Jasraj Aulakh

MSc Computer Science @ UCL, BSc Chemistry with Mathematics @ UCL

United Kingdom

About

Experience

  • Lead Educational Content Developer - Mathematics at Seneca Learning
    Feb 2026 - May 2026 · 4 mos

    - Led and managed 3 mathematics content creators, establishing project milestones, delegating workflows, and directly auditing team contributions to maintain quality control standards. - Designed and programmed the most complex sections of the course, coding advanced, multi-step questions with accompanying walkthroughs to cover the full GCSE syllabus across major UK exam boards. - Streamlined the production workflow using AI to accelerate question generation, designing specific prompts for different scenarios like template creation and modification. - Led the team to deploy ~2000 algorithmically variable questions, while programming adaptive, step-by-step walkthroughs that dynamically update with each unique variation. - Directed the quality assurance pipeline, reviewing and refining the team's work to ensure high standards before final deployment approval from senior management.

  • AI Systems Engineering Masters Project at IBM
    Jun 2025 - Sep 2025 · 4 mos

    Final MSc Computer Science capstone project at University College London (UCL). - Developed MotionInput for Chemistry, an AI-integrated, touchless learning tool created in collaboration with UCL, IBM, Intel, and Microsoft to improve accessibility in STEM education. - Designed and implemented end-to-end inference pipelines integrating real-time hand-tracking with a locally deployed LLM, and packaged the system as a standalone executable suitable for real-world deployment and publishing. - Focus on performance optimisation and translating machine-learning models into reliable, deployable software.

  • MAPS Research Intern at UCL Research
    Jun 2024 - Aug 2024 · 3 mos

    Worked as a Battery Modelling and Manufacturing Cost Estimation intern: - Conducted life cycle analysis of lithium-ion cells, using Excel and Python to visualise key performance metrics, assess cell rejuvenation after multiple cycles, whilst ensuring clear communication of insights through data visualisation techniques. - Performed cost estimations for pouch cells using CellEst, benchmarking predictions against market rates and exploring the economic impact of various cell configurations. - Utilised BatPac for cost estimation of pouch and prismatic cells with NMC333 chemistry, scaling predictions to EV battery packs and validating results against Tesla Model 3 LR 2024 pack specifications. - Analysed recycling methods with Everbatt, focusing on the commercially available LG cylindrical cell, and generated comparative visualisations using Python to evaluate the sustainability and economics of different recycling processes.

  • MAPS Ambassador at Unibuddy
    Nov 2022 - Jun 2024 · 1 yr 8 mos

    - Engaged with prospective students through the Unibuddy platform, answering questions and sharing personal experiences to provide insights into university life. - Represented the university by offering information about both academic and social aspects of the student experience.

  • Spring Intern at Goldman Sachs
    Apr 2023 - Apr 2023 · 1 mo

    - Gained insight into the financial sector through interactive case studies and presentations led by Goldman Sachs professionals. - Collaborated with peers in group activities, developing problem-solving and analytical thinking skills. - Gained a deeper understanding of the operations and strategic approaches across various departments within the firm.