• Class Number 2713
  • Term Code 3430
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Dr Abhishek Bhardwaj
    • Dr Abhishek Bhardwaj
  • Class Dates
  • Class Start Date 19/02/2024
  • Class End Date 24/05/2024
  • Census Date 05/04/2024
  • Last Date to Enrol 26/02/2024
SELT Survey Results

This course will introduce students to current research trends in an area of computational mathematics. Topics covered each year will vary but will cover one or more of those listed below, or even new emerging topics:

  • Data mining algorithms
  • Multiscale and multilevel techniques
  • The numerical solution of PDEs
  • Optimisation, approximation in particular of high-dimensional functions
  • Algorithms for the solution of linear systems of equations including iterative methods.


Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Explain the fundamental concepts of a topic in computational mathematics and its role in modern mathematics and applied contexts.
  2. Demonstrate accurate and efficient use of specific computational mathematics techniques.
  3. Demonstrate capacity for mathematical reasoning through analysing, proving and explaining concepts from computational mathematics.
  4. Conduct some (limited) independent research under expert supervision.

Research-Led Teaching

This is a reading course designed for self motivated students. The course is structured so that students from the class will present material from the resources to each other (with guidance from the lecturer only when necessary) - as such the class structure will be lead by the students. One of the aims of the course is to give students more experience in conducting, and presenting research.

Statistical and Computational Inverse Problems - Jari Kaipo, Erkki Somersalo

Staff Feedback

Students will be given feedback in the following forms in this course:

  • formal and informal oral and written feedback on presented material;
  • formal and informal written feedback on written material.

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Other Information

This course code is used for a variety of special topics classes offered to advanced mathematics students. The topics vary from semester to semester, and interested students should attend the course meeting at 10am on the first Monday of semester (details here: https://maths.anu.edu.au/study/courses/math3349-special-topics-mathematics). At this meeting the current topics will be announced, along with the required background.

Class Schedule

Week/Session Summary of Activities Assessment
1 This course code is used for a variety of special topics classes offered to advanced maths students. The topics vary from semester to semester. In Semester 1 2024 the topic covered is Inverse Problems.
This course will focus on the statistical approach to inverse problems with an emphasis on modelling and computations. The framework is the Bayesian paradigm, where all variables are modelled as random variables, the randomness reflecting the degree of belief of their value, and the solution of the inverse problem is expressed in probability densities. Some topics covered are, construction of prior models, Bayesian estimation, Markov Chain Monte-Carlo as well as optimisation methods. 
This is a reading course designed for self motivated students. The course is structured so that students from the class will present material from the resources to each other (with guidance from the lecturer only when necessary) - as such the class structure will be lead by the students. One of the aims of the course is to give students more experience in conducting, and presenting research.
The assessment for this course will be based on a research report conducted throughout the semester that explores one (or more) of the applications of the theory. These include topics such as image deblurring, limited angle tomography, biomagnetic inverse problems, etc.

Tutorial Registration

Workshop registration is via MyTimetable. ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

Assessment Summary

Assessment task Value Learning Outcomes
Research Proposal 10 % 1,2,3,4
Introduction & Literature Review 15 % 1,2,3,4
Research Report First Draft 20 % 1,2,3,4
Final Report 30 % 1,2,3,4
Peer Review 10 % 1,2,3,4
Revisions 5 % 1,2,3,4
Research Presentation 10 % 1,2,3,4

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details


ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.


In Semester 1 2024, this course is delivered in person, on campus. Topics courses are intended for advanced students with high level of engagement in the subject matter. Regular attendance and engaged participation are expected.

Assessment Task 1

Value: 10 %
Learning Outcomes: 1,2,3,4

Research Proposal

Students must submit a 1 page research proposal, which outlines an application of Inverse Problems that they will explore through the semester and apply their theoretical knowledge to.

Assessment Task 2

Value: 15 %
Learning Outcomes: 1,2,3,4

Introduction & Literature Review

Students must conduct a preliminary literature review on their chosen research topic. The literature review should include a history of the topic, with emphasis on the developments and improvements made in computational aspects. The literature review should also include a brief exposition into the current state-of-the-art methodologies in their chosen research topic. Based on the literature review, the students must also submit a (draft) introduction to their research report.

Assessment Task 3

Value: 20 %
Learning Outcomes: 1,2,3,4

Research Report First Draft

Students must submit a first draft of their research report. This should include the following sections; 1 introduction, 2 background, 3 problem statement & solution approach, 4 results, and 5 conclusions/discussions. While it is not essential to have every section completed fully, a proportion of the grade will be based on the completeness of the draft at the examiners discretion; this is done to avoid students only having completed a single section and leaving the rest blank.

Assessment Task 4

Value: 30 %
Learning Outcomes: 1,2,3,4

Final Report

Students must submit their completed final research reports. Guidelines and the grading scheme that will be used for the Final Report will be provided on Wattle.

Assessment Task 5

Value: 10 %
Learning Outcomes: 1,2,3,4

Peer Review

Students must review their peers research reports and provide feedback to their classmates. As this will be an unfamiliar task to most students, a review rubric will be provided to the students to use as a guide.

Assessment Task 6

Value: 5 %
Learning Outcomes: 1,2,3,4


Students must submit a revised version of their research report which addresses the comments and concerns raised by the examiner as well as the peer reviews conducted by their classmates.

Assessment Task 7

Value: 10 %
Learning Outcomes: 1,2,3,4

Research Presentation

Students must give a 15 minute oral presentation summarising their research over the semester.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.


The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

You will be required to agree to a declaration as part of the submission of your assignments, that will record your understanding of ANU academic integrity principles. MATH4201 does not use Turnitin, having been granted an exemption. See the course Wattle site for more information.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Late submission NOT permitted. Submission of assessment tasks without an extension after the due date is not permitted: a mark of 0 will be awarded.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Dr Abhishek Bhardwaj

Research Interests

Dr Abhishek Bhardwaj

By Appointment
By Appointment
Dr Abhishek Bhardwaj

Research Interests

Dr Abhishek Bhardwaj

By Appointment
By Appointment

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