About Me

I am a passionate Machine Learning and Artifical Intelligence researcher with a robust academic and industry background, dedicated to advancing AI solutions in healthcare, recommender systems, and multi-modal learning. My expertise spans reinforcement learning , cross-domain recommendation systems, and healthcare decision-making . Over the years, I’ve contributed to cutting-edge research, mentored future innovators, and led multidisciplinary teams to success.

Research Interests

  • Reinforcement Learning: Developing adaptive models for decision-making in complex environments.
  • Healthcare AI: Crafting intelligent systems to optimize personalized treatment and predictive diagnostics.
  • Agentic AI: Exploring AI autonomy and collaboration for multi-agent systems.
  • Time Series Analysis: Advancing methodologies for longitudinal and temporal data insights.
  • Multi-Modal User Modeling: Leveraging diverse data streams for enhanced user insights.

Key Experience

  • Postdoctoral Fellow, NUS Saw Swee Hock School of Public Health.
    Leading AI initiatives in healthcare, developing reinforcement learning frameworks for personalized treatment decisions.
  • Co-Founder & CTO, RecceLabs.
    Designed cutting-edge recommendation platforms and real-time bidding systems for cloud-based applications.
  • AI Consultant, HeHealth.
    Spearheaded NLP and computer vision projects for innovative healthcare screening solutions.
  • Research Scientist, Rakuten, Tokyo.
    Specialized in large-scale recommendation systems, designing and researching advanced machine learning methodologies to optimize real-time ad recommendations and drive user engagement.

Selected Projects

🩺🤖
Smart Imitator: Empowering AI to Learn from Imperfect Clinical Decisions

Healthcare isn’t a perfect science, clinician errors often impact outcomes. If experts struggle with complex cases, can AI do better? Click to learn more.

🩺🤖
Collaborative Multi-Agent AI: A Step Toward Agentic AI in Healthcare

Imagine a healthcare system where AI acts as a team of intelligent collaborators.
Click to learn more.

🩺🤖
Beyond Toy Problems: Collaborative Multi-Agent AI for Smarter Multi-Organ Healthcare Decisions

Imagine an AI system that doesn’t just focus on single organs but understands how treatments impact the entire body.
Click to learn more.

🎯🎵
CnGAN: The First GAN-Based Cross-Network User Preference Generator

Discover YouTube content inspired by your tweets—no account linking needed. CnGAN bridges platforms to deliver personalized recommendations effortlessly.
Click to learn more.

🎯🎵
From Social Network Explorations to spontaneous Cross-Platform Recommendations

Log into one system and get seamless recommendations—articles, videos, and podcasts—all tailored to your evolving interests across platforms.
Click to learn more.

🎯🎵
From Implicit Interactions to Comprehensive Cross-Network Recommendations

New to the network or experienced? This system delivers personalized recommendations by learning from your cross-platform interactions.
Click to learn more.

Education

Aug 2015 – Aug 2020
PhD in Computer Science
School of Computing - National University of Singapore
July 2009 – Sept 2013
BSc (Hons) in Information Technology
Faculty of Information Technology – University of Moratuwa, Sri Lanka

  • First Class Honours and on the Dean’s List Academic Excellence in all semesters.

Research Experience

Jun 2020 - Present
Postdoctoral Research Fellow
Institute of Data Science, National University of Singapore
Advisor: Associate Professor Mengling 'Mornin' Feng

  • Lead reinforcement learning (RL) research in the lab, focusing on AI-driven healthcare solutions.

  • Developed collaborative multi-agent RL frameworks to optimize complex medical treatments.

  • Mentored PhD and undergraduate students, fostering innovation in AI-driven healthcare solutions.

  • 🏅 Recipient of the prestigious Talent Development Award from the Saw Swee Hock School of Public Health, awarded for independent research excellence with a grant of S$100,000.

Aug 2015 – Aug 2020
Doctoral Researcher
School of Computing, National University of Singapore
Advisor: Professor Roger Zimmermann

  • Proposed a first of its kind generative adversarial learning frameworks to synthesize user preferences across social networks.

  • Developed state-of-the-art time-aware recommendation systems using deep learning.

  • Introduced generic learning-to-rank optimization criteria to enhance recommendation effectiveness using implicit feedback data.

Sep 2019 – Nov 2019
Research Scientist – Intern
Rakuten Inc., Tokyo

  • Designed a novel LSTM architecture for large-scale real-time ad recommendations, significantly improving user engagement and conversion rates in big data systems.

PROFESSIONAL Experience

Jan 2020 - 2024
Co-founder/CTO
RecceLabs (Pvt) Ltd, Singapore and Sri Lanka

Responsibilities:

  • Designed and scaled cloud-based recommendation platforms and real-time bidding systems.

  • Directed cross-functional teams in AI product development.

  • Developing technical strategies to align projects with business objectives and goals.

Jan 2021 - 2023
Consultant – AI Lead
HeHealth, Singapore

  • Led AI initiatives in Natural Language Processing (NLP) and Computer Vision (CV) projects, addressing critical healthcare screening challenges.

  • Designed and deployed new AI models tailored for health screning tasks, ensuring technical rigor and real-world applicability.

  • Managed end-to-end AI solution development, overseeing research, implementation, and deployment while mentoring technical teams.

Jan 2015 – July 2015
Senior Software Engineer
Virtusa (Pvt) Ltd,Sri Lanka, a CMMI Level 5 certified global software company

  • Managed Agile teams, delivering enterprise-grade full-stack solutions.

  • Developed WSO2 ESB connectors, integrating with public APIs and web services for seamless IoT business scenarios.

  • Conducted proof-of-concept implementations and conducted client demonstrations.

Sept 2013 – Jan 2015
Software Engineer
Virtusa (Pvt) Ltd, Sri Lanka

  • Rebuilt gov.lk, centralizing Sri Lanka's e-government services.

  • Developed a central payment gateway and scalable e-services for government departments, enhancing nationwide accessibility and efficiency.

Jan 2012 – Jun 2012
Software Engineer – Intern
Virtusa (Pvt) Ltd, Sri Lanka

  • Enhanced an automated code quality review system with Python and Pega support.

AWARDS & SCHOLARSHIPS

Awards:

  • 🏅 Recipient of the prestigious Talent Development Award from the Saw Swee Hock School of Public Health, awarded for independent research excellence with a grant of S$100,000, (2024).

  • 🏅 Dean's Graduate Research Excellence Award for outstanding PhD research performance, National University of Singapore, (Academic year: 2019/2020).

  • 🏅Dean’s List of Academic Excellence across all semesters, University of Moratuwa, Sri Lanka, (2009 - 2013).

Scholarships:

  • National University of Singapore Research Scholarship (2015 - 2019).

  • Travel grant to present research at the International Young Scientists Forum Peng Cheng Laboratory, Shenzhen, China (2019).

  • National University of Singapore conference travel grants for 4 consecutive years (2017 - 2019).

  • Mahapola Higher Education Scholarship, Government of Sri Lanka (2009 - 2013).

Publications and Patents

Publications:

  • Dilruk Perera, Liu Siqi and Mengling Feng., 2024. Smart Imitator: Learning from Imperfect Clinical Decisions. In Proceedings of the Journal of the American Medical Informatics Association (JAMIA).

  • Dilruk Perera, Liu Siqi and Mengling Feng., 2023. Demystifying complex treatment recommendations: A hierarchical cooperative multi-agent RL approach. In Proceedings of the International Joint Conference on Neural Networks (IJCNN).

  • Dilruk Perera and Roger Zimmermann., 2020, April. Towards comprehensive recommender systems: Time-aware unified recommendations based on listwise ranking of implicit cross-network data. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 34, No. 01, pp. 189-197).

  • Dilruk Perera and Roger Zimmermann., 2019, May. CnGAN: Generative Adversarial Networks for cross-network user preference generation for non-overlapped users. In Proceedings of the World Wide Web Conference (pp. 3144-3150).

  • Dilruk Perera and Roger Zimmermann., 2018, July. LSTM networks for online cross-network recommendations. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (pp. 3825-3833).

  • Dilruk Perera and Roger Zimmermann., 2017, October. Exploring the use of time-dependent cross-network information for personalized recommendations. In Proceedings of the 25th ACM International Conference on Multimedia (pp. 1780-1788).

Patents:

  • 🔖 Kularathna, Y. & Perera, D. Distinguishing a disease state from a non-disease state in an image. AI driven visually recognizable diagnostic system.
    Grant No: US11721023B1 .

RESEARCH GRANTS

  • 2024-2025: Principal Investigator of "Multi-Agent Reinforcement Learning System for Comprehensive Treatment Decisions", School of Public Health, National University of Singapore, S$100,000.

  • 2025: Co-Investigator of "Population Health Research Grant - AI-Powered Precision Healthcare for Chronic Disease Management", National Medical Research Council. (under submission).

TEACHING AND MENTORING

Since May 2021
Co-lecturer for Advanced Statistical Learning (SPH6004)
Saw Swee Hock School of Public Health, National University of Singapore

  • Preparing materials, conducting lectures covering reinforcement learning research methodologies, theory and applications for PhD students.

May 2018
Teaching Assistant for Data Structures and Algorithms (CS2040C)
School of Computing, National University of Singapore

  • Prepared and evaluated assignments of 200+ undergraduate students and conducted online invigilation for groups of 40 students.

2016 – 2018
Teaching Assistant for Software Engineering Project I and II (CS3201 and CS3202)
School of Computing, National University of Singapore

  • Conducted tutorials and consultations undergraduate students for 4 semesters.

  • Prepared, invigilated, and evaluated assignments of 280+ students.

Jan 2016
Teaching Assistant for Programming Methodology (CS1010)
School of Computing, National University of Singapore

  • Prepared Java coding assignments and test cases for evaluations.

ACADEMIC SERVICES

Invited Presentations

  • Invited to Present at the Clinical Information Systems Working Group at the American Medical Informatics Association (JAMIA) 2025.

  • Presented at the International Joint Conference on Neural Networks (IJCNN 23), Gold Coast, Australia in June 2023. [slides]

  • Presented at the 34th AAAI Conference on Artificial Intelligence (AAAI’ 20), New York, USA in February 2020. [slides]

  • Presented research at the Computing Research Week, National University of Singapore in 2020. [talk] [slides]

  • Presented at the 28th Web Conference (WWW’19), San Francisco, USA in May 2019. [slides]

  • Presented at the International Young Scientist Forum Peng Cheng Laboratory, Shenzhen, China in March 2019. [slides]

  • Presented at the at the 27th International Joint Conference on Artificial Intelligence (IJCAI-ECAI '18), Stockholm, Sweden in July 2018. [slides]

  • Presented at the 25th ACM International Conference on Multimedia (ACM MM’17), Mountain View, USA in October 2017. [slides]

Organizing Committee Member

  • Organizing Committee Member, Singapore Healthcare AI Datathon(Annual), National University of Singapore, National University Health System and MIT Critical Data.

  • Thematic Workshop Coordinator, 25th ACM International Conference on Multimedia (ACM MM’ 17).

  • National Young Innovators Competition Coordinator, University of Moratuwa.

Program Committee Member (Selected)

  • Association for the Advancement of Artificial Intelligence (AAAI), since 2020

  • International Joint Conferences on Artificial Intelligence (IJCAI), since 2020

  • Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), since 2020

  • IEEE International Conference on Multimedia and Expo (ICME), since 2019

  • IEEE International Conference on Multimedia Big Data (IEEE BigMM), since 2019

  • ACM Transactions on Intelligent Systems and Technology Journal (ACM TIST), since 2019

  • ACM International Conference on Multimedia (ACM MM), since 2017

  • International Conference on Design Science Research in Information Systems and Technology (DESRIST), since 2017

Project Supervision

  • Co-supervise PhD research projects at the Saw Swee Hock School of Public Health, NUS, focusing on the development of AI-driven treatment agents for personalized healthcare, leveraging reinforcement learning to model and optimize clinical decision-making.

  • Supervise undergraduate research projects at NUS, including work on deep learning, real-time bidding systems, and robust recommendation systems.

Contact Me

Dilruk Perera
Postdoctoral Research Fellow
National University of Singapore

EMAILs: dilruk@nus.edu.sg | dilrukperera28@gmail.com

Dilruk Perera
POSTDOCTORAL RESEARCH FELLOW

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