CV

CV

Libère Jensen Ndacayisaba

San Francisco, CA

Profile

Humankind’s most valuable asset and resource are health and time, respectively. Disease afflicts health and depletes time. There is no greater life purpose than the eradication of maladies and the betterment of human health. Humbled by the multiscale and spatiotemporal complexity of disease pathogenesis, I’m inspired by innovative science and technologies to decipher disease biology and make new medicines, and passionately committed to making therapeutic discovery more precise, predictable, and programmable.

Education

Ph.D. — Medical Biophysics, University of Southern California, Los Angeles, CA. Aug 2017 - May 2022
Highlights: 2022 Keck School of Medicine Commencement PhD Student Speaker, Order of Arete, Schlegel Family Endowed Fellow, PhD GEM Associate Fellow.
B.Sc. — Biotechnology, Syracuse University, Syracuse, NY. 2015
Highlights: Dean’s scholar, Ronald E. McNair Scholar, LSAMP Scholar.

Experience

Vitra Labs, San Francisco, CA, July 2023 - Present
Senior Computational Biologist

  • Building computational and data engineering infrastructure and capabilities for next-generation IVF.
  • Developing AI/ML and mechanistic modeling for prediction in single cell biology and applications in cell-based therapies for reproductive health.

NextRNA Therapeutics, Boston, MA, May 2022 - June 2023
Computational Biologist II, Team Lead for Data Science and Modeling

  • Built machine intelligence prediction capabilities in non-codingRNA(ncRNA) biology and RNA-directed therapeutics.
  • Spearheaded the development and validation of computational methods for lncRNA target identification, ncRNA-protein interactions, RNA structure prediction and analysis.
  • Lead a team comprised of a data scientist II, a masters co-op intern, and two expert consultants; spearheading collaborative projects with Platform Technology, RNA & Protein Sciences, Biology, and Drug Discovery Chemistry.
  • Successfully recruited two co-op interns and two expert consultants to support efforts within the Data Science and Modeling activities.

USC Michelson Convergent Science Institute in Cancer, Los Angeles, CA, May 2018 - May 2022
PhD Graduate Research Assistant

  • Led 6 research projects (over 5 manuscripts) applying single cell multiomics and deep learning to map and predict cancer progression.
  • Developed two 4-plex immunofluorecence assays & one 37-plex targeted proteomics assay for myeloma rare cell characterization.
  • Developed deep learning models using multimodal data to predict survival in solid tumors,resulting in a first-authored book chapter.
  • Spearheaded a cross-institutional collaboration, responsible for annual research progress reports, resulting in first-author publications.
  • Mentored over 8 junior colleagues in technical projects, scientific reading and writing, and professional development.

Nucleate, Los Angeles, CA, August 2021 - May 2022
Strategy Lead

  • Created a long-lasting strategic vision for enabling the creation and growth of early-stage life science companies in Los Angeles.
  • Mapped and connected the LA biontrepreneurial ecosystem to empower the formation of trainee-led bioventures.
  • Sourced top-caliber biotech ideas and business trainees and facilitating formation of founding teams via Nucleate Activator program.
  • Co-led efforts for expanding the innovation fellowship, creation of the NADP program, and research initiatives

USC Graduate Student Government, Los Angeles, CA May 2020 - May 2021
Director of Globalization and Inclusion

  • Served on the Executive Board governing a body of over 27,000 graduate and professional students.
  • Oversaw all strategic initiatives for undocu+ and international graduate students across 22 schools, colleges, and academic units.
  • Worked with university leadership to implement strategic national and global policies that impact and enhance the academic experience.

Novartis Institutes for BioMedical Research (NIBR), Cambridge, MA, Jan 2016 - Jun 2017
Postbac Intern, Data Science, CBT Data Science Group, Chemical Biology and Therapeutics (CBT)

  • Developed proteochemometric machine learning models for predictive drug discovery, target identification, and polypharmacology.
  • Evaluated the model performance and therapeutic predictability within and across protein families of the targetable human proteome.
  • Experimentally validated predicted interactions and delineated the polypharmacology of predicted targets and small molecule candidates.

Novartis Institutes for BioMedical Research (NIBR), Cambridge, MA, Jun 2015 - Aug. 2015
Intern, Computational Biology, Screening Informatics Group, Developmental and Molecular Pathways (DMP)

  • Developed machine learning models to predict siRNA off-targetting and discover pathway nodes in phenotypic screening.
  • Investigated top features of miRNA and siRNA that predict off target effects in RNA interference experiments.
  • Demonstrated the utility of prediction models for optimizing experimental design for phenotypic screening in target ID and drug discovery.

Syracuse University, Syracuse, NY, 2014 - Dec 2015
McNair Scholar Undergraduate Researcher, Lab of Yan-Yeung Luk, Department of Chemistry

  • Computationally investigated protein targets for novel disaccharide derivatives (DSDs) with optimally active stereochemistry.
  • Sampled the protein conformations of identified adhesion proteins and their binding affinity to bioactive DSDs.
  • Explored the utility of DSDs as inhibitors of biofilm formation in Pseudomonas aeruginosa, as a in vitro model of Cystic Fibrosis.s

University of California San Francisco, San Francisco, CA, Summer 2014
Undergraduate Researcher, Lab of Michael Grabe, Cardiovascular Research Institute

  • Homology modeled the structure of human sodium-glucose co-transporters (hSGLTs) based on structure of bacterial homologues.
  • Explored structural conformations of hSGLT1 and hSGLT2 models for optimal binding of Phlorizin, a competitive binder of D-glucose.
  • Investigated inhibitors of human SGLTs by computational screening libraries of active compounds and molecular docking of candidates.

New York State Department of Health, Albany, NY. Summer 2013
NSF-REU Undergraduate Researcher, Labs of Nilesh Banavali and Hongmin Li, The Wadsworth Center

  • Computationally analyzed the structural and biophysical properties of the Dengue virus (DENV) NS2/NS3 protease complex.
  • Performed molecular screening, docking, binding affinity analysis, and identified top 40 candidate inhibitors.
  • Cultured and purified the NS2/NS3 complex and performed in vitro screening for experimental validation of top DENV protease inhibitors.

University of California Berkeley, Berkeley, CA. Summer 2012
Undergraduate Researcher, Environmental Leadership Pathway, ESPM Department

  • Performed DNA extraction, amplification, and sequencing of COX1 and 28S, two evolutionarily conserved genes in Tahitian plant bugs.
  • Applied bioinformatics with Bayesian inference methods to calculate phylogenetic probabilities of speciation
  • Investigated the morphological and genetic speciation of Pseudoloxops (Hemiptera: Miridae) and identified 5 candidate new species.

Skills

Data Analytics and Computing: scikit-learn, CARET, PyTorch, Tensorflow, Git, Atom, cloud (AWS), Autodock Vina, RDKit
Machine Learning: Supervised and unsupervised learning, classification and regression (RF, NB, SVm), deep neural networks
Programming: Python, R, SQL, Bash, Atom, LaTeX
Experimental Biology: Single cell multiomics, immunofluorescence staining, microscopy, imaging mass cytometry, protein purification, molecular biology methods
Spoken Languages: English (professional fluency), French (professional fluency), Kirundi (native), Swahili (elementary)

Publications

  1. Setayesh S.M., Ndacayisaba L.J., et al., 2023 Sep 18 Targeted Single Cell Proteomic Analysis Identifies New Liquid Biopsy Biomarkers Associated with Multiple Myeloma. npj Precision Oncology. doi.org/10.1038/s41698-023-00446-0
  2. Ndacayisaba, L.J., Mason, J., Kuhn, P. (2023). Mathematical Oncology to Integrate Multimodal Clinical and Liquid Biopsy Data for the Prediction of Survival. In: Cote, R.J., Lianidou, E. (eds) Circulating Tumor Cells. Current Cancer Research. Springer, Cham. doi.org/10.1007/978-3-031-22903-9_7
  3. Dang M., Wang R., …Ndacayisaba L.J., …et al., 2023 Jun 12. Single Cell Clonotypic and Transcriptional Evolution of Multiple Myeloma Precursor Disease. Cancer Cell. doi.org/10.1016/j.ccell.2023.05.007
  4. Ndacayisaba L.J.. (2022). Multimodal Single-cell Biology and Machine Learning to Characterize Plasma Cell Neoplasms. PhD Dissertation. University of Southern California. Los Angeles, CA.
  5. Ndacayisaba L.J., et al., 2022 Nov 3 Characterization of BCMA Expression in Circulating Rare Single Cells of Patients with Plasma Cell Neoplasms. Int J Mol Sci. doi: 10.3390/ijms232113427
  6. Ndacayisaba L.J. et al., 2022 Apr 21, Enrichment-Free Single-Cell Detection and Morphogenomic Profiling of Myeloma Patient Samples to Delineate Circulating Rare Plasma Cell Clones. Current Oncology doi.org/10.3390/curroncol29050242

Selected Presentations

Invited Talks and Lectures

  • PIBBS Summer Bootcamps for incoming 1st year PhD students, Summer 2019, 2020, & 2021. Los Angeles, CA
    Topics: Programming for Bioscientists. Taught first year PhD students on foundations of computational sciences for bioscientists, with hands-on programming and data visualization in R and Python. ~30 PhD students each summer.
  • Syracuse University McNair Scholars Annual Symposium Jul. 2020 Jul 17 2020 Virtual
    Title: Single Cell Biology and Math Modeling to Delineate the Spatiotemporal Progression of Myeloma
  • ACE the CURE: Summer Undergraduate Program Summer 2020. Jul 2020 Virtual
    Topics: Predictive Math Modeling. Taught a one week-long bootcamp on predictive machine learning to 17 undergraduates
  • IMC User Group Meeting at Cedars Sinai: Accelerating Translational Science Through Mass Cytometry. Nov. 2019. Los Angeles, CA
    Title: Imaging Mass Cytometry in Liquid Biopsy: Proteomic Characterization of Circulating Rare Events in Single Cell Oncology
  • Novartis Postbaccalaureate Scholars quantitative Biology (qBio) Bootcamp, Co-lecturer. Dec 2016. Cambridge, MA
    Topics: introductory command line Bash scripting, Python programming, data analysis, and visualization (class of 8 post-baccalaureate scholars) students during a 2-day long quantitative biology bootcamp.
  • Invited Seminar Speaker, Novartis Summer Scholars Weekly Seminar Series. Jul 2016 . Cambridge, MA
    Topic: Science Communication, Chalk Talk. Led an hour long seminar to 22 undergraduate summer scholars on giving an effective chalk talk

Conference Presentations

  • Proteochemometric Machine Learning Models for Predictive Drug Discovery. Poster. New England Science Symposium (NESS). Apr 2017 Boston, MA
  • Proteochemometric Machine Learning Models for Predictive Drug Discovery, Target Identification, and Polypharmacology Deconvolution. Poster. Annual Winter Q-bio Meeting. Feb 2017 Kauai, HI
  • Proteochemometric Machine Learning Models for Predictive Drug Discovery, Target Identification, and Polypharmacology Deconvolution. Talk & Poster. ISCB Student Council Symposium at ISMB. Jul 2016 Orlando, FL
  • Exploring miRNA Silencing Mechanisms Using Machine Learning Algorithms to Discover Biologically Relevant Pathway Nodes Poster. New England Science Symposium (NESS). Apr 2016 Boston, MA
  • Exploring miRNA Silencing Mechanisms Using Machine Learning Algorithms. Poster. Annual Biomedical Research Conference for Minority Students (ABRCMS). Nov 2015 Seattle, WA
  • Exploring miRNA Silencing Mechanisms Using Machine Learning Algorithms. Talk. Leadership Alliance National Symposium (LANS). Jul 2015 Stamford, CT
  • Prediction and Characterization of Putative Ligand-receptor Interactions in Pseudomonas Aeruginosa. Talk. Ronal E. McNair Scholars Research Symposium. Apr 2015 Syracuse, NY
  • Ligand Discovery from a Crystal Structure and Homology Models of Sodium-glucose Co-transporters. Poster. Annual Biomedical Research Conference for Minority Students (ABRCMS). Nov 2014 San Antonio, TX
  • Ligand Discovery from a Crystal Structure and Homology Models of Sodium-glucose Co-transporters. Talk & Poster. UCSF Summer Research Symposium. Aug 2014 San Francisco, CA
  • Identification of Orthosteric Dengue Protease Inhibitors using Computer-aided Drug Design. Talk. NSF-REU Symposium at The Wadsworth Center. Aug 2013 Albany, NY
  • Molecular Taxonomy: Exploring the Speciation of Tahitian Plant Bugs. Poster. UC Berkeley ELP Annual Symposium. Jul 2012 Berkeley, CA

Awards and Honors

  • May 2022: PhD Commencement Student Speaker, Keck School of Medicine of USC’s 2022 graduation
  • May 2022: Recipient, Order of Arete, USC
  • Jul 2021: Recipient, Schlegel Family Endowed Fellowship awarded by USC
  • Oct 2019: Winner of Alix Ventures Award and Finalist at Health++ hackaton by Stanford University
  • Oct 2019: 2nd place Award, PIBBS Sci-5: Annual Research Presentation competition by Keck School of Medicine
  • 2017 PhD GEM Associate Fellow, The National GEM Consortium and University of Southern California
  • 2017 Univeristy Nominee, AAAS/Science Program for Excellence in Science, by USC
  • Jul 2016: F1000 Outstanding Poster Award, ISCB Student Council Symposium at ISMB. 1st out of 30 posters.
  • Jun 2015: Research Presentation Award, Novartis Slide Slam Competition. 3rd out of 21 flash talks.
  • May 2015: Don C. Sawyer III Community Legacy Award, to Syracuse University’s top minority graduating senior
  • Nov 2013: Dean’s Scholarship, Syracuse University merit-based renewable annual Scholarship

Service to the Profession

Society Membership

  • Nov 2021 - Present: Member, American Association for Cancer Research (AACR)
  • Jun 2019 – Present: Member, Society of Hematology Oncology (SOHO)
  • Oct 2015 – Present: Member, International Society for Computational Biology (ISCB) & ISCB Student Council
  • Jul 2017 – 2019: Member, American Association for the Advancement of Science (AAAS)
  • Dec 2014 – Mar 2018: Member, American Society for Pharmacology and Experimental Therapeutics (ASPET)

Leadership & Professional Activities

  • Sept 2017 – Present: President and lecturer, Code On! Lead the team and teach programming to the Keck School of Medicine of USC community
  • Jul 2017 – Present: PIBBS Ambassador, Recruitment and interviewing prospective Keck SOM PhD students
  • Oct 2016 – Jun 2017: Advisory Committee Member, TutoringPlus of Cambridge
  • Aug 2014 – Dec 2015: Founder & President, TheFirst, Syracuse University’s first generation students organization
  • Oct 2012 – Jan 2014 Teaching Assistant in Biotechnology & Biochemistry. Learning Alliance for Bioscience (LAB) program at Ohlone College