Ambrose Ling Email & Phone Number

Toronto, Ontario, Canada

(Starting Summer 2025) TT-Metal

Markham, Ontario, Canada

Diffusion Models for Consumer Business Group

Toronto, Ontario, Canada

Toronto, Ontario, Canada

Toronto, Ontario, Canada

· Involved in the team of 9 machine learning engineers in the research, development and implementation of protein function prediction models· Employing sequence truncation, positional encodings on protein sequences; developing Graph Neural Networks (GNN) models to learn protein interactions & spatial representations of protein sequences; predicting functions with Gene Ontology (GO) scheme· Leveraging transformer-based PorteinBERT, ESM for feature extraction to generate amino acid embeddings fed to GNN· Collaborating with cross-functional units (feature engineering & model architecture) to find model performance-enhancing features

Toronto

• Co-founded a tech start-up that creates AI-powered video-communication platform for seniors to connect over similar interests• Developed application with Flutter, FlaskAPI, Firebase, completed multiple rounds of 5 on 5 iterative user testing• Awarded Global Top 100 Finalists in Google Solutions Challenge 2023 out of 2000 teams; implemented at 25+ day-care agencies

Toronto, Ontario, Canada

• Led a team of 4 in R&D on computer vision for zebrafish tracking and time-series prediction for zebrafish virtual locomotion • Deployed a real-time zebrafish movement tracking model by fine-tuning ResNet50 & MobileNet models in Tensorflow• Preprocessed images by applying normalization, scaling; Preprocessed labels by converting coordiantes to gaussian heat map• Reduced tracking prediction times through parallel computing using distributed strategies in Tensorflow, from 0.183s to 0.062s• Developed and implemented multi-layer GRU, and GRU encoder CT-RNN decoder, both resulted in 5% reduction in MSE and 6% increase in R2 score compared to autoregressive (ARX) benchmark• Extraced curvature and deflection angle as features, applied local poynomial interpolation to handle uneven sampling in datasets• Presented RNN locomotion prediction research at undergraduate conferences, awarded Best Poster among 60 research projects

Toronto, Ontario, Canada

• Developed a FEED business model & 24 month cash flow projection for LINKUPSS startup, pitched start-up idea to investors• Practiced agile methodology by communicating with over 50+ user groups, 20+ competitors for market research• Evaluated mentor and user feedback to make continuous improvements to software and hardware design

Hong Kong Sar

• Involved in the development process of an AI-supported store stock planning and allocation system for jewellery company Chow Sang Sang• Responsible for constructing backend systems, databases in POSTGRESQL and used Javascript to develop an object relational mapping structure (ORM)• Involved with other minor supporting tasks in frontend department

Undergraduate, Computer Engineering

Ontario Secondary School Diploma (Ossd), Computer Science

Activities and Societies: Team X, Peer Counsellor, Osler Speech Champion, Debate Club, Academic Steward