models (3L)

  • Sequence modelling problems
  • Markov Models and Hidden Markov models
  • Inference in Hidden Markov Models using dynamic programming

Very Basic Monte Carlo (introduced through the lectures above)

  • Simple Monte Carlo

Further notes

Lecture allocations above are approximate.

Coursework

Title: Logistic Regression for Binary Classification

To implement an algorithm for performing classification, called logistic regression, using gradient descent optimisation.

Learning objectives: 

  • understand the logistic regression model through visualising predictions 
  • how to apply maximum likelihood and MAP fitting using optimisation
  • how to implement gradient ascent
  • understand how feature expansions can turn linear methods into non-linear methods

Practical information:

  • Sessions will take place in the DPO, during week(s) [TBD].
  • This activity involves a small amount of preliminary work [estimated duration 1hr].

Full Technical Report:

Students will have the option to submit a Full Technical Report.

Booklists

There is no required textbook. However, the material covered is treated excellent recent text books:

Kevin P. Murphy Machine Learning: a Probabilistic Perspective, the MIT Press (2012).

David Barber Bayesian Reasoning and Machine Learning, Cambridge University Press (2012), available freely on the web.

Christopher M. Bishop Pattern Recognition and Machine Learning. Springer (2006)

David J.C. MacKay Information Theory, Inference, and Learning Algorithms, Cambridge University Press (2003), available freely on the web.

Examination Guidelines

Please refer to Form & conduct of the examinations.

 
Last modified: 10/02/2026 17:28

Engineering Tripos Part IIA, 3F7: Information Theory and Coding, 2025-26

Leader

Prof Ramji Venkataramanan

Lecturer

Prof R Venkataramanan

Lab Leader

Dr Jossy Sayir

Timing and Structure

Michaelmas Term. 16 lectures. Assessment: 100% exam. Lectures will be recorded.

Aims

The aims of the course are to:

  • To introduce students to the principles of information theory, data compression, and error-correction, which form the foundations of modern communication and information processing systems.

Objectives

As specific objectives, by the end of the course students should be able to:

  • Explain why entropy and channel capacity arise as fundamental limits for data compression and transmission, respectively
  • Understand and implement basic compression algorithms such as Huffman coding and Arithmetic coding
  • Encode and decode information using simple linear block codes
  • Implement decoding algorithms for modern error-correcting codes such as LDPC codes

Content

 

Information Theory and Data Compression (11L)

  1. Probability fundamentals; Definitions of entropy, joint entropy, conditional entropy: interpretations as measures of uncertainty 
  2. Noiseless source coding theorem; Significance of entropy as the fundamental limit of compression 
  3. Bounds on code length for lossless data compression
  4. Practical compression algorithms: Huffman coding, Arithmetic coding
  5. Relative Entropy, Mutual Information: Properties and some applications
  6. Discrete Memoryless Channels and Channel Capacity
  7. The channel coding theorem: Random coding and the direct coding theorem; Fano's inequality and the converse theorem
  8. The additive white Gaussian noise (AWGN) channel and its capacity

 

Channel Coding (Error-correcting codes) (5L)

  1. Introduction to block codes; Linear block codes
  2. Representing a linear code using a factor graph; Sparse-graph codes
  3. Message passing decoding of sparse-graph codes for binary erasure channels
  4. The Belief Propagation (BP) algorithm; BP decoding of sparse-graph codes for general binary input channels

Further notes

This module will be of interest to anyone who wishes to  understand how information can be mathematically modelled, measured, compressed, and transmitted. Though not a pre-requisite for 3F4, 3F7 provides a good foundation for further study of digital communications.

Coursework

Data Compression: Build your own CamZIP

 

This lab can be done remotely in your own time, and there is no need to sign up for a lab slot. The lab is based on material that is covered in Week 3 of the lectures, so you can do the lab anytime after that.  If you need help, you can sign up for an online support sessions. Please see the course Moodle for details.

Learning objectives: 

  • To implement various data compression algorithms in Python/Matlab/Octave
  • To compare the compression performance of different techniques on text files
  • To understand the effects of finite precision implementation on the compression performance of arithmetic coding

Practical information:

  • Students can do the lab in their own time. Scheduled 'helpdesk' sessions will be held during Michaelmas term (times will be announced on Moodle)

Full Technical Report:

Students will have the option to submit a Full Technical Report.

Booklists

The following are useful references:

  • T. Cover and J. Thomas, Elements of Information Theory, Wiley-Blackwell, 2006.
  • D. MacKay, Information Theory, Inference and Learning Algorithms, Cambridge University Press, 2003 (free electronic copy available for download)
  • T. Richardson and R. Urbanke, Modern Coding Theory, Cambridge University Press, 2008.
  • R. Blahut, Algebraic Codes for Data Transmission, Cambridge University Press, 2012. 

Examination Guidelines

Please refer to Form & conduct of the examinations.

 
Last modified: 28/04/2026 14:34

Engineering Tripos Part IIB, 4M21: Software engineering and design (shared with IIA), 2025-26

Module Leader

Dr Elena Punskaya

Lecturer

Dr Elena Punskaya

Lecturer

Professor Per Ola Kristensson

Timing and Structure

Lent term. 16 lectures (including integrated examples classes). Assessment: 100% exam.

Objectives

As specific objectives, by the end of the course students should be able to:

  • Understand the main issues and processes necessary to achieve effective software product development.
  • Understand the benefits of modularity in design, be familiar with the main object oriented analysis and design concepts and processes.
  • Be familiar with formal design tools for object orientated design and analysis.
  • Understand software development methodologies.
  • Understand fundamental properties of users.
  • Have an awareness of user research methods and design theory.
  • Understand and apply user interface design principles.
  • Apply systematic design methods for user interface design and evaluation.

Content

Software forms an important part of many modern engineering products, from telecommunications to automotive to internet-based systems. This course will provide an understanding of the technical and management processes involved in the design of software systems, including human-computer interaction. Software engineering concepts are considered at a range of scales, from the manipulation of object-orientated concepts, through architectural design components, to the building of large complex software systems. 

Software Engineering and Design

  • Concepts behind software design: managing complexity of the software systems and 
minimizing risks.
  • Modularity in design and object-orientated software design and analysis: 
encapsulation, abstraction, polymorphism and inheritance.
  • Formal tools: introduction to UML.
  • Design patterns: frequently occurring design techniques and their role in building 
systems. 
  • Software development methodologies: from waterfall to agile programming.
  • Quality assurance and risk management: testing, automated testing, tools.
  • Software management: project lifecycle, release management, organising 
software teams, software innovation.

Human-Computer Interaction

  • Understanding people: perception, motor control, cognition, needs and motivations.
  • User research: interviews, field research, survey research, unobtrusive research.
  • Interaction: information and control, dialogue, artificial intelligence, tool use, practice.
  • User interfaces: input devices, displays, interaction techniques, commands and navigation, graphical user interfaces, reality-based interaction.
  • Design: design cognition, design processes, design practice.
  • Engineering: engineering processes, systems, safety and risk, engineering methods.
  • Evaluation: analytic methods, think-aloud studies, experiments.

Booklists

Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.

 

Examination Guidelines

Please refer to Form & conduct of the examinations.

 
Last modified: 04/06/2025 13:33

Engineering Tripos Part IIB, 4M20: Introduction to Robotics, 2025-26

Module Leader

F Forni

Lecturers and Demonstrators

R. Antonova, J. Bonsor-Matthews, K. Chu, F. Forni, D. Hardman, M. Ishida, A. Prorok, C. Sirithunge, X. Wang

Timing and Structure

Michaelmas term, 100% coursework

Prerequisites

3C5 useful; 3C8 useful; 3F2 useful; 3F3 useful, 3F8 useful.

Aims

The aims of the course are to:

  • Explain the core principles of modern robotics.
  • Gaining a comprehensive overview of the current robotics landscape.

Objectives

As specific objectives, by the end of the course students should be able to:

  • Apply fundamental modeling and control methodologies to a range of robotic systems.
  • Understand robotic systems across key sub-fields, including soft robotics, robotic learning, human-machine interaction, multi-agent robotics, and bio-inspired robotics.
  • Demonstrate practical skills through hands-on project work and comprehensive assignments.

Content

The course is divided into six modules, each providing a specialized look into a core area of robotics. The syllabus may be subject to minor adaptations. 

Part A – Fundamentals – (5h, F. Forni)

Introduction, architectures, kinematics, dynamics, and control. 

Part B – Soft robotics – (3h, D. Hardman, X. Wang)

Materials, models, actuation, and sensing. 

Part C – Robotic Learning – (3h, R. Antonova,  K. Chu)

Real-time perception, control policy learning, generalization and sim-to-real, semantic understanding. 

Part D – Human robot interaction (2h, C. Sirithunge)

Interaction modalities, information in HRI, and interaction modeling. 

Part E – Multiagent systems and bio-inspired locomotion (2h, A. Prorok, M. Ishida)

Multirobot systems, collective movements, localization, and bio-inspired locomotion. 

Part F – Microcontrollers and robotic programming (1h, J. Bonsor-Matthews)

Controller choice, I/O & comms, real-time systems, programming languages, debugging, and simulation platforms.

 

Coursework

The assignments will be 100% coursework. The coursework is divided in four assignments. Each assignment is worth 25% of the final grade, with an expected time commitment of approximately 10 hours/assignment.

Part A – Fundamentals

Format: Individual report, 4 pages, anonymously marked.

Due date & marks: 13 November 2025 [15/60]

Part B – Soft robotics: 

Format: Individual report, 4 pages, anonymously marked.

Due date & marks: 27 November 2025 [15/60]

Part C – Robotic learning

Format: Individual report, 4 pages, anonymously marked.

Due date & marks: 6 December 2025 [15/60]

Part D – Human-machine interaction

Format: Individual report, 4 pages, anonymously marked.

Due date & marks: 17 December 2025 [15/60]

 

 

 

 

Booklists

Recommended further reading materials will be instructed in the lectures.

Examination Guidelines

Please refer to Form & conduct of the examinations.

 
Last modified: 02/09/2025 00:35

Engineering Tripos Part IA, 1P4: Computing, 2025-26

Lecturer

Dr F Mancini

Timing and Structure

Michaelmas Term: week 1, 1 introductory lecture; weeks 1-, 12 independent exercises: Lent Term: week 1, 1 lecture; weeks 1-, group project

Prerequisites

None

Aims

The aims of the course are to:

  • Introduce students to computing for engineering applications.
  • Introduction to programming in Python.
  • Enable students to devise and implement algorithms to compute solutions to problems.
  • Develop foundational software engineering skills.
  • Develop skills for team-based software development, including use of version control.

Objectives

As specific objectives, by the end of the course students should be able to:

  • Describe using text and mathematics the purpose and flow of a program.
  • Write and run Python progams in (i) Jupyter notebooks and (ii) from multiple source files.
  • Understand variables, assignment, simple operators and precedence.
  • Appreciate the importance of types and the pitfalls of round-off error and floating point arithmetic.
  • Use of data structures and libraries.
  • Understand the concept of an algorithm and algorithmic complexity.
  • Apply error handling and unit testing as part of good software engineering practice.
  • Develop skills for numerical computing for engineering applications.
  • Be able to develop simple object-oriented data structures.
  • Fetch data from different sources, and manipulate the data and display graphically.

Content

Michaelmas Term

The Michaelmas Term part of the course involves 12 activities for self-study, and each activity has exercises to be completed. The exercises for at least the first six activities must be competed by end of week 2 and will be checked at a sign-up session, and the remainder must be competed by the sign-up session at the end of week 4.  

  • Familiarisation with the Jupyter environment for Python, including use of LaTeX for displaying mathematics
  • Variables and assignment of values
  • Control statements (if, for and while)
  • Types and floating point arithmetic
  • Functions
  • Libraries
  • Numerical computation, including array processing
  • Data plotting
  • Code testing and error handling
  • Algorithms
  • Complexity
  • Data structures
  • Object oriented design

Lent Term

The Lent Term activity is a group exercise, with students working in pairs. Each student takes charge of writing part of a software solution. A modular design and unit testing are required to ensure that the two parts work together correctly. 

  • Problem solving using abstraction and modularisation
  • Structured programming and program modularisation using functions
  • Using data structures
  • Using library functions and handling exceptions
  • Developing and running programs written in multiple source files
  • Use of git for version control

Further notes

There are separate web pages associated with each Term's coursework:

https://github.com/CambridgeEngineering/PartIA-Computing-Michaelmas

https://cued-partia-flood-warning.rtfd.io/

 

Examples papers

There are two examples papers: the first one is issued over the Christmas vacation, the second over the Easter vacation.

Booklists

Please refer to the Booklist for Part IA Courses for references to this module, this can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

 
Last modified: 06/10/2025 20:54

Engineering Tripos Part IIA, 3D3: Structural Materials & Design, 2025-26

Module Leader

Dr R Foster

Lecturers

Dr R Foster, Dr J Becque, Prof A Lawrence

Lab Leader

Dr R Foster

Timing and Structure

Michaelmas Term. 16 Lectures.

Aims

The aims of the course are to:

  • Provide a general understanding of the relationship between the properties of common structural materials, and the principles and approaches underpinning their use in structural design
  • Provide a bridge between the fundamental general engineering understanding of structures and materials developed in Part I and the applied specialist modules of Part II
  • Provide knowledge and knowhow enabling structural designers to improve our use of energy and material in the design of the built environment while providing safe, useful structures for people to use

Objectives

As specific objectives, by the end of the course students should be able to:

  • [1] Use the lower-bound theory of plasticity to perform load-path design of structural arrangements and to appreciate the benefits and limitations of the approach
  • [2] Consider the influence of risk, and variability of loading and material properties, in structural design and calculation
  • [3] Explain the environmental impacts of structural material and design choices
  • [4] Understand and carry out early-stage structural design with various structural materials
  • [4.1] Identify the theoretical and practical considerations governing structural design in various materials and explain how these may be accommodated in design
  • [4.2] Make reasonable conceptual design decisions regarding appropriate structural form, initial layout and initial member sizing for simple structures in various materials;
  • [4.3] Perform preliminary technical design calculations for simple structures in various materials
  • [4.4] Determine what design approaches may be appropriate, and what calculations necessary, for more complex structures in various materials

Content

The implications of the general principles of structural mechanics – equilibrium, compatibility, constitutive laws, and stability – are investigated for different materials. This leads to discussion of typical structural forms in the various materials, the reasons for adopting them, and appropriate methods of construction. The significant types of structural behaviour, and therefore the most useful methods of analysis and calculation, are investigated for the different material types. Our basic aim is to establish means of making reasonable preliminary decisions about structural form, layout and initial sizing of structural members made from a range of common construction materials.

Design methodologies will be developed, and design of typical elements will be discussed, for:

  • materials of low tensile but high compressive strength, such as masonry and glass;
  • composite materials of low tensile strength combined with a ductile tensile material, such as reinforced concrete;
  • high-strength, ductile materials such as steel and aluminium alloys;
  • moderate-  to high-strength, anisotropic, brittle materials such as engineered timber.

The critical modes of failure of structures made from these materials tend to differ, as do other considerations such as environmental impacts, so design approaches will be correspondingly different.

Weeks 1-2 provide an introduction to a number of important considerations and approaches in structural design across materials, such as: loadpaths and the lowerbound theorem; limit state design and variability; resource efficiency and sustainability

Weeks 3-8 apply these considerations and approaches to design with various structural materials including: masonry; glass; reinforced concrete; steel and timber.

 

Coursework

Concrete Lab

Learning objectives: 

To be able to:

1.Describe the common ingredients of concrete and their properties;
2.Design a concrete mix to satisfy certain technical requirements and cast a trial cube;
3.Supervise the casting of reinforced concrete beams and various plain concrete specimens for subsequent testing;
4.Observe and record results of destructive testing and identify different failure modes in concrete;
5.Compare empirical results with theoretical predictions based on as built-data, and evaluate the effectiveness and limitations of the theory.

Practical information:

Details will be available on the course Moodle page early in the term.

Full Technical Report:

Students will have the option to submit a Full Technical Report.

Booklists

Please refer to the Booklist for Part IIA Courses for references to this module, this can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

D1

Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.

S1

The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.

S3

Understanding of the requirement for engineering activities to promote sustainable development.

S4

Awareness of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety, and risk (including environmental risk) issues.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P4

Understanding use of technical literature and other information sources.

P6

Understanding of appropriate codes of practice and industry standards.

P7

Awareness of quality issues.

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US2

A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.

US3

An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.

US4

An awareness of developing technologies related to own specialisation.

 
Last modified: 04/06/2025 13:18

Engineering Tripos Part IIB, 4A4 Aircraft Stability and Control, 2025-26

Module Leader

Dr M Vera-Morales

Lecturer

Dr M Vera-Morales

Lecturer

Dr D Lefas

Lab Leader

Dr M Vera-Morales

Timing and Structure

Michaelmas (8 lectures) and Lent (6 Lectures) + 2 tutorial/examples classes + coursework. Assessment: coursework 100%

Prerequisites

A working knowledge of Part IA and IB fluid mechanics and control theory will be assumed.

Aims

The aims of the course are to:

  • Develop an understanding of the dynamics of an aircraft in flight, and an appreciation of how their characteristics may be improved using automatic control systems.

Objectives

As specific objectives, by the end of the course students should be able to:

  • Appreciate how the equations of motion for an aircraft follow from Newton's second law, and how they may be simplified to the small-disturbance form;
  • Understand how the free modes of motion follow from the equations of motion, and be aware of the approximate derivations of the modes;
  • Know the factors determining the static stability of an aircraft, and understand the significance of the position of the centre of gravity;
  • Have a knowledge of basic control strategies for autopilots, and their effects on aircraft stability;
  • Appreciate that the dynamic characteristics of the aircraft may be improved by feedback control, and understand how this concept applies to stability augmentation systems, and command augmentation systems.

Content

The flight test part of this module has a number limit. If it is oversubscribed, selection will be made on a competitive basis, subject to priority being given to students in Engineering Areas 3 (Aerospace and Aerothermal Engineering) and 8 (Instrumentation and Control). The module can be taken without participating in the flight tests.

Please also note that the first 4A4 lecture will be a briefing session only (lectures start in week 3).  Attendance at the briefing session is essential; if you are forced to miss it, contact the course leader by the end of week 1 at the latest.

Aircraft Stability (8L, Michaelmas term, Dr D. Lefas)

  • Aircraft equations of motion, small disturbance form, stability derivatives.
  • Longitudinal motion: phugoid mode, short period oscillation and approximate forms.
  • Lateral motion: roll subsidence, dutch roll, spiral mode and approximate forms.
  • Static stability of aircraft: longitudinal stability, directional stability, lateral stability.

Automatic Control Systems (6L, Lent term, Dr M. Vera-Morales)

  • Root locus plots and their use in designing feedback control systems.
  • Response to control inputs.
  • Autopilots: pitch and roll angle control, effect on aircraft dynamic response and stability.
  • Stability augmentation systems: pitch rate SAS & yaw damper as means of improving dynamic stability characteristics, relaxed static stability.
  • Command augmentation systems: C-star criterion as basis for longitudinal CAS in fly-by-wire aircraft.

Coursework

Flight tests on Cranfield flying laboratory at the end of the Michaelmas term. Assessment of static and dynamic stability based on flight test data. Design study for an automatic control system for the aircraft. 

 

Coursework Format

Due date

& marks

Static stability

Learning objective:

  • understand how flight-test assessment of static stability is conducted in practice

Individual report

Anonymously marked

Lent term

Weds week 0

[10/60]

Modes of motion

Learning objective:

  • appreciate requirements and difficulties in estimating dynamic stability properties

Individual report

Anonymously marked

Lent term

Weds week 3

[10/60]

Transfer functions

Learning objective:

  • appreciate requirements and difficulties in estimating dynamic stability properties

Individual report

Anonymously marked

Lent term

Weds week 6

[10/60]

Control systems design and final report

Learning objective:

  • use Matlab tools to generate and analyse conceptual control-system designs

Individual report

Anonymously marked

Lent term

Fri week 10

[30/60]

 

Booklists

Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

E4

Understanding of and ability to apply a systems approach to engineering problems.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US3

An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.

 
Last modified: 08/10/2025 15:52

Engineering Tripos Part IIB, 4M3: Spanish, 2025-26

Leader

Mr S Bianchi

Lecturer

Mr S Bianchi

Timing and Structure

Michaelmas Term. Course given at Intermediate and Advanced Levels; 7 lectures + 7 seminars + coursework Assessment Coursework / 3 Tasks: 2 written reports, 1 oral presentation / End of week 3 (30%), end of week 5 (30%), end of week 8 (40%)

Prerequisites

Spanish at Intermediate Level

Aims

The aims of the course are to:

  • To advance understanding in Hispanic science and technology, society and culture.
  • To enable all students to consolidate their listening skills and practise their speaking skills in class, while particular emphasis will be put on reading and writing skills outside the class.

Objectives

As specific objectives, by the end of the course students should be able to:

  • be confident in speaking/reading/writing whether in a general or work-related situation;
  • use the language as a tool to improve understanding of technology, society and culture;
  • analyse a topic/an issue in depth, compare all the elements at play, synthesise the major points and make a balanced judgement.

Content

Seminars (7 Lectures, various speakers, subject to changes)

  • La historia de la ciencia y la ingeniería en el Mundo Hispano: desde el pasado precolombino hasta el presente.
  • Principales avances tecnológicos y su impacto en España.
  • La ingeniería y la tecnología en aplicación en la vasta Hispanoamérica.
  • La industria tecnológica y sus desafíos en el Mundo Hispano.
  • Cómo pueden aplicarse las investigaciones a las necesidades de los países hispanos
  • La educación y la ciencia en España.
  • Una proyección hacia el futuro

Material to be announced in lectures.

A list of this year's module talks will be available at http://www.eng.cam.ac.uk/teaching/language/module-lectures.htm

Seminars

Associated with each lecture will be a one-hour seminar. This may be held before the lecture for preparation, or following the lecture for discussion purposes.

Coursework

The students will prepare 3 major pieces of coursework:

  • Two written reports (25% each)
  • Oral presentation (50%)
  • The assignments will be marked for both language and content (50% language, 50% content)

Coursework

Format

Due date

& marks

Coursework activity #1 Report

A structured report of 900 words in the target language.

Learning objective: 

  • Analyse, synthesise and/or critically evaluate a topic presented and discussed in class (topic related to science, technology or the culture of the Spanish-speaking world)
     
  • Express ideas in a logical and articulate manner using a range of structures and expressions appropriate to the task and expected at the level of proficiency in the target language

Individual report (900 words)

Non-anonymously marked

End of week 3

[25%]

Coursework activity #2 Report

A structured report of 900 words in the target language.

Learning objective: 

  • Analyse, synthesise and/or critically evaluate a topic presented and discussed in class (topic related science, technology or the culture of the Spanish-speaking world)
     
  • Express ideas in a logical and articulate manner using a range of structures and expressions appropriate to the task and expected at the level of proficiency in the target language

Individual report (900 words)

Non-anonymously marked

End of week 5

[25%]

Coursework activity #3 Oral presentation

A structured oral presentation (10-15 minutes followed by questions)

Learning objective: 

  • Analyse, synthesise and/or critically evaluate a topic presented and discussed in class (a topic related to science, technology or the culture of the Spanish-speaking world)
     
  • Express ideas in a logical and articulate manner using a range of structures and expressions appropriate to the task and expected at the level of proficiency in the target language

Individual oral presentation (10-15 minutes followed by questions)

Non-anonymously marked

Last session (week 8)

[50%]

 

 

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

P4

Understanding use of technical literature and other information sources.

 
Last modified: 04/06/2025 13:33

Engineering Tripos Part IIA, 3F2: Systems & Control, 2025-26

Module Leader

Lecturer

Prof R Sephulchre

Lab Leader

Prof G Vinnicombe

Timing and Structure

16 Lectures, Lent Term

Aims

The aims of the course are to:

  • make students familiar with “state-space” methods of modelling and analysing dynamic systems. These methods are extremely important for control engineering, signal processing, and related subjects.

Objectives

As specific objectives, by the end of the course students should be able to:

  • understand what a state-space model is, and how to obtain such a model;
  • relate state-space models to transfer-function models;
  • analyse the behaviour and structure of a state-space model;
  • have some understanding of feedback design using state-space, transfer function and root-locus techniques, and be able to relate them to each other;
  • appreciate the need for and usefulness of state observers, and their role in feedback and other systems.

Content

State-space models (6L)

  • Review of second-year material (linear algebra, transfer functions, poles)
  • Formulation from physical models
  • Linearising nonlinear models
  • Relationship to transfer function matrix (multiple inputs/outputs)
  • Free and forced responses (state-transition matrix convolution, stability)
  • Interconnections of systems

Feedback system design (4L)

  • Review of second-year material (feequency responses, controller structures, objectives of feedback design).
  • The root-locus diagram
  • Routh-Hurwitz criterion (examples of use).

State estimation (3L)

  • Observability.
  • State observer; Oberver design.
  • Connections to Kalman filters, sensor fusion etc.

Control in state-space framework (3L)

  • Controllability.
  • State feedback and pole-placement.
  • Optimal control.
  • State observer combined with state feedback

Examples papers

Paper 1: State-space models - issued in week 3
Paper 2: Root locus - issued in week 5
Paper 3: Observers and state feedback - issued in week 7

Coursework

Inverted pendulum experiment (state feedback). Laboratory report and/or full technical report.

Learning objectives: 

  • State feedback
  • Pole placement
  • Control design

Practical information:

  • Sessions will take place in EIETL laboratory, on Wednesdays and Fridays of full term
  • Students will find it helpful to read through the lab sheet in advance of carrying out the experiment.).

Full Technical Report:

Students will have the option to submit a Full Technical Report.

Booklists

Please refer to the Booklist for Part IIA Courses for references to this module, this can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

E4

Understanding of and ability to apply a systems approach to engineering problems.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US2

A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.

US3

An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.

 
Last modified: 12/01/2026 11:22

Engineering Tripos Part IB, Sustainable Engineering, 2025-26

Coordinator

Dr A Cabrera Serrenho

Lecturer

Dr E Borgomeo

Lecturer

Dr A Cabrera Serrenho

Lecturer

Prof J Cullen

Timing and Structure

5 in-person lectures in Michaelmas Term. Lectures will be recorded but all students are expected to attend in person.

Aims

The aims of the course are to:

  • Introduce some of the key engineering challenges to promote global sustainability

Objectives

As specific objectives, by the end of the course students should be able to:

  • Recognise the scale of the global challenges in energy production and control of climate change, and the importance of identifying, quantifying and pursuing developments which will have significant impact.
  • Understand a range of opportunities to reduce energy consumption and to implement lower carbon technologies, in different sectors of engineering, in both developed and developing economies.
  • Complete a technical investigation into an aspect of Sustainable Engineering.

Content

Students follow up 5 lectures with an individual assignment over the Christmas vacation, submitted as a poster. This is will be followed by a presentation and discussion during Lent term.

Climate Change Mitigation: an Engineering challenge

  • Climate Change: review and targets
  • What makes a difference and what progress has been made to date?
  • Net Zero vs Absolute Zero
  • The need for electrification of energy uses

Technology implementation to step up climate change mitigation

  • Why can’t technology solve everything? Pace of deployment and change
  • How to make sure we are doing the right thing? Life-cycle thinking
  • How fast can we go? What may limit our desired pace of deployment?

 

Pathways for climate change mitigation

  • Buildings
  • Transportation
  • Industry: steel, cement, plastics, fertilisers

Critical minerals for the energy transition

  • Why do we need critical minerals for decarbonisation?
  • What are the challenges associated with securing critical minerals globally?
  • The role of circularity and opportunities for development associated with critical minerals

Water engineering for climate change adaptation

  • Will the world run out of water?
  • Will water cause the next world war?
  • Opportunities for climate change adaptation through water engineering

Coursework

The coursework assessment for Sustainable Engineering comprises two stages:

1.     preparation of a technical poster about a topic discussed in the Sustainable Engineering lectures. The poster should:

·       present an activity or service that can’t happen in 2050 in the same way as today;

·       discuss how that service or activity might be delivered in 2050 and what needs to happen to make it possible.

2.     presentation and discussion of your poster during a 1-hour lab session to take place between weeks 1 and 4 of Lent term.

 

Booklists

Allwood, J. M., Cullen, J. M., Carruth, M. A., Cooper, D. R., McBrien, M., Milford, R. L., Moyniham, M. C., & Patel, A. C. H. (2012). Sustainable Materials with Both Eyes Open. UIT Cambridge. www.withbotheyesopen.com

Ashby, M. F. (2013) Materials and the Environmental — Eco-informed Material Choice. Elsevier. https://www.sciencedirect.com/book/9780123859716/materials-and-the-environment

IPCC — Intergovernmental Panel on Climate Change (2021). 6th Assessment Report. https://www.ipcc.ch

MacKay, D. (2008). Sustainable Energy — Without the Hot Air. UIT Cambridge. http://www.withouthotair.com/Contents.html

UN — United Nations (2015). Sustainable Development Goals. https://sdgs.un.org/goals

Examination Guidelines

Please refer to Form & conduct of the examinations.

 
Last modified: 07/08/2025 13:23

Pages

Subscribe to 2025-26