Research Assistant Professorship (RAP)

The Research Assistant Professorship (RAP) scheme aims to attract early career researchers focusing on research in particularly competitive areas. The RAP recipients must be sought after and of the highest rank. They are expected to bring special skills and expertise to NTU.

Hiring Criteria​​

  • RAP scheme targets Research Fellows within 4 years of obtaining PhD. or equivalent degree in competitive research areas
  • RAP recipients must sought after and of the highest rank.
  • Staff hired as Non-Faculty and Grant-Based RAPs are under the Research Staff scheme.
  • The recipient’s formal position is as a Research Fellow/Senior Research Fellow within the NTU Research Staff Scheme with a fixed term of 2-3 years contingent upon the availability of external competitive research grants from their NTU mentor. Direct top-up from Schools, Colleges or University budgets are not allowed.
  • During their appointment period, the recipient may use the title Research Assistant Professor.
  • RAP recipient does not provide a direct pathway to an academic position at NTU.
  • Salary range is competitive and will be based on the market rate.

Application Process

  • The RAP Call is currently open for applications till 10th Dec 2021.
  • Application is by nomination by potential mentor only.
  • Candidates interested to apply for the RAP scheme are required to contact their potential mentor (i.e. NTU Faculty) and work with the potential mentor in preparing their application package.
  • Required documents for submission includes indication of interest from potential mentor, CV and research proposal of the RAP candidates.

 Queries can be directed at rap@ntu.edu.sg

Contact

rap@ntu.edu.sg

 

 

 

​​​Awardees​

Feng Kaiyu

Feng Kaiyu 

Project Title: Deep Learning for Big Spatial Data Management
Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU) ​

 

Kaiyu Feng is currently a Research Assistant Professor in the School of Computer Science and Engineering (SCSE) at the Nanyang Technological University (NTU), Singapore. He obtained his PhD degree in computer science from NTU in 2018, under the supervision of Professor Cong Gao. His research interests include spatial database management and graph database. He is particularly interested in querying geo-taged data stream, spatial data visualization, efficient processing of spatial queries and graph and social data analysis. He has published  papers in premium venues in these areas such as SIGMOD, VLDB, ICDE, WWW, and the IEEE Transactions on Knowledge and Data Engineering.

RAP - Ng Wei Long

Ng Wei Long

Project Title: Biofabrication of Human Skin Tissue Models using 3D Bioprinting Approaches​​
HP-NTU Digital Manufacturing Corporate Lab​
Email: ng.wl@ntu.edu.sg

 

Ng Wei Long is a Research Assistant Professor at HP-NTU Digital Manufacturing Corporate Lab, and his current research focuses on the bioprinting of 3D human-based tissue models. Wei Long was awarded the A*STAR Graduate Scholarship (AGS) in year 2013 to pursue his Ph.D. on skin bioprinting under the supervision of Dr May Win Naing (SIMTech, A*STAR) and Assistant Professor Yeong Wai Yee (School of Mechanical and Aerospace Engineering (MAE), NTU). As a Ph.D. candidate, his key research is on developing of novel bio-inks and engineering functional microenvironment for 3D bioprinted in-vitro human tissue models. After his Ph.D., he worked as a Research Fellow under the supervision of Professor Chua Chee Kai at the Singapore Centre of 3D Printing (SC3DP) and then subsequently under the supervision of Associate Professor Yeong Wai Yee at HP-NTU Digital Manufacturing Corporate Lab. In August 2020, Wei Long took on his new appointment as a Research Assistant Professor to continue his research on 3D bioprinting of human-based tissue models.​


RAP - Cao Yixin

Cao Yi Xin

Project Title: Fine-grained Domain Knowledge Acquisition with Limited Supervision​​​
S-Lab for Advanced Intelligence
Previous affiliation: PhD (Computer Science), National University of Singapore, 2018 
Email: yixin.cao@ntu.edu.sg

 

Cao Yixin was a research fellow with NExT++, National University of Singapore (NUS). He received his Ph.D. in Computer Science from Tsinghua University in 2018​. His research interests span natural language processing, knowledge graph and recommendation. Various part of his works has been published in top conferences, such as ACL, EMNLP, COLING and WWW. Cao Yi Xin has also served as PC member for several conferences including ACL, EMNLP, NAACL, AAAI, IJCAI, and NeurIPs, and as reviewers for journals including TKDE, TKDD, TASLP and IEEE Access.

RAP - Bo Dai

Bo Dai

Project Title: Beyond Visual Perception: Towards Multi-Modality Perception and Imagination ​​​
S-Lab for Advanced Intelligence
Previous affiliation: PhD (Information Engineering), The Chinese University of Hong Kong, 2018
Email: bo.dai@ntu.edu.sg

 

Dai Bo was a research fellow (2018-2020) in MMLab@CUHK. His research interests include computer vision and machine learning. Recently, his research focus is on generative models, video analysis, and cross-modality analysis. He received his PhD (2014-2018) from CUHK. He obtained his BEng (2010-2014) from ACM class of SJTU. Previously, he had an internship at Microsoft Research Asia. He also visited University of Toronto in 2017.

Phyllis Liang

Phyllis Liang

Project Title: Data driven healthcare: Trajectory and predictors of quality of life for individuals with stroke
Rehabilitation Research Institute of Singapore
Previous affiliation: PhD, The University of Queensland, Australia
Email: phyllisliang@ntu.edu.sg

 

Phyllis Liang is a Research Assistant Professor and principal investigator at the Rehabilitation Research Institute of Singapore, Nanyang Technological University. She is a senior occupational therapist and specialises in neurological rehabilitation. She completed her PhD at The University of Queensland, Australia. Phyllis is an experienced clinician and have worked in various healthcare contexts and settings across Singapore and Australia. She uses both qualitative and quantitative approaches. She is an editorial board member of Hong Kong Journal of Occupational Therapy and a research mentor in the Singapore Association of Occupational Therapy.

Li Yuekang

Li Yuekang

Project Title: Intelligent Vulnerability Detection via Adaptive Analysis for Software
Continental-NTU Corporate Lab: Future-Oriented Continental's Urban Society (FOCUS) Lab
Previous affiliation: PhD, School of Computer Science and Engineering, Nanyang Technological University
Email: yukeang.li@ntu.edu.sg

 

Yuekang Li is currently a Research Assistant Professor in Continental-NTU Corporate Lab, Singapore. Prior to that, he received his B.Eng degree and Ph.D from Nanyang Technological University in 2016 and 2020. His research interests include program analysis, software testing and software security. He has publications in top-tier software engineering and security conferences such as FSE, ICSE, CCS and USENIX etc.

Arun Prasanth Nagalingam

Arun Prasanth Nagalingam

Project Title: Evidence-based digital surface enhancement for in-situ roughness monitoring of complex space rocket/fuel injector components using artificial intelligence techniques
Rolls-Royce@NTU Corporate Lab, Singapore
Email: arun.prasanth@ntu.edu.sg

 

Arun works as a Research Assistant Professor (RAP) at the Rolls-Royce@NTU Corporate Lab, Nanyang Technological University, Singapore. Through cutting-edge technology development and commercialization, he contributes to the Singapore 2030 Advanced Manufacturing Hub (AMH) and Jurong Innovation District (JID) initiatives. In addition, Arun is the IPT-Lead of the Manufacturing Technologies programme at Rolls-Royce and manages several projects, researchers, interns, and students.

Arun holds several professional memberships, including the European society for precision engineering and nanotechnology (euspen), project management institute (PMI) Singapore chapter etc. He is an active young member of the institute of mechanical engineers (IMechE) and works with student chapters to develop component engineers at NTU.

Arun’s doctoral work includes the development of a novel post-process surface finishing technique for additively manufactured complex internal passages in aerospace components. He utilized cavitation (a phenomenon that was stated uncontrollable and destructive in the marine industry), harnessed its intensity through a novel machine design, and constructively used it for surface engineering of hard-to-machine materials, including Titanium, Inconel, and Haynes. The process is deemed sustainable as water is the primary working fluid with just a 1.0 % addition of abrasives (while conventional techniques use 60-80 % abrasives). His other research work includes developing and modeling the intelligent vibratory polishing process of 6-stage blisks, additive manufacturing topology optimization and thermal simulations of aircraft electrical engines, etc. In collaboration with the Singapore Centre for 3D Printing (SC3DP), his past research work includes multimaterial polymer, fiber 3D printing of lightweight structures, dynamic materials testing, and non-destructive inspection of crack initiation in complex lattice structures.

In his research portfolio, Arun has several awards, patents, journals, conference proceedings, books, and posters related to advanced manufacturing technologies. In addition, he also serves as a guest editor and reviewer in several international journals, including Additive Manufacturing, Powder Technology, the Journal of Manufacturing Processes, Materials, Coatings, etc.

Bing Song

Bing Song

Project Title: Towards Saft Robot Learning in the Real World
HP-NTU Digital Manufacturing Corporate Lab
Email: bing.song@ntu.edu.sg

 

Bing Song is a Research Assistant Professor at HP-NTU Digital Manufacturing Corporate Lab, and she currently focuses on bridging control and reinforcement learning for robotics. Bing Song received her PhD in Control Theory Lab at Columbia University (2018). Her PhD focused on iterative learning control, specifically how to utilize data and dynamic model in learning. She expanded her research to robotics afterwards at Robotic Manipulation and Mobility Lab from 2019 to 2020 at Columbia University.

Lam Bhan

Lam Bhan

Project Title: Towards a scalable, autonomous, self-learning, ambient-adaptive Soundscape evaluation, augmentation, and monitoring (SEAM) system
SMART Nation Lab, School of Electrical & Electronic Engineering
Email: bhanlam@ntu.edu.sg

 

Lam Bhan is a Research Assistant Professor at the Smart Nation Lab at the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. He received the B.Eng. (Hons.) and Ph.D. degrees both from the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, in 2013 and 2019, respectively. In 2015, he was a visiting postgrad in the signal processing and control group at the Institute of Sound and Vibration Research, University of Southampton, UK. He was previously a research fellow at the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. He has authored more than 40 refereed journal articles and conference papers in the areas of acoustics, soundscape, and signal processing for active control. Dr. Lam was awarded the NTU Research Scholarship and EEE Graduate Award to undertake his PhD under the supervision of Professor Woon-Seng Gan. He was an invited tutorial speaker at APSIPA ASC 2020.

Li Chongyi

Li Chongyi

Project Title: Visual Perception Enhancement and Beyond in an Open World
MMLab@NTU, S-Lab for Advanced Intelligence

Email: chongyi.li@ntu.edu.sg

Chongyi Li is a Research Assistant Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. Prior to this position, he worked as a Postdoctoral Research Fellow in the same university, from 2020 to 2021, and City University of Hong Kong (CityU), from 2018 to 2020. He received his Ph.D. (2018) from Tianjin University under a joint training program with Australian National University. His research interests include image processing, computer vision, and deep learning, particularly in the domains of image restoration and enhancement. He published papers in top-tier journals and conferences, such as TPAMI, TIP, CVPR, ECCV, NeurIPs, etc. Among them, four papers were recognized as ‘ESI Highly Cited Paper’. He serves as an Associate Editor of the Springer Journal of Signal, Image and Video Processing and a Guest Editor of the IEEE Journal of Oceanic Engineering. He served as a senior program committee at AAAI 2022. He was selected as ‘Outstanding Reviewer’ of CVPR 2021 and ICCV 2021.

Shi Dongyuan

Shi Dongyuan

Project Title: Urban Noise Cancelling: Intelligent Anti-noise Window
SMART Nation Lab, School of Electrical & Electronic Engineering

Email: dongyuan.shi@ntu.edu.sg

Shi Dongyuan is currently a Research Assistant Professor in the School of Electrical and Electronic Engineering (EEE) at the Nanyang Technological University (NTU), Singapore. He completed his Ph.D. at the Nanyang Technological University under the supervision of Professor Gan Woon Seng. His research interests include advanced active noise control, deep learning, digital signal processing, adaptive array processing, and high-speed real-time digital system implementation. His work has been published in the Journals such as the journal of Acoustic Society of America (JASA), ACM/IEEE Transaction on Audio, Speech, and Language Processing (TASLP), IEEE transaction on Very Large Scale Integration (VLSI) system, Signal Processing (SP), IEEE Signal Letter (SPL), Mechanical Systems, and Signal Processing (MSSP), and IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). He is currently a member of the IEEE and Signal Processing Society (SPS). He serves as the associate editor of IEICE Transactions on Fundamentals of Electronics, Communications, and Computer Sciences and the first guest editor of Applied Science.

Wang Xinrun

Wang Xinrun

Project Title: Very Large-Scale Multi-Agent Reinforcement Learning
School of Computer Science and Engineering

Email: xinrun.wang@ntu.edu.sg

Xinrun Wang is currently a Research Assistant Professor in the School of Computer Science and Engineering (SCSE) at the Nanyang Technological University (NTU), Singapore. He obtained his PhD degree in computer science from NTU in 2020, under the supervision of Associate Professor Bo An. His research interests include algorithmic game theory, reinforcement learning and multi-agent reinforcement learning. He has published more than 10 papers at top AI conferences, i.e., AAAI, IJCAI, ICLR and NeurIPS.