Gabriella Garcia

Gabriella Garcia

Deal Partner

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Gabriella Garcia is a Deal Partner at Felicis. Prior to Felicis, Gabriella was an investor at Two Sigma Ventures, a New York based venture capital firm where she focused on DeepTech and Applied AI, and partnered with companies including FreeForm, ZeroMatter, Raincoat, Objective and more. Before Two Sigma, she built prosthetics at MIT’s Media Lab, mechanical systems at Apple and led product in augmented reality and fintech infrastructure at Google. Gabriella holds a joint degree in Mechanical Engineering and Computer Science from MIT. She lives in New York with her fiancé Ayush.

Let's get back to empire building.

How has your upbringing shaped your worldview?

I’m Colombian-American and lived between Bogota and Miami growing up. Colombia is the land of magical realism, with hills described as families of sleeping giants and where surrealism runs through the streets. As a result, I’ve always found magic to be a quiet part of reality, especially within science and engineering.  With each passing week, we’re seeing more breakthroughs that are borderline magical: from advancements in space tech and exciting applications of embodied AI to the latest in biotech innovations.   While a lifelong optimist, I’m also a realist — learning to bribe soldiers with water bottles and De Toditos and hiding my sibling’s blonde hair through checkpoints - taught me to be pragmatic, strategic, and scrappy. Those qualities are reflected in my life and work — empires are built with your heart, and the great ones are durable.

What area are you passionate about, and why are you so bullish about it?

It’s an excellent time for accelerating sciences, like applying new ML techniques to the physical world. New deep-learning approaches dramatically change the way we approach scientific discovery, going beyond traditional methods by using GNNS and simulations, making forecasting and experimentation more accurate, scalable, and efficient, and can even leverage cross-domain knowledge by analyzing diverse data modalities. Large academic labs (i.e. DeepMind’s AlphaFold, GNoME, and GraphCast) are seeing ML play a crucial role in areas like forecasting the weather, generating new metal alloy compositions, optimizing the design of fusion reactors, or calculating the binding affinities of candidate drug molecules to a target protein – opening up new possibilities for treatments and sustainable technologies.  Data-driven startups have a first-mover advantage to commercialize their full-stack platforms, don’t have the tech debt of previous approaches, and I believe will be key in pushing forward this ‘fifth paradigm’ of scientific computing by hiring cutting-edge talent from academic labs and research institutions. I’m bullish on “AI4Science” and founders at the forefront of exploring these vast markets and how they’re changing our understanding of the natural world.

Gabriella Garcia with a fish she caught in India
Fishing in Kerala, India! While not the biggest haul, I was pretty proud given the bamboo fishing rod.

What would you be doing if you weren’t an investor?

I’d be an archaeologist. At MIT,  it’s required to take humanities classes and I immediately fell in love with my archaeology lessons. While it's definitely not as sexy as Indiana Jones makes it out to be, new breakthroughs in material science, lidar to uncover lost sites, and even ML to decipher ancient scrolls are completely changing the field. I’d want to start by targeting regions with little prior art, i.e. the Colombian Amazon basin. To understand who we can be in the future, I think it's essential to uncover who we were, how we lived and what we built and discovered.

What’s something recent that you’ve learned?

I just wrapped up Deb Chachra’s “How Infrastructure Works: Inside the Systems That Shape Our World” and it was fascinating to see the similarities between physical infrastructure (electricity, water, sewage, telecom, etc) and software infrastructure (banking rails, databases, email APIs, etc). Infrastructure is famously boring because the best outcome is nothing happening — at least, nothing unexpected. But “nothing happening” results from a lot of careful attention, inspection, preventative maintenance, and a ton of resources. Back at Google, I spent most of my time explaining how much work goes into “keeping the lights on.” Silicon Valley’s culture celebrates making things over caregiving and maintenance, what is novel over what is sustained. I think that's a very wrong mentality — infra is essential and will become even more critical in the coming decade. Most structures fail gradually, as we are seeing with the aero industry at the moment, and we need to view this as an opportunity to rethink how we design infra to be modular, decentralized, and resilient.

How do you recharge or find balance?

I love to cook! I find it immensely relaxing and fulfilling—pull out a ton of random stuff from the fridge and see what you can make. No, I don't have a “go-to dish,” but I tend to cook a lot of Indian and Mediterranean dishes, which are my partner’s favorite cuisines. If you’re ever in NYC, I host “Hot Takes Dinners” in my apartment and would love to have you over for a home-cooked meal.