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First Makerere Workshop on Social Systems & Computation

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15 years ago

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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.

Denis Wamala

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Makerere’s CHUSS Embraces Digital Future as RIMS Training Sparks Push for Faster Graduate Completion

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18 minutes ago

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April 17, 2026

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Participants in the hands-on RIMS training for CHUSS follow proceedings on 16th April 2026. Comprehensive Hands-on training in the Research Information Management System (RIMS) by the Directorate of Graduate Training (DGT) and Directorate for ICT Support (DICTS) for staff from School of Psychology, School of Social Sciences, School of Liberal and Performing Arts, and the School of Languages, Literature and Communication, 16th April 2026, College of Humanities and Social Sciences (CHUSS) Smart Room, Makerere University, Kampala Uganda, East Africa.

By Moses Lutaaya

KAMPALA, April 17, 2026 — The College of Humanities and Social Sciences (CHUSS) at Makerere University has taken a decisive step toward strengthening graduate training and accountability following a comprehensive hands-on Research Information Management System (RIMS) training by a team from the Directorate of Graduate Training (DGT) and Directorate for ICT Support (DICTS)  held yesterday, April 16, in the CHUSS Smart Room.

Opening the session, the Director of Graduate Training, Prof. Julius Kikooma, underscored CHUSS’s central role in producing graduate students and contributing to Uganda’s development agenda. He cautioned that the college’s leading position could easily be overtaken if vigilance wanes.

“I’m glad we are back here to focus on something that can propel CHUSS to its rightful position,” Prof. Kikooma said. “Your contribution to graduate student production is highly envied across the university, but if you sleep even briefly, that position can be taken.”

Prof. Julius Kikooma. Comprehensive Hands-on training in the Research Information Management System (RIMS) by the Directorate of Graduate Training (DGT) and Directorate for ICT Support (DICTS) for staff from School of Psychology, School of Social Sciences, School of Liberal and Performing Arts, and the School of Languages, Literature and Communication, 16th April 2026, College of Humanities and Social Sciences (CHUSS) Smart Room, Makerere University, Kampala Uganda, East Africa.
Prof. Julius Kikooma.

He emphasized that beyond competition, the real goal is national transformation. According to Prof. Kikooma, increased graduate output directly supports Uganda’s Fourth National Development Plan (NDP IV), which prioritizes building relevant human capital.

“More than ever before, the country needs human resources from the humanities and social sciences,” he noted.

Prof. Kikooma explained that the RIMS platform builds on CHUSS’ pioneering cohort-based PhD model by introducing a digital solution to track student progress, enhance supervision, and improve completion rates. The system, developed in collaboration with the Directorate for ICT Support, allows both supervisors and students to log and monitor academic activities in real time.

“This is not optional,” he stressed. “By the end of this month, we must report on who is using the system. It is a strategic priority of the University Council.”

Some of the CHUSS Staff that attended the training with Prof. Julius Kikooma (L) during the training on 16th April 2026. Comprehensive Hands-on training in the Research Information Management System (RIMS) by the Directorate of Graduate Training (DGT) and Directorate for ICT Support (DICTS) for staff from School of Psychology, School of Social Sciences, School of Liberal and Performing Arts, and the School of Languages, Literature and Communication, 16th April 2026, College of Humanities and Social Sciences (CHUSS) Smart Room, Makerere University, Kampala Uganda, East Africa.
Some of the CHUSS Staff that attended the training with Prof. Julius Kikooma (L) during the training on 16th April 2026.

Welcoming participants, the Deputy Principal of CHUSS, Assoc. Prof. Eric Awich Ochen, described the training as timely and necessary in a rapidly digitizing academic environment.

“Makerere today is very different from the Makerere of 15 or 20 years ago,” he said. “We are moving from an analogue past to a digital future.”

He noted that while the college has improved its graduate output in recent years, gaps in tracking student progress remain a concern.

“We celebrate the numbers we graduate, but we may still have many students in the pipeline whom we cannot fully account for,” he said. “This system will help us track supervision and improve accountability.”

Prof. Eric Awich Ochen. Comprehensive Hands-on training in the Research Information Management System (RIMS) by the Directorate of Graduate Training (DGT) and Directorate for ICT Support (DICTS) for staff from School of Psychology, School of Social Sciences, School of Liberal and Performing Arts, and the School of Languages, Literature and Communication, 16th April 2026, College of Humanities and Social Sciences (CHUSS) Smart Room, Makerere University, Kampala Uganda, East Africa.
Prof. Eric Awich Ochen.

The training drew participation from the CHUSS Principal and Deputy Principal, senior lecturers, lecturers, and registrars from the School of Psychology, School of Social Sciences, School of Liberal and Performing Arts, and the School of Languages, Literature and Communication.

In an interview after the session, Dr. Jim Spire Ssentongo offered a more reflective perspective, welcoming RIMS as a timely innovation while highlighting key realities in graduate training.

“I think RIMS is a good idea with strong potential,” he said, noting that the system could help address long-standing supervision gaps by ensuring that interactions between students and supervisors are tracked and visible.

However, he pointed out that delays in graduate completion are not solely the fault of supervisors. According to him, student-related factors—particularly lack of consistency and self-discipline during the research phase—play a significant role.

“At the coursework level, students are guided by timetables and structured assessments, which keeps them active,” he explained. “But once they transition to research, much depends on their own discipline. Some students simply become unresponsive.”

Dr. Ssentongo observed that RIMS could help counter this by introducing a level of accountability on both sides. If properly used, the platform would enable students to track feedback from supervisors while also making it clear when they themselves have delayed progress.

Some of the CHUSS staff that attended the RIMS training. Comprehensive Hands-on training in the Research Information Management System (RIMS) by the Directorate of Graduate Training (DGT) and Directorate for ICT Support (DICTS) for staff from School of Psychology, School of Social Sciences, School of Liberal and Performing Arts, and the School of Languages, Literature and Communication, 16th April 2026, College of Humanities and Social Sciences (CHUSS) Smart Room, Makerere University, Kampala Uganda, East Africa.
Some of the CHUSS staff that attended the RIMS training.

He also noted that the system’s monitoring aspect could encourage improved completion rates, as both supervisors and students become more conscious of timelines and expectations.

At the same time, he cautioned that implementation would be key. He explained that while systems that enhance accountability are beneficial, they must be introduced in a way that supports rather than intimidates users.

“There is an element of monitoring, which is good,” he said, “but it should be balanced so that it does not create an environment where people feel over-policed.”

Dr. Ssentongo further emphasized that RIMS should be seen as part of a broader strategy to strengthen research culture at the university. Beyond improving completion rates, he said, there is need to encourage publication, collaboration between students and supervisors, and greater visibility of research outputs.

“If it is implemented well and supported by other initiatives, it can contribute not just to completion, but also to improving research productivity and impact,” he added.

The RIMS training marks a significant step in Makerere University’s efforts to modernize graduate education, improve accountability, and align academic output with national development priorities.

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Applications for Admission to Undergraduate Programmes 2026/27

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2 hours ago

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April 17, 2026

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Students in discussion groups in Freedom Square on 1st April 2026.

The Academic Registrar, Makerere University invites applications from Ugandan, East African, and international applicants for the undergraduate programmes under the private sponsorship scheme for the 2026/2027 Academic Year for ‘A’ Level Leavers Only.

Each applicant should:

Have the Uganda Certificate of Education (UCE) with at least five (5) passes, or its equivalent and at least two (2) principal passes at Uganda Advanced Certificate of Education (UACE) obtained at the same sitting. For day programmes only candidates who sat A’ Level in 2025, 2024 and 2023 are eligible to apply. For evening, afternoon, and external programmes, a candidate is not restricted on the year of sitting A’ Level. Detailed information on the weighting system can be accessed by following this link.

Other relevant information can be obtained from UNDERGRADUATE ADMISSIONS OFFICE, LEVEL 3, SENATE BUILDING OR CAN BE found on the University Website https://www.mak.ac.ug. Effective Monday 20th April 2026. 

A non-refundable application fee of shs.50,000/= for Ugandans, East African and S. Sudan applicants or $75 or equivalent for internationals  plus bank charges should be paid in any of the banks used by Uganda Revenue Authority.                                           

 Candidates who hold grades X, Y, Z, 7 and 9 of ‘O’Level results should not apply because they are not eligible for admission. Below are the availble courses including respective fees structure.

Advert-Mak-PRIVATE-Undergraduate-ADMISSION-2026-2027Download

How to submit your application                                            

  1. Applicants should access the Institution’s Admissions URL https://apply.mak.ac.ug/
  2. Sign up by clicking on the REGISTER NOW. Use your full name, e-mail and Mobile No.  Please note that your name must be similar to the one on your supporting academic documents for your application to be considered valid.
  3. A password will be sent to you on your mobile phone and email.                                      
  4. The system will prompt you to change the password to the one you can easily remember.
  5. To fill an application form, click on the APPLY NOW button displayed on the appropriate running scheme.                                              
  6. Obtain a payment reference number by clicking on “Pay for Form” Button
  7. Make a payment at any of the banks used by Uganda Revenue Authority                                            

MOBILE MONEY PAYMENT STEPS:                                                 

  1. Dial *272*6# on either MTN or Airtel                                                             
  2. Select option 3-Admission                                                     
  3. Select option 3-Pay Fees
  4. Enter reference number obtained from Application portal 
  5. Details of Application form will be confirmed                                                              
  6. Enter PIN to confirm payment                                                            

The closing date for receiving applications shall be Friday 22nd May 2026.

WARNING:                                                             

  1. Applicants are strongly warned against presenting forged or other people’s academic documents to support their applications for admission.  The consequences, if discovered, are very grave indeed.
  2. Do not buy any other documents not originating from the Academic Registrar’s Office.  Those who buy them do so at their own risk. 
  3. The Academic Registrar has not appointed any agent to act on his behalf to solicit for additional funds other than the application fee stated above.    
  4. Applicants are advised to use the right programme names and codes. the university will not be responsible for any wrong information entered in the system by applicants.                                               

Prof. Buyinza Mukadasi
ACADEMIC REGISTRAR

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CHS Registrars, Heads of Departments Embrace RIMS as Makerere Deepens Digital Shift in Graduate Supervision

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6 hours ago

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April 17, 2026

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Participants pose for a group photo after the hands-on training in the Research Information Management System (RIMS) at the College of Health Sciences (CHS). Hands-on training in the Research Information Management System (RIMS) by the Directorate of Graduate Training (DGT) and Directorate for ICT Support (DICTS) for over 25 Heads of Departments and College Registrars from the School of Medicine, School of Biomedical Sciences, School of Health Sciences, School of Dentistry, and School of Public Health, 15th April 2026, College of Health Sciences, Mulago Campus, Makerere University, Kampala Uganda, East Africa.

By Moses Lutaaya

The College of Health Sciences (CHS) at Makerere University has taken a significant step toward strengthening graduate training and research oversight following a hands-on training in the Research Information Management System (RIMS) held on Wednesday, April 15, 2026, at the CHS premises.

The training brought together over 25 Heads of Departments and College Registrars from the School of Medicine, School of Biomedical Sciences, School of Health Sciences, School of Dentistry, and School of Public Health, in a strategic push to digitize and streamline graduate supervision.

Leading the CHS team, Associate Professor Annettee Olivia Nakimuli, Dean of the School of Medicine, described RIMS as a transformative tool that will redefine how graduate students are tracked and supported.

“RIMS is definitely the way to go. It will help us track students in real time,” she said. “We have struggled to know how well students are progressing, and sometimes we are not even sure who needs help along the way.”

Prof. Nakimuli emphasized that the system will enhance accountability on both sides of the supervision divide.

“It will facilitate supervision for both the supervisor and the student. Supervisors will be more accountable, but students too will be more accountable. At any one time, we shall know exactly what is happening between student-supervisor pairs.”

Addressing concerns about possible resistance or tension arising from increased transparency, she noted that RIMS would instead clarify longstanding challenges affecting completion rates.

The training in session. Hands-on training in the Research Information Management System (RIMS) by the Directorate of Graduate Training (DGT) and Directorate for ICT Support (DICTS) for over 25 Heads of Departments and College Registrars from the School of Medicine, School of Biomedical Sciences, School of Health Sciences, School of Dentistry, and School of Public Health, 15th April 2026, College of Health Sciences, Mulago Campus, Makerere University, Kampala Uganda, East Africa.
The training in session.

“Completion challenges are multifactorial—sometimes it is the supervisor, sometimes the student, and sometimes both. This system will make it clear where the problem is so it can be addressed,” she explained, adding that mindset change—not technical ability—remains the biggest hurdle for some staff transitioning from analog systems.

She further aligned RIMS with Makerere University’s broader agenda of becoming a research-led, graduate-focused institution.

“This is how we begin to walk the talk of being a graduate training university,” she added.

Representing the Director of Graduate Training, Mr. Nestor Mugabe underscored that RIMS is part of a larger, evolving digital ecosystem aimed at strengthening research management across the university.

“RIMS is a comprehensive system that captures the entire research process, but today we are focusing on the e-supervision component,” he said.

He noted that the system has been rolled out progressively across colleges, with CHS engagements tailored to accommodate the demanding schedules of health professionals.

“A student cannot progress if their supervisor is not on the system. That is why we are bringing everyone on board—supervisors, administrators, and students—so that the system works seamlessly,” Mugabe emphasized.

To ensure sustainability, he revealed that dedicated technical personnel have been deployed to provide on-site support.

“We now have resident technical staff who can support you directly in your offices, ensuring that no one is left behind in this transition.”

Arthur Moses Opio from DICTS was the lead trainer on RIMS. Hands-on training in the Research Information Management System (RIMS) by the Directorate of Graduate Training (DGT) and Directorate for ICT Support (DICTS) for over 25 Heads of Departments and College Registrars from the School of Medicine, School of Biomedical Sciences, School of Health Sciences, School of Dentistry, and School of Public Health, 15th April 2026, College of Health Sciences, Mulago Campus, Makerere University, Kampala Uganda, East Africa.
Arthur Moses Opio from DICTS was the lead trainer on RIMS.

From a technical standpoint, Arthur Moses Opio of the Directorate for ICT Support (DICTS) highlighted RIMS as a critical pillar in Makerere’s digital transformation journey.

“This system is about bridging the gap between supervisors and students,” he said. “It logs activities, tracks feedback, and ensures that no academic guidance is lost or disputed.”

He explained that RIMS allows students to upload research milestones—from concept notes to final theses—while enabling supervisors and examiners to engage within a transparent, traceable system.

“Before, a student could get lost in the process. Now, every comment, every revision, every step is recorded. It brings clarity and accountability.”

Opio also noted that RIMS is integrated with key university systems, including the Human Resource Management System and the Academic Management Information System (ACMIS), ensuring data consistency and institutional oversight.

CHS College Registrar Mr. Herbert Batamye welcomed the initiative, describing it as a timely intervention in addressing inefficiencies in graduate supervision.

Prof. Annettee Olivia Nakimuli, the Dean School of Medicine (L) and Mr. Herbert Batamye, the Registrar of CHS (R). Hands-on training in the Research Information Management System (RIMS) by the Directorate of Graduate Training (DGT) and Directorate for ICT Support (DICTS) for over 25 Heads of Departments and College Registrars from the School of Medicine, School of Biomedical Sciences, School of Health Sciences, School of Dentistry, and School of Public Health, 15th April 2026, College of Health Sciences, Mulago Campus, Makerere University, Kampala Uganda, East Africa.
Prof. Annettee Olivia Nakimuli, the Dean School of Medicine (L) and Mr. Herbert Batamye, the Registrar of CHS (R).

“RIMS is going to be a wonderful addition to our academic processes. It will accelerate supervision and improve efficiency if fully adopted,” he said.

He observed that the system had already received strong buy-in from participants.

“We brought together over 25 Heads of Departments and registrars, and the response has been very positive. Staff appreciate its potential.”

Mr. Batamye pointed out that one of the key strengths of RIMS is its ability to synchronize multiple supervisors on a single student’s progress.

“If a candidate has several supervisors, each will clearly see what the other is doing. It ensures that everyone is accountable and that delays are minimized.”

As Makerere University continues to digitize its academic and research processes, the CHS RIMS training signals a growing institutional commitment to improving graduate completion rates, enhancing supervision quality, and positioning research at the heart of its mission.

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