Curriculum Vitae
Chris J. Czarnecki
[ kjczarnecki.com ] [ kjczarne@gmail.com ]
ORCID: 0009-0008-3721-6151
Experience
AI Engineer/Scientist at KisoJi Biotech
(Aug 2024 - now, Waterloo, ON, Canada)
- Lead of the Digital KisoMouse project – a digital twin of a mouse immune response
- Developed an in-house VHH antibody design pipeline within 4 months of joining the company
- Generated VHH antibodies against several targets with lab-confirmed activity
- Fine-tuned structure-to-sequence models significantly improving sequence recovery metrics
- Developed a new metric for sequence recovery – [[Substitution-Aware Sequence Recovery]]
- Developed a novel proprietary strategy of epitope selection for VHH antibody design
- Lead generation and propagation of results
- KisoJi Paratope Map poster at BioLogics Summit SanDiego 2025
Junior SW Developer at Technica Engineering GmbH
(Dec 2019 - Aug 2022, Munich, Germany)
- Hardware testing infrastructure development – toolkit development for QA engineers (test automation with tools like Kalash (GPLv3), custom packet parsers and test suite API for CAN, LIN, FlexRay and Ethernet devices)
- Managing CI, workflow automation and code quality assurance systems (GitLab CI, Jenkins, Docker, SonarQube)
BSc Research Student at Systems Biology Department, University of Warsaw / IBB Polish Academy of Sciences
(Oct 2017 - Jul 2018, Warsaw, Poland)
- Designing Gateway constructs for plant transformation
- DNA isolation, PCR, electrophoresis, microbiological cultures
Selected Research Projects
- UArr (Oct 2023 - Nov 2024) [5] – microarray image denosing, improved on 2020 SOTA from $20.05$ PSNR to $19.88$ PSNR, developed a biologically-relevant metric for denoising success
- NutritionVerse Utensil Estimation (Jan 2024 - April 2024, CVPR 2024 MetaFood Workshop paper) [3] – volumetric estimation of food items on the utensil
- NutritionVerse Plate Ellipse Fitting (Jan 2024 - April 2024, CVPR 2024 MetaFood Workshop paper) [2]
- DC-AC for skin cancer detection (Nov 2023) [1] – Double-Condensing Attention Condenser architecture in skin cancer detection
Education
- MASc Systems Design Engineering, University of Waterloo (Sep 2022 - Sep 2024, 89.75% GPA)
- CBB NSERC CREATE Training in Global Biomedical Technology Research and Innovation (Dec 2022 - Aug 2024)
- Data Science Retreat Bootcamp, Berlin (Apr 2019 - Jul 2019)
- BSc Biotechnology, University of Warsaw (Oct 2015 - Jul 2018, 4/5 final grade)
Awards & Recognition
Skills
- Programming: Python, C#, F#, Rust, C++, API development, automation
- Protein modeling and antibody design: ChimeraX, generative models for protein design (RFdiffusion, ProteinMPNN, etc.)
- AI/ML: PyTorch, Scikit-Learn, TensorFlow, Natural Language Processing, Computer Vision, Torchvision, PIL, OpenCV, data collection, data curation, diffusion models, transformer models, convolutional neural networks
- DevOps/MLOps: Docker, Docker-compose, Jenkins, GitLab CI, Snakemake, Apache Airflow, SQL, NoSQL, GitHub
- Immunology: VHH antibodies, bi-specific antibodies, antibody humanization, antibody developability assessment
- Wet Lab: PCR, Electrophoresis, cDNA preparation, microbiological cultures
- Project management, Leadership
Additional info
Languages
| Language | Level |
|---|---|
| 🇬🇧 English | fluent (C2) |
| 🇩🇪 German | advanced (C1) |
| 🇵🇱 Polish | native |
| 🇳🇱 Dutch | basic (A1) |
Publications
[1] C. A. Tai, E. Janes, C. Czarnecki, and A. Wong, ‘Double-Condensing Attention Condenser: Leveraging Attention in Deep Learning to Detect Skin Cancer from Skin Lesion Images’. arXiv, Nov. 20, 2023. doi: 10.48550/arXiv.2311.11656.
[2] A. Pathiranage, C. Czarnecki, Y. Chen, P. Xi, L. Xu, and A. Wong, ‘In The Wild Ellipse Parameter Estimation for Circular Dining Plates and Bowls’. arXiv, May 11, 2024. Accessed: May 14, 2024. [Online]. Available: http://arxiv.org/abs/2405.07121
[3] A. Sharma, C. Czarnecki, Y. Chen, P. Xi, L. Xu, and A. Wong, ‘How Much You Ate? Food Portion Estimation on Spoons’. arXiv, May 11, 2024. doi: 10.48550/arXiv.2405.08717.
[4] D. Lu _et al._, ‘Integrating deep transformer and temporal convolutional networks for SMEs revenue and employment growth prediction’, _Expert Systems with Applications_, vol. 252, p. 124129, Oct. 2024, doi: 10.1016/j.eswa.2024.124129.
[5] C. Czarnecki, “Microarray Image Denoising Leveraging Autoencoders and Attention-Based Architectures with Synthetic Training Data,” Sep. 2024, Accessed: Sep. 17, 2024. [Online]. Available: https://hdl.handle.net/10012/21007
[6] A. Nazemi, M. H. Sepanj, N. Pellegrino, C. Czarnecki, and P. Fieguth, “Particle-Filtering-based Latent Diffusion for Inverse Problems,” Aug. 25, 2024, _arXiv_: arXiv:2408.13868. doi: [10.48550/arXiv.2408.13868](https://doi.org/10.48550/arXiv.2408.13868).