CDE4301A Ideas to Start-up<\/strong> is offered for students who are interested to pursue commercialisation of their project ideas. This two-semester course builds upon the principles of the Lean LaunchPad and the Disciplined Entrepreneurship framework to accelerate students’ understanding of the entrepreneurial process and enables further development of their ideas\/projects into viable and sustainable ventures. In the process, students will learn to identify the customer and market, develop a minimum viable product (MVP) using design and engineering skills that they have garnered throughout their undergraduate study and design a viable business model. Students will also learn the mechanics of company building, for example company formation, fund raising and intellectual property strategy. At the end of the two semesters, the students deliver an investment pitch on demo day to potential investors.<\/p>\r\n Incoming Year 4 students who are not enrolled in the Innovation & Design Programme are also welcome sign up for CDE4301 and CDE4301A, and work on projects together with their peers from different majors.<\/p>\r\n For students in Design and Engineering<\/strong> majors, CDE4301 and CDE4301A automatically fulfil the Integrated Project<\/strong> pillar in the CDE Common Curriculum regardless whether they are enrolled in the Innovation & Design Programme (those who are not enrolled in the Innovation & Design Programme as a second major may also be able to count CDE4301 towards selected specialisations in Engineering). For those in other majors<\/strong>, the courses are counted as unrestricted electives<\/strong>.<\/p>\r\n Examples of recent past projects for CDE4301 and CDE4301A may be found on the microsite of our latest EDIC Project Showcase.<\/p>\r\n EDIC Project Showcase (April 2026) <\/a><\/p>\r\n The project selection exercise will be open from 13 April 2026 until 8 May 2026<\/strong>.<\/p>\r\n Students can opt for one of the following in the project selection exercise:<\/p>\r\n Students who are interested to enroll in CDE4301 or CDE4301A submit their response via this project selection form<\/strong>:<\/p>\r\n Link to online project selection form <\/a><\/p>\r\n We have a diverse range of projects that are offered by our faculty members and industry partners. They are grouped into a number of broad themes below. Students can contact the project supervisors to find out more about each project.<\/p>\r\n In the online project selection form, students can choose up to 5 projects<\/strong> and rank them in order of preference<\/strong>.<\/p>\r\n Designing a light weight solar power marine craft<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisors: Dr Tang Kok Zuea<\/strong>\u00a0<\/b>(kz.tang@nus.edu.sg<\/a>), A\/Prof Martin Henz <\/b>(henz@nus.edu.sg<\/a>)<\/p>\r\n The Solar Proa<\/a> design concept is highly regular and modular, which makes it ideally suitable for parametric design. It is regular in that the boat is symmetric about a transversal axis, the solar panels are arranged in two rectangles, and most dimensions follow from a small number of parameters such as LOA and the number and size of the solar panels. It is modular in that the main design components – hull, rig, crossbeams, electrical system – are functionally independent, which allows their validation to be mapped directly onto separate stages in the framework.<\/p>\r\n In this project, students will design and make components to realise a small craft using the Solar Proa design.<\/p>\r\n FSAE dynamometer<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisors: Mr Lim Hong Wee<\/strong>\u00a0<\/b>(hongwee@nus.edu.sg<\/a>), Mr Kenneth Neo<\/b> (kenneth@nus.edu.sg<\/a>)<\/p>\r\n The NUS Formula SAE (FSAE) team is looking for an individual wheel dynamometer to test their 80kW race vehicle. Students will need to spec components suitable for the use case and design and prototype the dynamometer. The race car will be used to test the dynamometer. The work involves building electrical circuits, designing the frame, mounting and integration to the race car safely. Work will be distributed according to the core knowledge of the student.<\/p>\r\n FSAE race car simulator<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisors: Mr Lim Hong Wee<\/strong>\u00a0<\/b>(hongwee@nus.edu.sg<\/a>), Mr Kenneth Neo<\/strong> (kenneth@nus.edu.sg<\/a>)<\/p>\r\n Join the team to create a racing simulator for the FSAE team! This simulator is not the ordinary game for leisure. It is a game with full physics of the race car design by the team, and it will be used for drivers’ training for different events in the competition. The simulator will be tweaked with data collected with actual race car to be as real as possible.<\/p>\r\n There are many different aspect that students can work on:<\/p>\r\n Red Dot Mobility electric mobility<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: Mr Lim Hong Wee<\/strong>\u00a0<\/b>(hongwee@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: Red Dot Mobility<\/p>\r\n Red Dot Mobility (https:\/\/reddotmobility.com\/<\/a>) is a local company creating electric mobility vehicles from 2 to 4 wheelers. They have projects in the following category:<\/p>\r\n The project can be customised according to the students’ primary major and interest.<\/p>\r\n AI-assisted medication code recognition for automated pharmacy dispensing<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisors: Dr Tang Kok Zuea<\/strong> (kz.tang@nus.edu.sg<\/a>), Mr Keith Tan<\/strong> (keithtcy@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: National University Hospital (NUH)<\/p>\r\n NUH Pharmacy operates ROWA automated dispensing systems, which rely on accurate barcode or QR code scanning when medications are loaded for dispensing. In real-world settings, pharmaceutical packaging typically contains multiple codes on a single box, such as manufacturer identifiers, batch numbers, expiry dates, regulatory markings, and pharmacy-specific labels.<\/p>\r\n A key challenge arises because the ROWA barcode scanning system is unable to reliably decipher and select the correct code when multiple codes are present on the same package. As a result, pharmacy staff must intervene manually to identify and scan the appropriate code required by ROWA. This manual intervention introduces significant workflow bottlenecks and diverts skilled pharmacy personnel away from higher-value clinical and operational activities. Given the volume and variety of medications processed daily, these inefficiencies have a substantial impact on overall pharmacy productivity and throughput.<\/p>\r\n To develop an AI-assisted medication code recognition solution that enhances the ROWA medication loading process by accurately identifying and selecting the correct barcode or QR code from pharmaceutical packaging.<\/p>\r\n AI & Computer Vision Exploration:<\/p>\r\n Professional & Industry Skills:<\/p>\r\n Automated inspection of opthalmic surgical tools<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: Mr Nicholas Chew<\/strong> (nick.chew@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: Singapore National Eye Centre<\/p>\r\n This project continues the development of an automated visual inspection system for ophthalmic surgical tools, building on the foundational work established by the previous batch of final year engineering students.<\/p>\r\n The existing system leverages a Keyence smart camera integrated with a custom-developed user interface, and employs a YOLO-based object detection model trained on a dataset of ophthalmic instruments. While this represents a solid baseline, significant enhancements remain to be explored and implemented.<\/p>\r\n The incoming team will focus on three key areas of development. First, advancing the machine learning pipeline by exploring and benchmarking more sophisticated detection architectures – specifically DETR (Detection Transformer) and Mask R-CNN – against the current YOLO implementation, with the goal of improving detection accuracy and robustness across varying tool geometries and surface conditions. Second, expanding the inspection coverage to address a critical limitation of the current setup: the inability to detect defects on the back surface of tools. Solutions may involve multi-camera configurations, mirror-assisted imaging, or robotic repositioning mechanisms. Third, consolidating these improvements into a reliable, production-ready inspection system with refined UI workflows and systematic validation protocols.<\/p>\r\n This project is well-suited for students with interests in computer vision, deep learning, and mechatronics, and offers the opportunity to work on a practical, high-impact application in the medical device domain.<\/p>\r\n Development of an AI-powered system for senior wellbeing<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisors: A\/Prof Lim Li Hong Idris<\/strong> (lhi.lim@nus.edu.sg<\/a>), Dr Kate Sangwon Lee<\/strong> (katelee@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: Imperial College London<\/p>\r\n The rapid advancement of AI presents a transformative opportunity to address the growing wellbeing needs of senior citizens. This project proposes the development of an AI-powered system designed to support the wellbeing of older adults in both home and care settings. The system will leverage natural language processing and adaptive learning to provide personalised companionship, health monitoring reminders, cognitive engagement activities, and seamless communication with caregivers and family members. By centering the design process around the lived experiences of seniors, the project aims to produce an accessible, ethical, and empathetic AI solution that enhances quality of life, promotes independence, and reduces the burden on formal and informal care systems.<\/p>\r\n Objectives:<\/p>\r\n Fabric-based wearables for intelligent clinical applications using AI<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: Dr Tang Kok Zuea<\/strong> (kz.tang@nus.edu.sg<\/a>)<\/p>\r\n Continuous monitoring of vital signs is essential for early detection of health deterioration, chronic disease management, and preventive care. Conventional wearable devices often rely on rigid electronics and discrete sensors, which may cause discomfort, limit wearability, and reduce long-term user compliance. This project aims to develop a fabric-based wearable system that can be integrated into garments to enable comfortable, unobtrusive, and continuous monitoring of vital physiological signals using AI.<\/p>\r\n Improving unit dose medication repackaging through workflow design and assistive technologies<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisors: Dr Tang Kok Zuea<\/strong> (kz.tang@nus.edu.sg<\/a>), Mr Soh Eng Keng<\/strong> (ek.soh@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: National University Hospital (NUH)<\/p>\r\n The National University Hospital (NUH) inpatient pharmacy operates a closed loop medication management system that supports medication safety and traceability through unit dose repackaging and barcode enabled administration. A key part of this system involves pharmacy technicians manually converting medications into unit doses by cutting blister strips, separating capsules, relabelling ampoules, and repackaging bulk medications from bottles or multi dose containers.<\/p>\r\n These tasks require repetitive manual handling, precision, and adherence to strict hygiene and safety standards. The predominantly manual workflow constrains throughput, introduces variability in packaging quality, and places high physical and cognitive demands on staff. Rather than fully automating this process, there is an opportunity to redesign workflows and introduce specially designed devices or enabling technologies that enhance productivity, consistency, and ergonomics while preserving human oversight and control.<\/p>\r\n To design and prototype workflow enhancements and productivity enabling devices or technologies that assist pharmacy technicians in safely and accurately converting pharmaceutical packaging into unit dose formats.<\/p>\r\n Innovation for community care apartments<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisors: A\/Prof Lim Li Hong Idris<\/strong> (lhi.lim@nus.edu.sg<\/a>), Dr Kate Sangwon Lee<\/strong> (katelee@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: Vanguard Assisted Living (Harmony Village@ Bukit Batok)<\/p>\r\n Harmony Village’s community care apartments represent an innovative housing model where HDB-owned apartments are leased to seniors, with shared communal facilities including meeting rooms, coffee lounges, exercise areas, and gardens. Vanguard Assisted Living’s Community-Based Care Model brings care directly to residents’ homes through preventive care, social participation, housing support, custodial care, caregiver support, and building a sense of purpose. The goal: enable seniors to age-in-place in their own homes, with dignity and appropriate care. As the senior population grows, Vanguard Assisted Living has identified seven critical challenges requiring innovative, practical, and human-centred solutions:<\/p>\r\n In a team, you will develop a solution to one or more of the problems above, to enable the seniors to age with dignity.<\/p>\r\n Intelligent linen inspection and workflow redesign for hospital operations<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisors: Dr Tang Kok Zuea<\/strong> (kz.tang@nus.edu.sg<\/a>), Mr Soh Eng Keng<\/strong> (ek.soh@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: National University Hospital (NUH)<\/p>\r\n The NUH Group Hospitality (GH) manages hospital linen operations, including patient pyjamas and other textile items that must meet strict hygiene and quality standards. Currently, patient pyjamas undergo 100% manual inspection for defects such as stains, fabric tears or pinholes, discolouration, odour or moisture, and missing buttons, followed by folding and packaging.<\/p>\r\n These inspection processes are highly labour intensive, time consuming, and dependent on individual judgement, resulting in inconsistent quality and extended turnaround times. With increasing patient volumes and healthcare expansion, manual inspection has become a key operational bottleneck. There is a growing need to explore technology enabled inspection and workflow improvements that can improve inspection accuracy, consistency, and throughput while supporting workforce sustainability and maintaining hygiene standards.<\/p>\r\n This project aims to design and prototype a technology enabled linen inspection solution, together with a redesigned operational workflow, that enhances the efficiency and consistency of hospital linen quality checks.<\/p>\r\n Intelligent surgical tools checking using robotics and AI<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: Dr Tang Kok Zuea<\/strong> (kz.tang@nus.edu.sg<\/a>)<\/p>\r\n In a typical hospital, the instrument processing department may handle up to 900 surgical trays per day, creating a high potential for human error in inventory and surgical set preparation. The high demand in volume, combined with the visual similarity between many surgical tools, makes manual verification error-prone. This leads to frequent cases of missing instruments and incomplete surgical sets in operating theatres, resulting in workflow disruption, surgical delays, and increased stress for staff. To address this issue, this project explores the development of an intelligent scanning system that uses robotics and AI to detect, verify, and evaluate surgical tools. The system is designed to compare each scanned tool against a reference set, automatically flagging missing or incorrect instruments before the tools are packed.<\/p>\r\n Technology-enabled medication verification system for drug dispensing machine<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisors: Dr Tang Kok Zuea<\/strong> (kz.tang@nus.edu.sg<\/a>), Mr Soh Eng Keng<\/strong> (ek.soh@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: National University Hospital (NUH)<\/p>\r\n The National University Hospital (NUH) pharmacy operates Drug Dispensing System (DDS) machines that require manual medication loading by pharmacy staff, followed by a mandatory verification step performed by a second staff member to ensure the correct medication is placed in the appropriate drawer. While this dual staff verification process is essential for medication safety, it creates significant manpower bottlenecks-especially when DDS machines trigger low stock alerts that require replenishment.<\/p>\r\n Given rising patient volumes and staffing constraints in Singapore’s healthcare sector, there is a strong need to improve the efficiency and responsiveness of medication replenishment workflows without compromising medication safety or regulatory compliance.<\/p>\r\n This project aims to design and prototype a technology enabled medication verification solution that reduces or eliminates the need for dual staff involvement during DDS machine replenishment. The solution should achieve the following goals:<\/p>\r\n Through this project, students can expect to:<\/p>\r\n WearBP: a wearable system for continuous bood pressure monitoring in daily life<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: Dr Cai Shaoyu<\/strong> (shao.cai@nus.edu.sg<\/a>)<\/p>\r\n Blood pressure is one of the most important indicators of cardiovascular health, but current monitoring methods have clear limitations:<\/p>\r\n There is therefore a strong need for a wearable blood pressure monitoring system that is comfortable, practical, and capable of supporting regular or continuous measurement in daily life.<\/p>\r\n AI conversation coach for nursing communication training<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: A\/Prof Khoo Eng Tat <\/strong>(etkhoo@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: National University Hospital (NUH)<\/p>\r\n Traditional communication training at NUH relies heavily on in person workshops and role play, which are resource intensive, limited in frequency, and inconsistent across learners. Nurses are facing increasingly complex patient and family interactions, requiring more scalable and repeatable practice opportunities to build confidence and competence. The purpose of this project is to transform nursing communication training through an AI powered platform that enables nurses to practice difficult conversations – such as breaking bad news, serious illness discussions, behavioural coaching, and emotional distress counselling – in a safe, structured, and repeatable digital environment.<\/p>\r\n This project aims to provide an AI conversation coach that simulates realistic patient and family interactions.<\/p>\r\n Students in this project may design and develop one or more of the following scopes:<\/p>\r\n AI simulated patient for dentistry student communication training in VR<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: A\/Prof Khoo Eng Tat <\/b>(etkhoo@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: NUS Faculty of Dentistry<\/p>\r\n Effective communication is crucial in dentistry for patient care and treatment success. However, many dentistry students face challenges in developing communication skills due to limited opportunities for practice with real patients. To address this, we propose the development of an AI Simulated Patient system tailored for dentistry student communication training. This project integrates emerging technologies including generative AI (Gen-AI), Large Language Models (LLM), and Virtual Reality (VR) to create realistic simulated patient interactions.<\/p>\r\n Students in this project may design and develop one or more of the following scopes:<\/p>\r\n The project will be supervised by Associate Professor Khoo Eng Tat and supported by the research fellow and engineers from the Immersive Reality Lab. It will be carried out in collaboration with Associate Professor Wong Mun Loke from the NUS Faculty of Dentistry. Example of immersive reality (VR\/MR) and generative AI (Gen-AI) student projects completed under Immersive Reality Lab can be found on the website https:\/\/cde.nus.edu.sg\/edic\/projects\/innovating-with-immersive-reality\/<\/a>.<\/p>\r\n AquaSenseXR: multisensory wearable interfaces for embodied ocean exploration<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: Dr Cai Shaoyu<\/b> (shaoyucai@nus.edu.sg<\/a>)<\/p>\r\n AquaSenseXR proposes a wearable multisensory system that integrates haptic feedback (thermal, vibrotactile, pressure) with physiological sensing (HR, EDA, respiration) to create an embodied ocean exploration experience. Users navigate underwater environments in VR while their physiological states dynamically modulate environmental responses (e.g., water currents, visibility, marine life behavior). The system investigates closed-loop human-environment coupling, where ocean conditions influence bodily perception, and users’ internal states reshape the virtual ecosystem.<\/p>\r\n AromaOcean: multisensory olfactory-haptic interfaces for marine environment simulation<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: Dr Cai Shaoyu<\/b> (shaoyucai@nus.edu.sg<\/a>)<\/p>\r\n Building on your olfactory interface work, AromaOcean integrates scent (salinity, algae, seafood), thermal cues, and airflow to recreate marine environments. Combined with VR visuals and haptics, users can experience different ocean zones (reef, deep sea, coastal). The system explores how olfactory-thermal-tactile integration enhances realism and memory in immersive environments.<\/p>\r\n Future frontiers: GenAI and immersive reality<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: A\/Prof Khoo Eng Tat <\/b>(etkhoo@nus.edu.sg<\/a>)<\/p>\r\n This project is dedicated to pushing the boundaries of immersive technologies, generative AI, and large language models (LLMs). Students can explore how these technologies can be integrated to transform VR\/AR simulation systems used in sectors like medical education, aviation training, and elderly care. Students will investigate the current limitations of immersive systems, design novel solutions to enhance realism, interactivity, and usability, and pioneer new use cases. A key emphasis will be placed on user experience (UX) design, real-time AI-driven feedback, and human-AI interaction.<\/p>\r\n Students joining this project will have the flexibility to either select from a curated list of project topics or propose their own ideas that align with the studio’s themes. Under the guidance of A\/Prof Khoo Eng Tat and the Immersive Reality Lab team, students will work closely with industry partners to develop real-world solutions that innovate beyond today’s capabilities.<\/p>\r\n Proposed areas of exploration:<\/p>\r\n Problem statements (students may choose or propose their own):<\/p>\r\n Gen-AI and VR-based full-body dance sensing and choreography optimisation<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: A\/Prof Khoo Eng Tat <\/b>(etkhoo@nus.edu.sg<\/a>)<\/p>\r\n Advancements in full-body motion sensing and generative AI are opening new frontiers in the art and science of dance. Traditional dance practice often relies on repetitive rehearsals and instructor feedback, but dancers face challenges in achieving precise technique refinement and exploring creative movement variations.<\/p>\r\n This project aims to create an innovative system that integrates VR-based immersive full-body tracking with Generative AI-driven choreography. The goal is to empower dancers to train anywhere, receive real-time, AI-guided feedback, and collaborate with AI to generate new, optimized choreography. By blending immersive reality and creative AI generation, the project envisions a future where human dancers and AI co-create, enhance technical mastery, and expand artistic boundaries.<\/p>\r\n We will collaborate with student dance groups to collect real-world motion data and evaluate the system’s impact on choreography development and learning outcomes.<\/p>\r\n Students participating in this project can choose to contribute to one or more areas, including:<\/p>\r\n Gen-AI and VR simulations to improve nursing students’ clinical reasoning and interprofessional communication skills<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: A\/Prof Khoo Eng Tat <\/b>(etkhoo@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: NUS Alice Lee Centre for Nursing Studies<\/p>\r\n A study by Goodman et al. (2023) demonstrated that the accuracy and completeness of generative artificial intelligence (Gen-AI) chatbot responses to diverse medical question types and difficulties were rated high by physicians. Integrating Gen AI and virtual reality (VR) simulations in nursing education have tremendous potential of enhancing clinical reasoning and interprofessional communication skills for the nursing students. These technologies provide immersive, realistic, and scalable training solutions that bridge the gap between classroom learning and real-world clinical practice.<\/p>\r\n Students in this project will design and develop Gen-AI agents and multiusers VR simulation to improve nursing students’ clinical reasoning and interprofessional communication skills. User study will be employed to test the feasibility of the Gen-AI powered VR simulation. Accuracy and ethical aspects of Gen-AI may also be explored, including strategy on fine tuning LLMs with nursing domain specific content.<\/p>\r\n The project will be supervised by Associate Professor Khoo Eng Tat and supported by the research fellow and engineers from the Immersive Reality Lab. It will be carried out in collaboration with Professor Liaw Sok Ying from the Alice Lee Centre for Nursing Studies (NUS Nursing), NUS Yong Loo Lin School of Medicine. Example of immersive reality (VR\/MR) and generative AI (Gen-AI) student projects completed under Immersive Reality Lab can be found on the website https:\/\/cde.nus.edu.sg\/edic\/projects\/innovating-with-immersive-reality\/<\/a>.<\/p>\r\n Generative AI human: emotion simulation and emotional sensing for intelligent agents<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: A\/Prof Khoo Eng Tat <\/b>(etkhoo@nus.edu.sg<\/a>)<\/p>\r\n As human-AI interaction becomes more pervasive in industries such as healthcare, customer service, and aviation, the ability for AI agents to simulate and respond to human emotions will be critical for realism, effectiveness, and empathy. This project, Generative AI Human, explores the creation of AI-driven virtual agents capable of both simulating human-like emotional expressions (e.g., anger, frustration, compassion) and detecting the emotional states of users to adapt their responses accordingly.<\/p>\r\n Students will work on two intertwined challenges:<\/p>\r\n Develop intelligent agents that can generate nuanced emotional behaviours, such as anger or impatience, critical for realistic training scenarios (e.g., angry customer simulations for service training, distressed patient simulations for medical training). This includes voice tone modulation, facial expression animation, and contextual behaviour adaptation using generative AI and LLM-based techniques.<\/p>\r\n Implement systems capable of detecting user emotions through computer vision (facial recognition), audio analysis (speech tone\/sentiment), or physiological data. These insights can be fed back into the agent’s behaviour to create a dynamic two-way emotional interaction.<\/p>\r\n Students will have the opportunity to contribute to both technical development (e.g., building emotion models, integrating sensing technology) and user experience design (e.g., ensuring the interaction feels natural and realistic). Applications range from customer service training simulations to healthcare communication skills education.<\/p>\r\n Possible areas of focus (students may specialize based on interest):<\/p>\r\n Potential use cases:<\/p>\r\n HapticNet: learning-based haptic rendering models<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: Dr Cai Shaoyu<\/b> (shaoyucai@nus.edu.sg<\/a>)<\/p>\r\n This project uses machine learning to map input signals (visual\/audio\/physics data) to optimal haptic outputs, replacing hand-designed mappings. The proposed method can support data-driven haptic synthesis, personalisation of haptic feedback Project supervisor: Dr Cai Shaoyu<\/b> (shaoyucai@nus.edu.sg<\/a>)<\/p>\r\n Building on liquid-metal sensing, this project develops a thin, flexible wearable skin capable of decoding continuous touch position and force at high resolution. The system enables expressive interaction (e.g., drawing, pressure-based control) on deformable surfaces.<\/p>\r\n The contribution mainly covers:<\/p>\r\n Immersive VR\/MR childbirth delivery simulation<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: A\/Prof Khoo Eng Tat <\/b>(etkhoo@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: NUS Yong Loo Lin School of Medicine<\/p>\r\n This project aims to revolutionize obstetrics and gynaecology (O&G) childbirth delivery training using immersive simulation by transforming how medical professionals learn and acquire competency in birth delivery procedures. Our innovative Virtual Reality (VR) and Mixed Reality (MR) Birth Delivery Training platform offers an unparalleled opportunity for medical students to immerse themselves in realistic and interactive simulations of childbirth scenarios.<\/p>\r\n Students in this project will design and develop new training scenario for O&G doctors, medical students, mid-wives and nursing students. Students will gain exposure to immersive reality technology and generative AI using large language model to create a dynamic training environment\/procedures and AI patient that mirrors real-life obstetric situations. They will carry out research with medical faculty and students, gain hands on experience in VR\/MR and generative AI (Gen-AI) development, and perform user study to validate the efficacy of the simulations.<\/p>\r\n The project will be supervised by Associate Professor Khoo Eng Tat and supported by the research fellow and engineers from the Immersive Reality Lab. It will be carried out in collaboration with Assistant Professor Gosavi Arundhati Tushar from the Department of Obstetrics & Gynaecology, NUS Yong Loo Lin School of Medicine. Example of immersive reality (VR\/MR) and generative AI (Gen-AI) student projects completed under Immersive Reality Lab can be found on the website https:\/\/cde.nus.edu.sg\/edic\/projects\/innovating-with-immersive-reality\/<\/a>.<\/p>\r\n Multisensory tangible interfaces for inclusive cultural heritage experience<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: Dr Cai Shaoyu<\/b> (shaoyucai@nus.edu.sg<\/a>)<\/p>\r\n The project will design and develop a system of interactive tangible artefacts – 3D-printed replicas embedded with electronics, that allow users to touch, grasp, and explore heritage objects through integrated haptic, auditory, and visual feedback. By leveraging wearable sensing and haptic technologies, the system aims to support both sighted and visually impaired users, enabling deeper cultural understanding through embodied interaction and multisensory storytelling.<\/p>\r\n BoxBunny<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisors: Mr Graham Zhu<\/b> (graham.zhu@nus.edu.sg<\/a>), Mr Royston Shieh<\/strong> (shiehtw@nus.edu.sg<\/a>)<\/p>\r\n Float like a butterfly, sting like a bee \ud83e\udd4a<\/p>\r\n Meet BoxBunny – an intelligent boxing robot designed to make high-quality boxing training accessible, interactive, and fun. Imagine training with a smart sparring partner that adapts to your skill level, tracks your progress, and helps you improve step by step – just like a real coach.<\/p>\r\n Over the past 2 years, BoxBunny has evolved through multiple iterations, and we’re now taking it to the next level-towards a professional, real-world product. This is your chance to be part of that journey.<\/p>\r\n By joining this project, you won’t just build a robot – you’ll gain hands-on experience across multiple cutting-edge domains, including:<\/p>\r\n If you enjoy building, experimenting, and pushing ideas into reality, this project will challenge you, grow your skills, and let you work on something truly exciting and impactful.<\/p>\r\n Step into the ring with BoxBunny – and help shape the future of smart training. \ud83d\ude80<\/p>\r\n Design of a box orientation mechanism for conveyor<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: Mr Soh Eng Keng\u00a0<\/b>(ek.soh@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: CEVA Logistics<\/p>\r\n Value-added-services (VAS) operations often require product boxes to be reoriented on a conveyor from a flat laying position to an upright standing position for downstream processes such as packing. Current operations rely on manual intervention by operators to reorient items, which limits productivity and consistency.<\/p>\r\n This project aims to design a minimalist, space-efficient, and flexible mechanical solution capable of reliably flipping product boxes from a laying position to a standing position while they are moving on a conveyor. The design should accommodate a wide range of box sizes with minimal adjustment and be easily integrated into existing conveyor systems without major modifications. The solution should prioritize simplicity, reliability, ease of utilization, and operational robustness.<\/p>\r\n Expected outcomes include a functional design concept and prototype of the orientation mechanism, mechanical design and component selection, adaptability features for different SKU dimensions, and integration considerations for existing conveyor lines. Documentation will describe the design, operating principles, testing results, and an adjustment SOP for operations.<\/p>\r\n Development of an automated box forming machine<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: Mr Soh Eng Keng\u00a0<\/b>(ek.soh@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: CEVA Logistics<\/p>\r\n Value-added-services (VAS)\u00a0operations require flexible packaging solutions to support varying product types. Currently, box forming from flat cartons to fully erected boxes is a fully manual process, which is labor-intensive and can become a bottleneck in packing operations.<\/p>\r\n This project aims to design and implement a compact, movable automated box forming machine capable of folding flat cartons into fully formed boxes. The solution should improve operational efficiency, ergonomics, and consistency while retaining flexibility for redeployment across different production lines. A mobile design enables shared use across multiple processes without permanent installation.<\/p>\r\n The system should reliably handle defined box formats, perform controlled folding and forming operations, and operate safely in an industrial environment. Expected outcomes include a working prototype suitable for VAS applications, mechanical design and actuation concepts for box folding, a control system implementation (PLC or embedded controller), and appropriate safety features.<\/p>\r\n Development of an automated plastic bag dispensing and opening machine<\/a> Expand<\/i><\/a><\/p>\r\n Project supervisor: Mr Soh Eng Keng\u00a0<\/b>(ek.soh@nus.edu.sg<\/a>)<\/p>\r\n Industry partner\/collaborator: CEVA Logistics<\/p>\r\n In value-added-services operations, operators perform repetitive manual tasks such as separating, opening, and preparing plastic bags for product insertion. These tasks are time-consuming, ergonomically demanding, and prone to inconsistency, which can reduce throughput and increase operator fatigue. In many conveyor-based workflows, manual bag preparation creates operational bottlenecks.<\/p>\r\n This project aims to design and implement an automated machine capable of dispensing and opening plastic bags from a stacked pile, presenting each bag in a ready-to-use position for an operator. After the operator inserts the product into the opened bag and places it onto the conveyor, the system should automatically prepare the next bag for insertion.<\/p>\r\n Students will conduct requirements definition and concept evaluation, develop the mechanical design for reliable bag separation and opening, select appropriate actuators, sensors, and control hardware, and implement control logic for coordinated operation. A functional prototype will be fabricated and tested to demonstrate reliable bag handling and smooth integration into an existing conveyor workflow.<\/p>\r\n Development of an autonomous ground-effect vehicle for runway inspection<\/a> Expand<\/i><\/a><\/p>\r\nCDE4301\/CDE4301A project selection exercise<\/h3>\r\n
\r\n
Staff\/Industry-proposed projects for CDE4301<\/h3>\r\n
Innovating for Future Mobility<\/h4>\r\n
\r\n
\r\n
Innovating for Healthcare and Wellbeing<\/h4>\r\n
Project aim<\/h4>\r\n
Possible project scope and learning opportunities<\/h4>\r\n
\r\n
\r\n
![\"\"](\"https:\/\/cde.nus.edu.sg\/edic\/wp-content\/uploads\/sites\/37\/2024\/10\/EG3301R-Roboscan-1024x576.png\")
<\/p>\r\n\r\n
![\"\"](\"https:\/\/cde.nus.edu.sg\/edic\/wp-content\/uploads\/sites\/37\/2026\/04\/CDE4301-2026-AI-senior-wellbeing-1024x572.jpeg\")
<\/p>\r\n![\"\"](\"https:\/\/cde.nus.edu.sg\/edic\/wp-content\/uploads\/sites\/37\/2026\/04\/CDE4301-2026-fabric-wearables.jpg\")
<\/p>\r\nProject aim<\/h4>\r\n
Possible project scope and learning opportunities<\/h4>\r\n
\r\n
\r\n
![\"\"](\"https:\/\/cde.nus.edu.sg\/edic\/wp-content\/uploads\/sites\/37\/2026\/04\/CDE4301-2026-community-care-768x1024.jpg\")
<\/p>\r\nProject aim<\/h4>\r\n
Possible project scope and learning opportunities<\/h4>\r\n
\r\n
![\"\"](\"https:\/\/cde.nus.edu.sg\/edic\/wp-content\/uploads\/sites\/37\/2026\/04\/CDE4301-2026-surgical-tools.jpg\")
<\/p>\r\n\r\n
\r\n
\r\n
Innovating with Immersive Reality<\/h4>\r\n
\r\n
\r\n
\r\n
\r\n
\r\n
Simulating emotions in AI agents<\/h4>\r\n
Emotional detection and feedback loop<\/h4>\r\n
\r\n
\r\n
and generalisable across devices. HapticSkin+: super-resolution wearable tactile interfaces for continuous interaction<\/a> Expand<\/i><\/a><\/p>\r\n\r\n
Innovations in Intelligent Systems<\/h4>\r\n
\r\n
![\"\"](\"https:\/\/cde.nus.edu.sg\/edic\/wp-content\/uploads\/sites\/37\/2026\/03\/IS-431-BoxBunny-1024x576.png\")
<\/p>\r\n![\"\"](\"https:\/\/cde.nus.edu.sg\/edic\/wp-content\/uploads\/sites\/37\/2026\/04\/CDE4301-2026-box-conveyer.png\")
<\/p>\r\n![\"\"](\"https:\/\/cde.nus.edu.sg\/edic\/wp-content\/uploads\/sites\/37\/2026\/04\/CDE4301-2026-box-forming.png\")
<\/p>\r\n![\"\"](\"https:\/\/cde.nus.edu.sg\/edic\/wp-content\/uploads\/sites\/37\/2026\/04\/CDE4301-2026-plastic-bags.png\")
<\/p>\r\n