Eduardo Abeliuk, Ph.D.

Brief bio

Eduardo Abeliuk is a scientist, founder and investor who builds AI-driven technologies that advance human potential. Over two decades his work has spanned computational biology, productivity and online networks. Today, at TeselaGen, the AI-for-biology company he co-founded with Stanford colleagues, his team develops software and agents that speed up biological design and manufacturing, and he is a co-inventor on U.S. patents for generative and predictive design. His research has been cited more than 1,500 times.

Background

The thread through his work is information systems: algorithms that design biology, AI agents that make people more productive, networks that compound value. He has spent his career building them, and backing others who do.

At Stanford, where he earned a Ph.D. in Electrical Engineering and an M.S. in Bioengineering and was a member of the Information Systems Laboratory, Eduardo studied how bacterial cells divide and regulate their cell cycle, using high-throughput genetics and genomics. As co-first author he mapped the essential genome of a bacterium, the set of genes and regulatory sequences it cannot live without. That work and other papers have appeared in Nature Communications, Molecular Systems Biology, PLOS Genetics, Molecular Microbiology and PLOS One, among others. He also taught in Stanford courses on international technology research and on entrepreneurship in Asian high-tech industries.

While still a graduate student he built KissMe, one of the first viral Facebook applications. It reached a million users within weeks and was acquired a year later. He went on to co-found TeselaGen, a spin-out of Lawrence Berkeley National Laboratory and Stanford that builds AI for designing and engineering biological systems.

As an investor he has backed more than 30 founders and projects across the United States and Latin America, in education technology, fintech, proptech, blockchain and social networks, and has supported multiple tech funds. He funds undergraduate fellowships through the Abeliuk Institute.

Education

2011
Ph.D. Electrical Engineering, Stanford University
GPA 4.1/4.0
2008
M.S. Bioengineering, Stanford University
GPA 4.0/4.0
2003
Eng. Electrical Engineering, University of Chile
Highest Honors
2003
B.S. Physics, University of Chile
Highest Honors
2002
B.S. Electrical Engineering, University of Chile
Highest Honors

Honors

Eduardo won first place in Chile's National Physics Olympiad and second place in its National Mathematics Olympiad, and graduated as valedictorian of Santiago College. The Chilean Institute of Engineers gave him the Roberto Ovalle Aguirre Award for the best engineering thesis of 2004, and his undergraduate work on embedded signal processing received IEEE paper awards.

Patents

2025
Method, apparatus, and computer-readable medium for efficiently optimizing a phenotype with a specialized prediction model
Abeliuk E. et al.
US Patent App. US18/295158
2025
Method, apparatus, and computer-readable medium for efficiently optimizing a phenotype with a combination of a generative and a predictive model
Abeliuk E. et al.
US Patent US12217828 · Granted 02/04/2025
2023
Method, Apparatus, And Computer-readable Medium For Optimized Partitioning For Assembly Of Nucleic Acid Sequences
Abeliuk E. et al.
US Patent App. 18/790662
2023
Method, apparatus, and computer-readable medium for efficiently optimizing a phenotype with a specialized prediction model
Abeliuk E. et al.
US Patent US11620544 · Granted 04/04/2023
2023
Method, apparatus, and computer-readable medium for efficiently optimizing a phenotype with a combination of a generative and a predictive model
Abeliuk E. et al.
US Patent US17240553 · Granted 02/07/2023
2021
Method, apparatus, and computer-readable medium for optimal pooling of nucleic acid samples for next generation sequencing
Abeliuk E. et al.
US Patent App. 17/219,474
2015
Compositions and methods for identifying the essential genome of an organism
Christen B., Fero M., Abeliuk E.
US Patent US9150916 · Granted 10/06/2015

Book chapters

2012
A strategy for identifying noncoding RNAs using whole-genome tiling arrays
Landt S.G., Abeliuk E.
Bacterial Regulatory RNA (ed. Keiler K.), Methods in Molecular Biology

Selected peer-reviewed publications 1,500+ citations

2020
Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism
Zhang J., Petersen S.D., Radivojevic T., Ramirez A., Perez-Manriquez A., Abeliuk E., Sanchez B.J., Costello Z., Chen Y., Fero M.J., Martin H.G., Nielsen J., Keasling J.D., Jensen M.K.
Nature Communications
2015
The global regulatory architecture of transcription during the Caulobacter cell cycle
Zhou B., Schrader J.M., Kalogeraki V.S., Abeliuk E., Dinh C.B., Pham J.Q., Cui Z.Z., Dill D.L., McAdams H.H., Shapiro L.
PLOS Genetics
2011
The essential genome of a bacterium
Christen B.*, Abeliuk E.*, Fero M.J., Collier M.J., Kalogeraki V., Passarelli B., Coller J.M., McAdams H.H., Shapiro L.
Molecular Systems Biology
2011
Assembly of the Caulobacter cell division machine
Goley E.D., Yeh Y.C., Hong S.H., Fero M.J., Abeliuk E., McAdams H.H., and Shapiro L.
Molecular Microbiology
2011
Regulatory Response to Carbon Starvation in Caulobacter crescentus
Britos L, Abeliuk E, Taverner T, Lipton M, McAdams H.H., Shapiro L.
PLOS One
2008
Small non-coding RNAs in Caulobacter crescentus
Landt S.G., Abeliuk E., McGrath P.T., Lesley J.A., McAdams H.H., Shapiro L.
Molecular Microbiology
2007
Current progress in network research: toward reference networks for key model organisms
Srinivasan BS, Shah NH, Flannick JA, Abeliuk E, Novak AF, Batzoglou S.
Briefings in Bioinformatics