General
First Makerere Workshop on Social Systems & Computation
Published
15 years agoon
Summary Top researchers from Northwestern University (Chicago), University of British Columbia (Vancouver) and Makerere (Kampala) are teaming up to offer a workshop on cutting-edge methods for computational modeling of social systems, algorithm design, and machine learning. The sessions will take place between December 3rd and 10th, and there is no cost for attendance; however, registration is mandatory.
Summary Top researchers from Northwestern University (Chicago), University of British Columbia (Vancouver) and Makerere (Kampala) are teaming up to offer a workshop on cutting-edge methods for computational modeling of social systems, algorithm design, and machine learning. The sessions will take place between December 3rd and 10th, and there is no cost for attendance; however, registration is mandatory.
Attendance is limited to academic staff working at a Ugandan university; students doing research in related areas may also be given special permission to attend if space permits. Participants will have the opportunity to publish papers in official, reviewed workshop proceedings at a later date. A certificate of completion will be provided to participants who attend at least two thirds of workshop sessions.
Overview Traditionally, computer science has viewed data as coming from either an adversarial source or from nature itself, giving rise to worst-case and average-case design and analysis of optimization algorithms. In recent years with the advent of modern technologies like the Internet, it has become increasingly apparent that neither of these assumptions reflects reality. Data is neither adversarial nor average, but rather inputs to algorithms are constructed by a diverse set of self-interested agents in an economy, all aiming to maximize their own happiness. Thus the raw data is often not available to an algorithm designer, but must be solicited from the agents–that is, the designer faces an economic constraint. The primary goal of this workshop is to explore the implications of this observation. We will study the performance of algorithms in the presence of utility-maximizing agents and ask whether alternate designs might create incentives for agents to act more optimally. Simultaneously, we will look at other more traditional optimization problems such as approximation and learning and techniques to solve them, pointing out that these may often be leveraged to solve issues in the economic setting.
Related Research Areas Computer Science Theory; Artificial Intelligence; Economics; Business
Format The workshop will consist of six 3-hour lectures, plus meal/breakout sessions for informal research discussion. Spaces are strictly limited, and attendees must pre-register. We will aim to select topics and session times that are best for our participants. To register, and to indicate your preferences for topics and dates, please complete the survey at http://www.surveymonkey.com/s/WWGMKZG.
List of Candidate Topics The workshop will consist of up to six of the following twelve topics.
Introduction to Game Theory
Game theory is the mathematical study of interaction among independent, self-interested agents. It has been applied to disciplines as diverse as economics, political science, biology, psychology, linguistics—and computer science. This tutorial will introduce what has become the dominant branch of game theory, called noncooperative game theory, and will specifically describe normal-form games, a canonical representation in this discipline. The tutorial will be motivated by the question: "In a strategic interaction, what joint outcomes make sense?"
Voting Theory
Voting (or "Social Choice") theory adopts a“designer perspective” to multiagent systems, asking what rules should be put in place by the authority (the “designer”) orchestrating a set of agents. Specifically, how should a central authority pool the preferences of different agents so as to best reflect the wishes of the population as a whole? (Contrast this with Game Theory, whichadopts what might be called the “agent perspective”: its focus is on making statements about how agents should or would act in a given situation.) This tutorial will describe famous voting rules, show problems with them, and explain Arrow's famous impossibility result.
Mechanism Design and Auctions
Social choice theory is nonstrategic: it takes the preferences of agents as given, and investigates ways in which they can be aggregated. But of course those preferences are usually not known. Instead, agents must be asked to declare them, which they may do dishonestly. Since as a designer you wish to find an optimal outcome with respect to the agents’ true preferences (e.g., electing a leader that truly reflects the agents’ preferences), optimizing with respect to the declared preferences will not in general achieve the objective. This tutorial will introduce Mechanism Design, the study of identifying socially desirable protocols for making decisions in such settings. It will describe the core principles behind this theory, and explain the famous "Vickrey-Clarke-Groves" mechanism, an ingenious technique for selecting globally-utility-maximizing outcomes even among selfish agents. It will also describe Auction Theory, the most famous application of mechanism design. Auctions are mechanisms that decide who should receive a scarce resource, and that impose payments upon some or all participants, based on agents' "bids".
Constraint Satisfaction Problem Solving
This hands-on tutorial will teach participants about solving Constraint Satisfaction Problems using search and constraint propagation techniques. This is a representation language from artificial intelligence, used to describe problems in scheduling, circuit verification, DNA structure prediction, vehicle routing, and many other practical problems. The tutorial will consider the problem of solving Sudoku puzzles as a running example. By the end of the session, participants will have written software (in Python) capable of solving any Sudoku puzzle in less than a second.
Bayesian methods and Probabilisitic Inference
Bayesian methods are commonly used for recognising patterns and making predictions in the fields of medicine, economics, finance and engineering, powering all manner of applications from fingerprint recognition to spam filters to robotic self-driving cars. This session will show how principles of probability can be used when making inferences from large datasets, covering issues such as prior knowledge and hyperpriors, the construction of "belief networks", and nonparametric methods such as Gaussian processes. Several applications will be demonstrated.
Computer Vision
It is useful to be able to automatically answer questions about an image, such as "is this the face of person X?", "how many cars are there on this street?" or "is there anything unusual about this x-ray?". This session will look at some of the current state of the art in computer vision techniques, including methods for representing the information in an image (feature extraction), and to recognise objects in an image given such a representation. We will particularly spend some time looking at approaches which have been found to work well empirically on object recognition, such as generalised Hough transforms, boosted cascades of Haar wavelet classifiers, and visual bag-of-words methods. Locally relevant applications in crop disease diagnosis, parasite detection in blood samples and traffic monitoring will be demonstrated as illustrating examples.
Learning Causal Structure from Data
Until a few decades ago, it was thought to be impossible to learn causes and effects from purely observational data without doing experiments. Sometimes, however, it is impossible to do experiments (e.g. in some branches of genetics), or experiments may be costly or unethical (e.g. situations in climate change or medicine), so the emergence of computational methods for distinguishing causes, effects and confounding variables is likely to have wide implications. Some principles are now understood for learning the causal structure between different variables, and this session will explain the most successful current approaches, their possibilities and their limitations.
Internet Search and Monetization
The internet is one of the most fundamental and important applications of computer science. Central to its existence are search engines which enable us to find content on the web. This module focuses on the algorithms like PageRank that these search engines use to help us find webpages. It also studies how these engines make money through advertising.
Social Networks
Social networks describe the structure of interpersonal relationships and have many alarmingly predictable properties. While most people have just a few friends, most social networks have at least a few very popular people. Furthermore, most people are closely linked to every other person so that a message (or an idea or a disease) can spread rapidly throughout the network. Finally, social networks tend to be fairly clustered — i.e., if two people share a common friend it is quite likely that they are also friends. This module will discuss the typical structures of social networks, models that explain these structures, and the impact of these structures on activities in the social network such as message routing or the adoption of new technologies.
Two-Sided Matching Markets
Many markets involve two “sides'' that wish to be matched to one another. For example, a marriage market matches women to men; a job market matches workers to employers. In such settings, people on each side have strict preferences over the options on the other side of the market. Hence, a woman Julie may like David best, John second best, and Christopher third. David on the other hand may prefer Mary to Julie. In such settings, what matches might we expect to form? Can these matches be computed by a centralized algorithm, a match-maker for example, and what are the corresponding incentives of the participants? These questions are of fundamental importance as such centralized algorithms are in use in many important markets. In many countries, medical students are matched to hospitals using such algorithms, or school children to schools.
Approximation Algorithms
In the field of algorithms, many tasks turn out to be computationally difficult. That is, the time to complete the task is fundamentally large compared to the size of the problem. For example, consider the problem of finding the optimal way to visit 10 cities, visiting each exactly once. To minimize travel time, one could test all possible travel schedules, but for 10 cities there are already 3.5M of them! Unfortunately, there is not a significantly quicker way to find the optimal solution. However, one can find an approximately optimal solution quickly. That is, with just a few things to check, one can design a schedule that takes at most 50% more time than the optimal one. In this module we showcase a few general techniques for computing approximate solutions to hard problems, including the use of randomization and linear programming.
Graph Theory
A graph is a combinatorial object consisting of nodes and edges, and is a extremely valuable abstraction of many practical problems. For example, nodes might represent jobs and edges might connect pairs of jobs that can not be performed simultaneously. Alternatively, nodes might represent electronic components on a circuit board and edges the wiring that connects them. Many questions that arise in such domains can be cast as an optimization question in the corresponding graph. The number of workers required to complete all jobs in fixed time frame in the first example is at its heart a graph coloring problem. Asking whether one can lay out the circuit board so no two wires cross becomes the problem of determining which graphs have planar representations. This course defines graphs, shows how to solve a few fundamental graph problems, and applies them to practical settings.
Speaker Bios
Nicole Immorlica is an assistant professor in the Economics Group of Northwestern University's EECS department in Chicago, IL, USA. She joined Northwestern in Fall 2008 after postdoctoral positions at Microsoft Research in Seattle, Washington, USA and Centruum voor Wiskunde en Informatica (CWI) in Amsterdam, The Netherlands. She received her Ph.D. from MIT in Boston, MA, USA, in 2005 under the joint supervision of Erik Demaine and David Karger. Her main research area is algorithmic game theory where she investigates economic and social implications of modern technologies including social networks, advertising auctions, and online auction design.
Kevin Leyton-Brown is an associate professor in computer science at the University of British Columbia, Vancouver, Canada. He received a B.Sc. from McMaster University (1998), and an M.Sc. and PhD from Stanford University (2001; 2003). Much of his work is at the intersection of computer science and microeconomics, addressing computational problems in economic contexts and incentive issues in multiagent systems. He also studies the application of machine learning to the automated design and analysis of algorithms for solving hard computational problems.
John Quinn is a Senior Lecturer in Computer Science at Makerere University. He received a BA in Computer Science from the University of Cambridge (2000) and a PhD from the University of Edinburgh (2007). He coordinates the Machine Learning Group at Makerere, and his research interests are in pattern recognition and computer vision particularly applied to developing world problems.
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General
Graduate Training Students Advised to Read the Graduate Handbook as a “Bible”
Published
1 day agoon
August 12, 2025By
Eve Nakyanzi
At an orientation for Postgraduate students held at the Yusuf Lule Central Teaching Facility Auditorium on 11th August 2025, the Academic Registrar and Acting Deputy Vice Chancellor in charge of Academic Affairs, Prof. Buyinza Mukadasi, reiterated Makerere University’s readiness to avail all the necessary support to ensure timely completion of various programmes. He underscored the contribution of research conducted by Makerere to national development priorities and urged Postgraduate students to play their role in making this influence more impactful.
Picking up from where Prof. Buyinza left off, the Director, Directorate of Graduate Training, Prof. Julius Kikooma reassured students that “Makerere University has all the resources to facilitate you through the academic journey of your graduate studies.” He equally further advised that “The Graduate Handbook is your bible that will guide you through your academic programs,” given its comprehensive reference to policies, procedures, and resources that support students during their graduate journey.

In his remarks, the Director, Prof. Robert Wamala introduced the Directorate of Research, Innovations, and Partnerships (DRIP) and outlined its role in guiding students in research. He explained DRIP’s primary functions, which include promoting and coordinating research activities, innovation and technology transfer, and overseeing research ethics and integrity. The Directorate also enhances research capacity and infrastructure, secures funding, and manages partnerships. He stressed the importance of understanding and following key university policies such as the Research and Innovations Policy and the Intellectual Property Management Policy. Prof. Wamala explained that the Intellectual Property Policy ensures that “IP created by a student in the course of study at the university, will be owned by the student,” adding that, “whatever you develop through the course of your study belongs to you and not the university.” He further encouraged students to protect their ideas and innovations through proper registration and documentation.

Dr. Godfrey Kawooya Kubiriza, from the Department of Zoology, Entomology & Fisheries at the College of Natural Sciences (CoNAS), discussed the importance of aligning research with relevant Sustainable Development Goals (SDGs) to ensure it remains current and impactful. He advised students to be cautious of peers who might negatively influence their studies and urged them to co-create with stakeholders to ensure their research has a clear impact. He also emphasized translating research evidence into policy briefs and building interdisciplinary and regional networks, encouraging connections with colleagues from East Africa, West Africa, and Europe for future collaborations and career development.
The Head ICT Division, Office of the Academic Registrar, Dr. Mike Barongo welcomed the students and underscored the importance of downloading admission letters from the portal, as these contain student numbers necessary to activate the student portal. He highlighted that enrolment is key to knowing the fees to be paid and to creating a Makerere University email address. In case of challenges, students were encouraged to seek help from college registrars or the Directorate of ICT Support. “The College of Computing has a support center at the basement of Block A, where students can get assistance,” he said.

The Deputy University Librarian, Dr. Kizito Ongaya, provided an overview of library services, noting significant changes compared to the 1990s and early 2000s. He outlined various training programs, including Reference Management Tools and Plagiarism Detection, and stressed the importance of using the available resources. “There are over 40 online libraries that we pay for. We pay over 1 billion shillings per annum to subscribe to these libraries, and you need special training so that you are able to access these,” he said. He also shared the library website, https://mulib.mak.ac.ug/ as a valuable resource.

Mr. Henry Nsubuga the Head of Counselling and Guidance Services addressed mental health and well-being, especially for PhD and Masters students, noting the significant mental toll of such programs. He pointed out that over 40% of graduate students experience depression, anxiety, and stress, and urged them to seek help early. He advised against internalizing negative feedback, suggesting instead that criticism be reframed as external rather than personal. He also encouraged positive self-talk to maintain motivation.

Ms. Diana Nabikolo, the Safeguarding Liaison Officer, briefed students on the Safeguarding Policy launched in April, which complements 11 other safeguarding policies available on the university policies website. She explained that the policy addresses various forms of abuse—physical, emotional, and neglect—as well as infrastructure-related concerns. She mentioned the presence of Safeguarding Champions in each college, both staff and students, who may assist in logging cases into the Makerere Safe Space and determining whether an issue qualifies as a safeguarding concern.

The Registrar at the Directorate of Graduate Training Ms. Caroline Nannono Jjingo explained the Directorate’s presence at all colleges and its coordination role with college and school registrars. She clarified the difference between enrolment and registration, noting that enrolment signifies acceptance of the study offer and triggers billing, while registration must follow enrolment. She also outlined the official withdrawal process, which can be prompted by financial challenges, illness, or job opportunities. Students were advised to formally notify the university to avoid being marked absent. “Withdrawal can only occur after registration,” she said, adding that students should inform the university if they plan to return.

The event was moderated by the Managing Editor Makerere University Press Dr. William Tayeebwa, who also doubles as a Senior Lecturer in the Department of Journalism and Communication, College of Humanities and Social Sciences (CHUSS). It follows a similar orientation session for undergraduate students held on 4th August 2025.
General
Application for Change of Programmes/Subjects 2025/2026
Published
2 days agoon
August 12, 2025By
Mak Editor
The Academic Registrar, Makerere University informs all intending applicants for Change of Programmes /Subjects for 2025/2026 Academic year that the deadline has been extended from Tuesday 12th August 2025 to Friday 15th August 2025.
General
Makerere University Safeguarding Champions Rise to the Occasion for Freshers!
Published
3 days agoon
August 11, 2025
As the new academic year begins, our dedicated staff and student Safeguarding Champions are stepping up to ensure that all freshers feel welcomed, safe, and supported. These committed individuals are here to guide New University Students through their university journey, offering resources, advice, and a listening ear. Together, we’re creating a vibrant and secure campus community where everyone can thrive!
Safeguarding Measures at Makerere University
“At Makerere University, we prioritise the safety and well-being of our students, staff, and the surrounding community. Our safeguarding measures include a range of policies and practices designed to prevent harm and create a secure environment. We are committed to fostering a supportive atmosphere where everyone feels safe and valued,” remarked Prof. Buyinza Mukadasi, the Deputy Vice Chancellor of Academic Affairs.
Safeguarding is about protecting people’s health, well-being and human rights, enabling them to live free from harm, abuse and neglect. Specific to Makerere University, it is the measures put in place to promote the safety and well-being of all Students, Staff and other stakeholders.

As part of the University Initiative to Improve the Safety and Wellbeing of Students and Staff, 25 Staff and 68 Student Safeguarding Champions attended an intensive refresher training on Safeguarding at Makerere University. They received information materials and planned their engagements during the University Orientation, which took place from 4th to 8th August 2025.
Orientation week is always a lively blend of excitement and nervousness for the new students. Thousands of fresh students arrive from all corners of Uganda and beyond, carrying dreams and sometimes unspoken worries.
During the 2025 Freshers’ Orientation, an Information Tent was set up at the Senate Building to assist new students, parents, and guardians with various types of information and guidance. The well-trained Student Champions, representing the 9 Colleges and 3 Schools at both the main campus and the Jinja Campus, wore white “Safeguarding Champion” T-shirts. They actively helped welcome the new students and familiarise them with the university environment.

A key emphasis was on increasing awareness of Safety and Well-being at Makerere University. In each college, the Student Safeguarding Champions were supported and guided by the Staff Safeguarding Champions. Others moved between groups of freshers, providing peer-to-peer guidance and distributing brochures with simple messages: ‘Your safety matters.’
Speaking during Orientation, Prof. Buyinza Mukadasi, the Ag. Deputy Vice Chancellor, Academic Affairs and University Academic Registrar, emphasised that the University was committed to the Safety and well-being of all University Students and Staff.
“When students know their rights and have the support systems in place, they are better positioned to thrive academically and socially. This is the kind of environment that nurtures both learning and personal growth,” Prof. Buyinza noted.

In her speech, Dr. Winfred Kabumbuli, the Dean of Students, pointed out that the Safeguarding policy included provisions for Students, Staff, and other Stakeholders, as well as the accredited Hostels and their owners.
Talking about the Champions, she mentioned that “These young leaders have taken it upon themselves to be the first line of support for their peers. Their presence is a reminder that at Makerere University, safety, respect, and inclusivity are everyone’s responsibility.”
As the semester begins, the Safeguarding Champions will continue their work by organising peer-support circles, awareness drives, and training sessions in various colleges. The University Management is urging all students and staff to have a personal responsibility of ensuring a safe, respectful and inclusive environment for all.
When discussing with the Champions, she highlighted, “These young leaders have made it their mission to be the first line of support for their peers. Their presence serves as a reminder that at Makerere University, safety, respect, and inclusivity are the responsibility of everyone.”

Addressing the student champions, Prof. Justine Namaalwa Jjumba, a member of the Safeguarding Implementation Team, urged them to lead by example in their behaviour, willingness to support other Students to identify any safeguarding risks, prevent any form of harm or abuse, report in case of any incident and support during case management.
“Let us be champions of inclusive language. We do not refer to them as ‘blind people’; we say ‘visually impaired.’ As champions, you need to be keen on identifying risks and possible causes of safeguarding concerns, report promptly, and support each other,” Prof. Namaalwa said.
The Safeguarding Liaison Officer, Ms. Diane Nabikolo Osiru, who supports monitoring the implementation and review of the Makerere University Safeguarding policy as well as coordinating activities of awareness creation and enhancement among students, staff, and partners, was at the forefront of championing awareness creation during orientation week.

Student Safeguarding Champions speak out
Mary Agnes Atim, a third-year Fine Art student, described orientation week as a valuable experience that provided a well-rounded introduction to university life for her peers.
“I have really enjoyed the orientation. As an advocate, I appreciated the opportunity to talk to fellow students about the safeguarding initiative. I’m confident that by now they know the ‘dark spots’ and will be better protected from fraudsters,” Atim said.
Edinah Kamurasi, a second-year Bachelor of Arts in Economics student, expressed gratitude for the in-depth two-day training, admitting that she had not been fully aware of the University’s safeguarding policy before.
“I am really grateful for the in-depth training we had as champions. Before this, I wasn’t even sure about the safeguarding policy, but now I can confidently explain it to others and interact with students every day, explaining the same thing. I also learnt a lot,” Kamurasi said.
Jenkins Okidi, a third-year Bachelor of Animal Production student, shared that many of the students he interacted with were enthusiastic about the MakSafeSpace, the University’s confidential e-reporting platform.
“Most freshers were excited to learn they have a safe, private way to report any concerns,” Okidi, said.

Sharifah Nalubembe, a second-year Library and Information Science student, noted that during the orientation week, she was able to guide fellow students to the appropriate offices for support.
“It felt very satisfying to help and ensure that no one ended up in the wrong hands,” Nalubembe said.
Fahad Kiyimba, a second-year Software Engineering student, described the training as highly informative in promoting the safety and wellness of students across campus.
“After the training we received as champions, I gained valuable knowledge and skills. It gave me the confidence to engage first-year students about our comprehensive safeguarding policy, and that is exactly what I did during orientation week,” Kiyimba said.
Ms. Carol Kasujja Adii is the Senior Communication Officer in charge of Safeguarding and Crisis communication at Makerere University.
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