Francisco Pérez
Principal Scientist at Bristol Myers Squibb
Dos Hermanas, Andalusia, Spain
Summary
👤
Senior🎓
Top SchoolFrancisco Pérez is a Principal Scientist with a Ph.D. in machine learning applied to bioinformatics and over a decade of experience bringing advanced AI into pharmaceutical and biomedical research. He has led cross-modal deep learning projects—from CNNs and self-supervised models to diffusion models, GANs and VAEs—applied to digital pathology, multi-omics fusion and synthetic cancer data generation. At Bristol Myers Squibb and during research stints at Stanford and Universidad de Granada he combined high-performance training of large models with practical integration into clinical end-point prediction pipelines. He is comfortable spanning research and production, mentoring students and teaching courses, and has a track record of publishing and collaborating internationally (Fulbright at Stanford). Based in Andalusia, he blends rigorous academic pedigree with hands-on engineering for real-world drug discovery challenges.
11 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Machine Learning applied to Bioinformatics, Doctor of Philosophy - PhD, Machine Learning applied to Bioinformatics at Universidad de GranadaComputer Science, Computer Science, Computer Science, Computer Science at Politecnico di MilanoThe Mediterranean Machine Learning (M2L) summer school (postponed to 11th-16th of January due to Covid19) will be structured around 6 days of keynotes, lectures and practical sessions. The program will include social or cultural activities to foster networking. Participants will be encouraged to (optionally) present their work at evening poster sessions during the school and to interact with our sponsors and with each other during the coffee breaks throughout the week.
Lectures and laboratories taught by local and international AI experts. State-of-the-art content and code will be accessible to all school participants.
Topics:
Computer vision, Natural Language Processing, Generative models, Meta/Multitask learning, Graphnet
,(Deep) reinforcement learning, Robotics, Bayesian and causal inference, Applied deep learning (E.g., healthcare, physics, weather), The Mediterranean Machine Learning (M2L) summer school (postponed to 11th-16th of January due to Covid19) will be structured around 6 days of keynotes, lectures and practical sessions. The program will include social or cultural activities to foster networking. Participants will be encouraged to (optionally) present their work at evening poster sessions during the school and to interact with our sponsors and with each other during the coffee breaks throughout the week.
Lectures and laboratories taught by local and international AI experts. State-of-the-art content and code will be accessible to all school participants.
Topics:
Computer vision, Natural Language Processing, Generative models, Meta/Multitask learning, Graphnet
,(Deep) reinforcement learning, Robotics, Bayesian and causal inference, Applied deep learning (E.g., healthcare, physics, weather) at Mediterranean Machine Learning summer school
English, Italian, Spanish
Stackoverflow
23reputation
1kreached
0answers
3questions
Github Skills (72)
textbook10
economics10
computer-science10
text-to-image10
javascript10
history10
philosophy10
bioinformatics10
psychology10
react10
rna-seq9
gene-expression9
optical-flow9
generative-model8
imaging8
Programming languages (5)
Github contributions (5)
pacocp/SendTweet
Jul 2015 - Jan 2019
Contributions:1 PR, 14 pushes, 1 branch in 3 years 6 months
birdpythontwitterterminal
pacocp/YOLOF
Apr 2019 - Oct 2022
:video_camera: YOLO meets Optical Flow
Contributions:7 commits, 1 PR, 1 push in 3 years 6 months
optical-flowobject-detectionyolo
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