Sasha Chernenkoff sjchernenkoff@gmail.com   ·   GitHub   ·   LinkedIn   ·   Download CV (PDF) Education Master of Science, Specialization in Bioinformatics   ·   Cumming School of Medicine, University of Calgary, Canada   ·   Expected February 2027
GPA: 4.0/4.0
Thesis: Transfer learning reveals post-transcriptional sequence determinants of protein abundance
Areas of interest: machine learning, representation learning, computational genomics, statistical genetics Bachelor of Science, Honours in Chemistry   ·   Dietrich School of Arts and Sciences, University of Pittsburgh, USA
GPA: 4.0/4.0
Thesis: Selective inhibition of histone lysine demethylases using sterically modified inhibitors Experience Research Associate   ·   University of Calgary, Canada
August 2023 - Present
• Fine-tuning a genomic foundation model to predict protein abundance from DNA sequence, and using in silico mutagenesis to study what the retargeted model learns (PASTL)
• Developing a categorical VAE that compresses genome-wide genotypes into low-dimensional representations for SNP heritability estimation (HERL)
• Building a multi-GPU training system with LoRA adapters and custom loss functions for personalized gene expression prediction from diploid genomes R&D Scientist II / I   ·   PerkinElmer Genomics
June 2020 - July 2023
Developed second-tier biochemical diagnostic tests for newborn screening programs: LC-MS/MS biomarker panel for MPS I & II; Western blot CRIM-status assay for Pompe disease Undergraduate Research Associate   ·   University of Pittsburgh, USA
September 2018 - June 2020
Synthesized small-molecule inhibitors of enzymes involved in transcriptional regulation and used mutagenesis to generate enzyme variants for evaluating inhibitor selectivity and binding mechanisms Publications Chernenkoff, S., Enoma, D., Weeraman, J. & Long, Q. Transfer learning reveals post-transcriptional sequence determinants of protein abundance. In preparation (2026). Kemogne, A., Weeraman, J., Wang, D., Enoma, D., Li, C., Sridharan, G., Chernenkoff, S., Chekouo, T., Zhang, Q. & Long, Q. Genomic variational autoencoder enables stable representation learning in high-dimensional genomic data with moderate sample sizes. Under review (2026). Kuwik, J., Hinkelman, K., Waldman, M., Stepler, K. E., Wagner, S., Arora, S., Chernenkoff, S., Cabalteja, C., Sidoli, S., Robinson, R. A. S. & Islam, K. Activity guided azide-methyllysine photo-trapping for substrate profiling of lysine demethylases. J. Am. Chem. Soc. 145, 21066-21076 (2023). Abstracts Donti, T., Smith, S., Chernenkoff, S., Ellgass, M. & Hegde, M. P012: Measuring non-reducing terminal glycosaminoglycan fragments increases specificity and differentiates mucopolysaccharidosis type I (MPS I) from mucopolysaccharidosis type II (MPS II). Genet. Med. Open 1, 100022 (2023). Poster Presentations Chernenkoff, S., Enoma, D., Weeraman, J. & Long, Q. Transfer learning reveals post-transcriptional sequence determinants of protein abundance. ASHG Annual Meeting, Montreal, QC (2026). Chernenkoff, S., Zhang, Q. & Long, Q. Variant annotation for low-prevalent disorders empowered by transfer-learning. ACHRI Research Retreat, Banff, AB (2023). Smith, S. E., Gelb, M. W., Herbst, Z. M., Dellagatta, J. N., Chernenkoff, S., Donti, T. & Khaledi, H. Measurement of non-reducing terminal glycosaminoglycan fragment increases specificity of second-tier testing for mucopolysaccharidosis type I (MPS I). APHL Newborn Screening Symposium, Tacoma, WA (2022). Awards & Scholarships ACHRI Graduate Scholarship
September 2026 Canada Graduate Scholarships - Master's Program (CIHR)
April 2024 Phillips Medal
February 2020 American Chemical Society Undergraduate Award in Organic Chemistry
October 2019 Skills Languages & ML:    Python   ·   PyTorch   ·   PyTorch DDP   ·   LoRA/PEFT   ·   pandas   ·   NumPy   ·   SciPy   ·   scikit-learn   ·   statsmodels   ·   WandB   ·   SQL   ·   transfer learning   ·   representation learning   ·   variational autoencoders   ·   attention pooling   ·   custom loss functions   ·   mixed precision (bfloat16)   ·   gradient checkpointing   ·   genomic foundation models (Enformer, Borzoi, Evo2) Statistics & genomics:    regression modelling   ·   nested cross-validation   ·   partial correlation   ·   hypothesis testing   ·   bootstrap CIs   ·   multiple-testing correction   ·   Bayesian inference (MCMC)   ·   GWAS/PWAS   ·   SNP heritability (GCTA-GREML)   ·   in silico mutagenesis   ·   variant calling (GATK)   ·   variant annotation   ·   sequence alignment   ·   PLINK   ·   pysam   ·   bcftools Computing & infrastructure:    SLURM (HPC clusters)   ·   Linux/bash   ·   Git/GitHub   ·   HDF5/h5py   ·   Docker   ·   Nextflow   ·   AWS (Batch, S3, ECR, IAM) Wet lab:    LC-MS/MS   ·   Western blotting   ·   organic synthesis   ·   mutagenesis   ·   protein expression and purification