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Associate ProfessorAvinash Malik

Associate Professor

Elec Comp and Software Eng

Orcid identifier0000-0002-7524-8292
  • Associate Professor
    Elec Comp and Software Eng
  • +6493737599 Ext.89231 (Work)
  • ENGINEERING BLOCK 5 - Bldg 405, 5 GRAFTON RD, AUCKLAND CENTRAL, AUCKLAND, 1010, New Zealand

TEACHING INTERESTS


Current Teaching:
COMPSYS723 - Embedded Systems Design
COMPSYS303 - Microcomputers and Embedded systems
COMPSYS705 - Formal Methods for Engineers

SOFTENG 751 -- High Performance computing

 


Postgraduate Supervision:
Jin-Woo Ro, 2018-2020 -- Efficient traffic simulation engines using quantized state integration on super-dense time

 

PhD ongoing:

Mr. Hongshen Yang (2022-current) -- supervisory control algorithms for arbitrage trading.

Mr. Guiming Zhang (2019-current) -- Machine learning techniques for the inverse problem of electrocardiography

Mr Pinzhang Wu (2025-current) -- Safety of AI

 

ME ongoing:

Mr. Peter Briesch -- ML/AI algorithms for option implied volatility prediction (thesis submitted).

Mr Eugene Lee -- Real-time pacemaker for the Gut.


PhD supervised to completion:

Dr. Luman Wang (2022), post-doc ECSE UoA.

Dr. Manish Tiwari (co-supervisor), 2023

Dr. Surinder Sood (2024), ARM Manchaster UK

Dr. Ke Ren (2019)

Dr. Tommy Peng (2019), Bionic institute Australia

Dr. Hee-Jong Park (co-supervisor), PhD. 2015, postdoc at NTU Singapore
Dr. Zhenmin Li (co-supervisor), PhD. 2016, Assistant Professor, Hefei University of Technology, China.
Dr. Jin-Woo Ro (co-supervisor), thesis submitted.


Master (ME Research) candidates completed:
Mr. Rakesh Vallabh, 2019 
Ms. Luman Wang, 2019 

TEACHING & SUPERVISION

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  • PHD ONLY SUPERVISION OPPORTUNITY
    Combining text and visual language models to generate safe and efficient software.
    2 Jan 2025 - 31 Dec 2025
    Writing performant software programs is challenging. Software engineering has seen significant uptake of Large Language Models (LLMs) for tasks such as automated patching of functionally incorrect programs, to requirements engineering. However, LLM assisted correction of software performance-defects remains elusive. This project aims to fill in this gap. We develop a new LLM called CodeGem that combines text-language model (CodeGemma) and visual-language model (PaliGemma) to understand performance defects and assist developers in fixing these bugs. In doing so, we aim to improve: 1 software efficiency of large software infrastructure thereby reducing its carbon footprint, 2 improve functional safety of AI generated software, and 3 improve future developer productivity.
  • GENERAL SUPERVISION OPPORTUNITY
    The current research of Dr Avinash Malik
    Enrolment information: NZ Citizens, NZ Permanent Residents, International Introduction RESEARCH | CURRENT - Real-time systems - Embedded systems - Compiler construction - Programming language semantics - Logic for program verification