Hi! I'm Laurence,
I'm an engineering student at McGill University,
and the founder of Inspire (NEXT AI '23), an early stage startup that aims to build low-cost robots for patient monitoring in isolated regions.
Growing up as a self-taught programmer at 14 years old in Canada, I spent my high school years organizing hackathons,
and building ML models for bioinformatics which I presented at science fairs at the national level.
My recent work includes developing motor performance ML models and visualization tools at the R&D team at ACSL Ltd (Japan's largest industrial drone manufacturer),
leading product and developing version one of the core API at Perceive Now as a data scientist,
and co-authoring the AGORA architecture for safe speech-to-text transcription, and the Scavennging Hyena paper for state space model distillation (both awarded 1st place paper at Project X, hosted by UofT AI, two years in a row).
I'm actively looking for research oppotunities related to robotics and machine learning for Summer and Fall 2024. My interests include:
- Sensor fusion
- 3D-space mapping
- Dynamic speedup optimizations
- Generalizable ML models for applied science
- Control systems
- Nature-inspired kinematics
I would love to share my past work and current ideas over a call, and I'm excited to connect!
Experience
- Student Researcher at McGill University and MILA
- Evaluating distillation for state space models, advised by Professor Irina Rish's group (MILA)
- Research Lead at the MAIS Kernel for non-English misinformation detection, advised by Kellin Pelrine (Professor Rabbany's group (MILA))
- prev. Data Scientist at Perceive Now
- Deployed the first version of the core API (startup currently valued at $2.5M+ in pre-seed)
- prev. Drone R&D Intern at the Autonomous Control Systems Laboratory, Ltd.
- Wrote software for the R&D group at Japan's largest industrial drone manufacturer in Tokyo
- prev. Backend Dev at Soulzone
- Developed the API routes for the internal search engine
- prev. Software Dev (Apprentice Program) at Expedia
- Built NLP tools for the Worldwide Engineering Team
Projects
- Inspire (Founder, backed by NEXT AI '23)
- (v1) An autonomous robotic arm (with 3D-printed parts) that can diagnose respiratory disease using automated machine learning
- (v2) (Semi-stealth mode) Low-cost robots for general-purpose patient monitoring in developing and isolated communities
- (July 2023) We are searching for early stage funding and opportunities to grow our core team. Please feel free to connect or recommend someone who may be interested, we'd be super grateful!
- Organizing Hackathons
- 7 editions of hackathons which brought together 1,000+ high school and univeristy student participants since 2018
- McHacks 9, 10
- MariHacks 2020, 2021
- BrébeufHx 2018, 2019, 2020
- Leading a team that raised 5 figures in sponsorships
- Worked with Expedia, CAE and Front Row Ventures
- miRNA Treatments for COVID-19
- Developed a pipeline based on miRDB to identify 169 miRNA candidates
- that could potentially slow down the spread of COVID-19 through RNA interference
- Presented at Regeneron ISEF and Sanofi Biogenius
- AI-Based Predictions for Transcription Factors (genes) that Stimulate Spinal Cord Regeneration
- Developed ADAGE, an ensemble model based on TRRUST v2 that predicts
- transcription factors associated to specific cellular functions, including CNS neuron regeneration.
- I'm incredibly grateful for the time and support of Prof. Patten from the INRS Armand-Frappier to experimentally test the model predictions in a laboratory setting.
- Presented at the Canada-Wide Science Fair and Sanofi Biogenius.
- Handheld Exoskeleton for Surgery (proof-of-concept)
- Developed the computer vision and controls components of a handheld exoskeleton,
- which can be controlled by gesturing in front of a webcam
- Built at HackMIT (2nd Place PRHI Challenge), and we're looking for industry and resarch opportunities to grow.
Recognition
- Cansbridge Fellow
- 2x Microsoft Imagine Cup World Finalist (Top 48)
- HackMIT PRHI 2nd Place
- Mitacs Business Strategy Internship Grant Recipient
- TEDx Speaker
- Regeneron ISEF Grand Award Recipient
- 2x Canada-Wide Science Fair Bronze Medalist
- 1st Place Sanofi Biogenius in Québec (3rd in Canada)
- 3rd Place Hack Harvard
- 1st Place Project X (Co-author, Human-to-Human Category)
- NEXT AI Cohort '23
- IRONMAN 70.3-distance Finisher at Triatlon Esprit (+/- 300 metres, due to race track)
Education
- Engineering at McGill University (in progress)
- McHacks Organizer
- Cansbridge Fellow
- RippleX Fellow
- Founded a robotics startup during my freshman year, currently backed by NEXT AI '23
- Taught two courses at MIT Splash
- Honours Health Sciences at Marianopolis College
- Elected President of the Marianopolis Student Union
- MariHacks Organizer
- Grade 12 + university freshman year-equivalent courses
- Secondary School at Collège Jean-de-Brébeuf
- BrébeufHx Hackathon Organizer (co-founder)
- Fencing Top 8 in Québec (2016, 2017)
- Grades 7 to 11
Publications + Writing
- Publications and Poster Presentations
- T. R. Ralambomihanta, S. Mohammadzadeh, M. S. N. Islam, W. Jabbour, L. Liang, ‘Scavenging Hyena: Distilling Transformers into Long Convolution Models,’ https://arxiv.org/abs/2401.17574, Jan. 2024.
- L. Liang, V. Pak, N. Irshaid, and Z. Yang, ‘Improving Classification Accuracy using Contrastive Principal Component Analysis’. (Manuscript in preparation.)
- Joly-Chevrier M, Nguyen AX-L, Liang L, Lesko-Krleza M, Lefrançois P. The State of Artificial Intelligence in Skin Cancer Publications. Journal of Cutaneous Medicine and Surgery. 2024;0(0). doi:10.1177/12034754241229361
- V. Cruz and L. Liang, ‘AGORA: a Language Model for Safe Speech-to-Text Conversion’, Canadian Undergraduate Conference on Artificial Intelligence (CUCAI), 2023. (Awarded top 6 overall paper at CUCAI 23.)
- L. Liang, ‘Computer-Based miRNA Predictions to Inhibit SARS-Cov-2 Replication’, Regeneron ISEF, 2021. (Awarded 4th place in computational biology).
- L. Liang, ‘Using a Computer Model to Assist Neuron Regeneration’, Canada-Wide Science Fair (CWSF), 2019. (Awarded a bronze medal in the senior category).
- L. Liang, ‘Using AI to Understand Neuronal Behaviour’, Canada-Wide Science Fair (CWSF), 2018. (Awarded a bronze medal in the intermediate category).
- Speaking Opportunities
- U. Kalkar and L. Liang, ‘Panel on Machine Bias,’ International Development Conference at the University of Toronto Scarborough, 2024.
- L. Liang, ‘A Stochastic Optimization Approach for Energy-Efficient Robotic Manipulator Simulations,’ Seminars on Undergraduate Mathematics in Montreal (SUMM 2024), 2024. (link)
- L. Liang, ‘Bioinformatics, Molecular Solutions, Intelligent Machines, and the Future of Medical Care,’ Big Data and AI Toronto (BDAIT 23), 2023. (link)
- L. Liang, ‘Controlling a Robotic Arm using Computer Vision’, MIT Splash, 2022. (link) (E15416 course taught at MIT Splash)
- L. Liang, ‘Identifying Cancer Cells Using Genetic Analysis and Computer Vision’, MIT Splash, 2022. (link) (S15418 course taught at MIT Splash)
- L. Liang, ‘Curing Disease from our Living Rooms: a Vision for Bioinformatics,’ TEDx McGill, 2021. (link)
- Essays & Newsletter