Dr. Hansani Weeratunge

Assistant Professor | Department of Mechanical Engineering | Faculty of Engineering

CAREER SUMMARY

Hansani is serving as an Assistant Professor in the Department of Mechanical Engineering at the Sri Lankan Institute of Information Technology (SLIIT). She holds a PhD from the University of Melbourne and a BSc from the University of Peradeniya. She also worked as a postdoctoral researcher at the University of Melbourne and CSIRO, the national research agency in Australia. Her expertise lies in the applications of optimization and machine learning, particularly for enhancing the efficiency of energy systems and developing materials with tailored properties.

ACADEMIC QUALIFICATIONS

  • Doctor of Philisophy, The University of Melbourne, Australia
  • Bachelors in Engineering (Hons), University of Peradeniya, Sri Lanka.

HONOURS AND AWARDS

  • E.O.E Pereira Gold Medal, for the Most Outstanding Student Graduating from the Faculty, University of Peradeniya
  • C. A. Hewavitharana Prize for the Best Performance in Engineering, University of Peradeniya
  • Channa Lalith Maddumage Prize, for Best Performance in Mechanical Engineering, University of Peradeniya
  • E.O.E Pereira Prize, for Structures (Third Year), University of Peradeniya 
  • M.P Ranaweera Prize, for Finite Element Methods in Solid Mechanics, University of Peradeniya
  • J.C.V Chinnappa Prize, for Energy Studies, University of Peradeniya
  • L.R.L Perera Prize for Best Performance in Applied Thermodynamics, University of Peradeniya
  • S. Mahalingam Prize, for Mechanics of Machines, University of Peradeniya
  • T. Sivaprakasapillai Prize, for Industrial Engineering, University of Peradeniya

RESEARCH CLUSTERS

Advanced AI Applications in Engineering

"The ""Advanced AI Applications in Engineering"" research group focuses on integrating cutting-edge artificial intelligence techniques across various engineering fields, including electrical and electronics, telecommunications, civil, mechanical, mechatronics, and biomedical engineering.  The group aims to address complex real-world challenges by applying AI to optimize system performance, enhance energy efficiency, and improve automation. 

Key areas of research include AI-driven system design, signal processing, smart infrastructure, autonomous systems, biomedical diagnostics, and intelligent manufacturing. Through interdisciplinary collaboration, the group seeks to advance AI-driven innovations that contribute to smarter, more resilient, and efficient engineering solutions."

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