Public relations
I am available for speaking to tech audiences at conferences, symposiums, hackathons, and meetups. Topics range from generative AI (specifically, genAI for image generation) to AI for population genetics and genetic genealogy. My talks are described as very crisp and niche. Contact at geleta [at] berkeley [dot] edu.
Previous talks include: top-tier conferences (AAAI & ICASSP); Deep Learning Barcelona Symposiums; American Society of Human Genetics Meetups; SF Tech meetups.
Event organization
I carried out the organization of dozens tech workshops, and in-person and online career fairs with +200 participants, organization of Europe's biggest student hackathon with +700 participants, and took on positions of responsibility within two associations and the governance of Barcelona School of Informatics (FIB). My events are characterized by efficient logistics, positive attendee feedback, and large participation (all +100).
In 2022, I was the SF Techstars Community Leader & organized a 3-day startup hackathon in San Francisco, with +150 participants, 17 teams, 5 workshops, 2 talks (Doordash & Meta Research), 32 ideas pitched.
Currently, I'm the social chair at the Computer Science Graduate Entrepreneurs organization at UC Berkeley.
Check my CV for the full list of events that I organized in the past.
I am open for event organization collaborations.
Research
Currently, I'm doing research on generative modeling & genetic genealogy.
My DMs are always open! Although, I do not have open positions for research projects at present.
I am into genealogy. If you think we are distant cousins, send me an e-mail: geleta [at] berkeley [dot] edu.
Through my genealogy research, not only have I gained a deep understanding of my family's past, but I have also contributed to the preservation of Pentecostal movement history in Siberia. Because of my strong efforts in genealogical research, in 2023, I have been awarded the Samuel Silver Memorial Scholarship Award.
Some of my papers are listed below. Check my CV for the full list.
Near Perfect GAN Inversion
Qianli Feng*, Raghudeep Gadde, Viraj Shah, Margarita Geleta, Pietro Perona, Aleix M. Martinez [Under Review]
Imagine being able to effortlessly manipulate, edit and morph photos with just a few clicks. Well, with our new algorithm, you can do just that! We've presented a method that achieves nearly perfect reconstructions of images from the latent space of Generative Adversarial Networks (GANs), while preserving strong editability capabilities.
Adversarial Learning for Feature Shift Detection and Correction
Míriam Barrabés*, Daniel Mas Montserrat*, Margarita Geleta, Xavier Giro-i-Nieto, Alexander G. Ioannidis [NeurIPS 2023] & [DLBCN 2023]
Think of it as a band of discriminators, trained to spot the difference between two data distributions. Now, these discriminators do more than just point fingers: they lend a hand in both spotting and correcting those features, getting rid of the feature shifts in the dataset.
Autoencoders for Genomics
Margarita Geleta*, Daniel Mas Montserrat, [Carlos D. Bustamante], Xavier Giró-i-Nieto, Alexander G. Ioannidis [ASHG 2021] & [DLBCN 2021]
In this exhaustive study, we explore the many ways in which VAEs can be used for dimensionality reduction, classification, compression, imputation and simulation of genomic data. But that's not all! We also delve into interesting discussions about human populations, unlocking new insights into the diverse genetic makeup of our world.
Towards Robust Image-in-Audio Steganography
Jaume Ros Alonso*, Margarita Geleta*, Jordi Pons, Xavier Giro-i-Nieto [WiCV/CVPR 2023]
Want to hide your images in audio with the utmost finesse? Look no further than our enhanced steganography method! We present an improved version of a deep steganographic model for hiding images in audio.
Maestro: A Gamified Platform for Teaching AI Robustness
Margarita Geleta*, Jiacen Xu, Manikanta Loya, Junlin Wang, Sameer Singh, Zhou Li and Sergio Gago Masague [AAAI 2023] & [SIGCSE 2023]
Are you passionate about robust AI and want to put your skills to the test? I am the proud maintainer of the Maestro platform and expert tester of the framework. This platform offers a unique opportunity for adversarial AI enthusiasts to engage in a thrilling and educational domain of adversarial attacks and defenses.
PixInWav: Residual Steganography for Hiding Pixels in Audio
Margarita Geleta*, Cristina Punti, Kevin McGuinness, Jordi Pons, Cristian Canton, Xavier Giro-i-Nieto [ICASSP 2022] & [WiCV/CVPR 2021] & [DLBCN 2022]
Are you ready to unlock the secrets of "the art of hiding"? Our pioneering work on hiding images within audio waveforms is sure to leave you in awe. It's the ultimate fusion of sight and sound, allowing you to hide information in plain sight and unlock a whole new world of possibilities.
Generative Moment Matching Networks for Genotype Simulation
Maria Perera*, Daniel Mas Montserrat, Míriam Barrabés, Margarita Geleta, Xavier Giró-i-Nieto, Alexander G. Ioannidis [EMBC 2022] & [ASHG 2022]
Discover the power of Generative Moment Matching Networks (GMMNs) in SNP simulation and privacy-preserving data sharing for biobanks. Our research shows GMMNs can mitigate population bias and improve data accuracy, unlocking new insights for genetic research.
MT-adapted datasheets for datasets: Template and repository
Marta R. Costa-jussà, Roger Creus, Oriol Domingo, Albert Domínguez, Miquel Escobar, Cayetana López, Marina Garcia, Margarita Geleta [LREV 2020]
We created a MT Datasheets repository, where the research community could upload the description of their datasets for Machine Translation (MT). This served as an attempt to provide reliability and transparency of the composition, collection and preprocessing steps in the datasets creation.