Arpit Garg

Experience

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  Indian Navy

  May 2018 - Jul 2018

  Research Intern

  • Designed ammunitions for naval ships and submarines using JavaFx, ensuring precision and efficiency in weaponry systems.• Researched and outlined various meters required on submarines and ships, collaborating with Indian Navy technical team for seamless integration.• Programmed tools to enhance user control, resulting in improved operational capabilities and user experience.Comp

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  Defence Terrain Research Laboratory, DRDO

  Dec 2018 - Mar 2019

  Research Intern

  • Conducted research on image processing algorithms to optimize object geometry tuning for end-users.• Utilized Machine Learning and Deep Learning techniques to solve face detection and object detection problems.• Analyzed performance of 40+ image processing algorithms to enhance system efficiency.• Practiced OpenCV and Digital Image Processing for robust evaluations of systems and computer vision algorithms.

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  Australia for UNHCR

  Jan 2020 - Mar 2020

  Frontliner

  • Strategized creative ways for walkers to reach fundraising goals, boosting event participation and retention rates• Conducted market research and analytics to increase event participation, resulting in a significant rise in donations• Maintained positive relationships with clients, demonstrating patience and professionalism throughout interactions

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  MODELL'E

  Feb 2020 - Mar 2020

  Information Technology Consultant

  • Monitored web pages for continuous improvements using cPanel• Diagnosed errors on the website and applied enhancements for better user experience• Managed software improvements and developer training to integrate sites

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  University of Adelaide

  Jul 2020 - Jan 2024

  • Assisted professors and collaborated with Teaching Assistants to prepare data-driven reporting for student evaluation.• Delivered pre-lab talks on core concepts for Programming Matlab and C, Big Data Analysis, and more.• Provided timely grading and valuable feedback to students, identifying trends for improvement. • Designed and delivered comprehensive curriculum for Big Data Mining course, focusing on scalable data analysis techniques• Led lectures covering key topics including data preprocessing, pattern mining, clustering, and large-scale machine learning• Developed hands-on programming assignments using real-world datasets to reinforce practical implementation skills • Implemented a system to find relationships between authors, APIs, and projects for developer assignment.• Analyzed homogeneous relationships to optimize project allocation and developer expertise.• Developed algorithms to streamline the assignment process and improve project outcomes. • Developed automated machine learning pipeline for security patch analysis across large-scale codebases.• Engineered deep learning models to classify and categorize security vulnerabilities in software patches.• Built end-to-end system processing 10K+ patches, enabling rapid identification of critical security updates. • Developed course materials and curriculum for Big Data Mining, including lectures and practical assignments• Engineered automated grading systems for efficient evaluation of student submissions• Created plagiarism detection tools to maintain academic integrity• Implemented Learning Management System automation for course administration and grade management • Provided personalised support for commencing International students in the International Peer Study Support (IPSS) program at the University of Adelaide.• Mentored small groups of commencing students weekly, sharing advice and support for a smooth transition to university life.• Facilitated a supportive environment for students to connect with Senior International Mentors from the same Faculty for guidance and assistance.

  • Teaching Assistant

    Mar 2020 - Jan 2024

  • Lecturer

    Feb 2022 - Jun 2023

  • Research Engineer

    Jul 2021 - Jan 2022

  • Summer research scholarship

    Nov 2020 - Feb 2021

  • Academic Staff Member

    Nov 2020 - Dec 2020

  • International Peer Study Support Mentor

    Jul 2020 - Nov 2020
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  Adelaide Business School

  Jun 2022 - Jun 2023

  Machine Learning Engineer

  • Developed an advanced market intelligence system using computer vision and NLP to analyze C-suite sentiment across 5,000+ companies.• Built ML models to extract strategic insights from executive communications for data-driven market analysis.• Implemented scalable NLP pipelines to process and classify large volumes of business communications data.

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  Australian Institute for Machine Learning (AIML)

  Oct 2022 - Jan 2025

  • Developed novel methodologies to enhance image classification robustness under noisy label conditions.• Published cutting-edge research at ECCV2024 and WACV 2023, advancing techniques for handling label noise in deep learning.• Investigated theoretical foundations and practical implementations of noise-resistant training strategies. • Led interactive presentations and workshops on AI and ML for diverse audiences, inspiring the next generation of technologists.• Organized hands-on AI demonstrations during open days, making complex concepts accessible through interactive examples.• Represented the AIML department at key stakeholder events, communicating technical concepts to government officials and industry partners.

  • Researcher PHD Student

    Nov 2021 - Jan 2025

  • Student Ambassador

    Oct 2022 - Dec 2024
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  Rising Sun Pictures

  Jun 2023 - Oct 2024

  Machine Learning Engineer

  • Spearheaded ML initiatives as Head of Machine Learning for Sonic 3, leading technical strategy and implementation.• Architected end-to-end ML pipeline for Sonic 3's VFX production, including super-resolution and neural rendering systems.• Developed cutting-edge ML solutions for character enhancement through advanced deepfake and gaze redirection techniques.Credits: Sonic3, Madmax: Young Furiosa, Deadpool vs Wolverine, Mickey17, LaBrea

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  TikTok

  Jan 2025 - now

  Machine Learning Engineer

  • Conducted systematic analysis of visual backbone architectures in multi-modal LLMs to enhance model robustness and improve detection reliability.• Developed novel knowledge transfer frameworks to distill specialized visual abilities into production models for safety-critical tasks.• Spearheaded research initiatives to map the relationship between architectural choices and emergent visual understanding in multi-modal systems at TikTok.