Elissa Lim

Elissa Lim

Logistics Intern

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  • Timeline

  • About me

    Researcher at PRML Lab, Korea University

  • Education

    • National University of Singapore

      2013 - 2017
      Bachelor of Science Business Analytics Honours
    • Yonsei University 연세대학교

      2014 - 2014
      Summer Immersion Programme Korean Language
    • University of California, Riverside

      2015 - 2015
      Student Exchange Programme Business Administration
    • Korea University

      2022 - 2024
      Master's degree Artificial Intelligence

      Korean Government Scholarship Programme 2021 for Graduate Degrees (2021-2024)Grade: Summa cum laude

  • Experience

    • Suzhou Xinning Logistics Co. Ltd

      Dec 2012 - Feb 2013
      Logistics Intern

      • Communicated directly with Chinese and international counterparts• Managed import and export of goods with knowledge of China customs regulations• Contributed to enhancement of warehouse management system

    • Olam

      Apr 2013 - May 2013
      Documentation Officer

      • Interacted with international clients• Handled invoices, Letter of Credit and payment• Validated shipping documents

    • Singtel

      May 2015 - Aug 2015
      Business Analytics Intern

      • Assisted in data analysis, KPI reporting and strategic planning for Dash, the mobile payment business• Coordinated cross-functional stakeholders for the analysis of customer acquisition, mobile application usage and marketing campaigns to evaluate marketing efforts• Analysed sales and churn data for forecasting and determining effectiveness by channels• Delivered insights and recommendations to increase user engagement

    • Apple

      Jan 2016 - Jul 2016
      Project Management Office Intern

      • Assisted in end-to-end planning and execution of Asia Pacific supply chain projects, including geo-expansion project for an emerging market, which streamline processes and enhance logistics systems• Collaborated with external OEM, ODM and 3PL, and internal cross-functional stakeholders• Supported various stages of project lifecycle namely, kick-off, validation of business requirements for internal and external IT systems and infrastructures, UAT (system testing), go-live and warranty

    • SP Group

      Aug 2017 - Dec 2021

      • Researched, designed and developed a novel solution to detect Partial Discharge signals in Switchgears• Designed and developed statistical rules and algorithms to derive energy insights• Designed impact analysis to measure the effectiveness of a green initiative • Led a microgrid project for economic dispatch, oversaw the overall system design, and implemented the first principal equipment models and optimization engine• Led the load shifting scheduler ideation as an extension of the capacity management service • Developed and deployed a novel automatic peak shaving solution using the Energy Storage System• Analysed various data sources such as CRM system, call and chat logs, and developed a rule-based chatbot• Designed and developed the profiling capability using a customer’s energy consumption profile to estimate and evaluate their Contracted Capacity efficiency score and potential savings • IT Graduate Development Programme (iGRAD) with the Digital Technology Team: Software Engineer (August 2017 to March 2018) and Data Analyst (April 2018 to July 2019)• Developed a merchant web portal using Ruby on Rails (MVC framework) for the company’s digital wallet initiative• Developed API using Go for the Energy Web blockchain Renewable Energy Certificate

      • Senior Data Scientist

        Jul 2020 - Dec 2021
      • Data Scientist

        Aug 2019 - Jul 2020
      • Data Analyst (Graduate Programme)

        Apr 2018 - Jul 2019
      • Software Engineer (Graduate Programme)

        Aug 2017 - Mar 2018
    • Korea University

      Sept 2022 - now
      Researcher

      • Research on decoding brain activity using electroencephalography signals for Brain-Computer Interfaces at the Pattern Recognition and Machine Learning Lab (http://pr.korea.ac.kr)Academic Papers• GITGAN: Generative Inter-subject Transfer for EEG Motor Imagery Analysis (Pattern Recognition Volume 146)• Baseline-Guided Representation Learning for Noise-Robust EEG Signal Classification (46th Annual International Conference of the IEEE Engineering in Medicine & Biology Society)

  • Licenses & Certifications

  • Volunteer Experience

    • Volunteer at Meet-the-People Session

      Issued by Group Representation Constituency on Jan 2013
      Group Representation ConstituencyAssociated with Elissa Lim
    • Korea-Singapore Supporter

      Issued by Embassy of the Republic of Korea on Sept 2014
      Embassy of the Republic of KoreaAssociated with Elissa Lim