<![CDATA[LUCIANA MELINA LUQUE

<![CDATA[LUCIANA MELINA LUQUE - Blog]]>Tue, 07 Apr 2026 09:40:29 +0100Weebly<![CDATA[A summer with google at the land of the in-Between]]>Sun, 01 Mar 2026 00:00:00 GMThttps://www.lmluque.com/blog/cartopiax-and-the-land-of-the-in-betweenAlmost a year ago I started collaborating with the Compiler Research group through the Google Summer of Code programme. What I expected to be a technical collaboration quickly turned into a real cross-disciplinary adventure. This time I found myself advising not only on programming and mechanistic models, but also on the biology behind the system — a beautiful reminder that the most interesting scientific problems rarely belong to just one field.

Together we built CARTopiaX, a platform that combines my agent-based model with BioDynaMo to explore biological questions, with the long-term hope that this kind of work might one day help guide therapies all the way to the patient. It was one of those projects where physics, computation and biology kept talking to each other until something meaningful started to emerge.

They kindly invited me to write a blog post about something I care deeply about: the importance of cross-disciplinary research. The piece was published on their website, but I wanted to share it here as well for those of you who wander through this corner of the internet with me.

Writing it was a real pleasure. I hope you enjoy reading it as much as I enjoyed putting those thoughts into words.

CARTopiaX and the Land of the In-Between

After moving from loop quantum gravity to statistical mechanics and eventually into cancer research, I arrived at a conclusion that would once have surprised me: the most consequential scientific problems do not live inside disciplines. They live in the in-between.

Not because physics is incomplete. Not because biology is messy. Not because computation is insufficient. But because the systems we now try to understand — and intervene in — are too complex to respect the lines we draw between departments.

Cancer is one of those systems.

I work on immunotherapies, particularly CAR T-cell therapy [1]. CAR T cells are a patient’s own immune T cells, genetically engineered to recognise and attack specific cancer-associated targets. In certain cancers they have produced extraordinary clinical responses — eliminating advanced disease where other treatments failed, sometimes persisting long term and reducing relapse.

And yet the system is far from uniform. Some patients respond; others do not. Toxicities can be severe. Bone marrow behaves differently from peripheral blood. The cerebrospinal fluid is not equivalent to a solid tumour microenvironment. Activation, proliferation, exhaustion, cytokine diffusion, spatial constraints — all interact.
We are not dealing with a single pathway. We are dealing with a coupled, stochastic, spatially structured system. And large portions of that system remain only partially characterised.

Biology is full of such unknowns. We often know components but not governing dynamics. We identify markers but lack formal equations. We describe behaviour without fully formalising the mechanism.

Looking at such a system from only one disciplinary angle is like walking through a landscape at ground level. You see detail — texture, local interactions. Change the perspective — step back, change the formalism — and gradients, flows and constraints become visible. It is the same terrain, but different variables emerge.

For quantitatively trained scientists, this presents a choice. One can treat biological complexity as something to simplify away. Or one can treat it as a systems problem to formalise.

I clearly chose the second option.

From Mechanistic Model to CARTopiaX

A couple of years ago I developed a mechanistic agent-based model (ABM) to formalise CAR T-cell dynamics and test alternative dosing strategies under controlled in silico conditions. In this framework, individual cells are represented as discrete agents governed by explicit interaction rules. Activation, tumour killing, proliferation and exhaustion are encoded as probabilistic state transitions constrained by biologically informed parameters. Spatial positioning influences encounter rates. Time discretisation governs stability. Local interactions scale to system-level behaviour.

The model was designed not only to understand mechanisms but to explore hypotheses that are expensive, slow or ethically impractical to test experimentally. Multiple simulations can be run in parallel. Parameter spaces can be explored systematically. Dosing regimens can be perturbed in ways that would be difficult in vivo. In this sense, the model functions both as a lens and as a sandbox.

CARTopiaX is the scalable implementation of that mathematical framework within the BioDynamo simulation platform, developed in collaboration with the Compiler Research group. My contribution was the biological grounding and mechanistic structure of the ABM. Their expertise lay in high-performance architecture, modular design and computational scalability.

The model formalises biology.

CARTopiaX turns that formalism into robust infrastructure.

Why Formalisation Forces You to Cross Disciplines

To encode CAR T-cell behaviour mechanistically, one cannot remain descriptive.

Cytokines do not simply “spread.” They diffuse. That diffusion must obey a formalism. Is Fickian diffusion sufficient at the spatial scale of interest? Does the microenvironment justify a continuum approximation? Should transport be implemented via discretised partial differential equations on a grid? What resolution balances biological fidelity with computational feasibility?

Answering those questions required learning not only immunology, but transport physics and stochastic processes. Choosing the diffusion equation is not decorative mathematics; it constrains emergent behaviour. An inappropriate abstraction alters gradients, signalling thresholds and ultimately predicted outcomes.

Similarly, activation and exhaustion are not labels; they are stochastic transitions. At each time step, state-transition probabilities govern behaviour. Those probabilities must be calibrated against experimental measurements. Sensitivity analysis must reveal which parameters materially alter system dynamics.

In my own trajectory, this necessity pushed me beyond computation into biological training — not to change identity, but to understand the provenance of the data constraining the equations. Calibration and validation are not technical afterthoughts; they are epistemic commitments.

Biology defines what interactions matter.
Physics constrains how they propagate.
Mathematics formalises their dynamics.
Computation implements them at scale.

Implementation Is Not Secondary

Many academic models are designed to answer a question, generate a figure and remain difficult to extend. If a model is to become infrastructure rather than illustration, its computational architecture matters.

My original ABM was built with object-oriented C++ because performance, modularity and reproducibility are structural requirements, not engineering luxuries. Agent-based systems grow rapidly in complexity. They may involve thousands or millions of interacting entities. Without modular design, small changes cascade unpredictably. Without careful separation of concerns, validation becomes fragile. Without reproducibility, trust erodes.

The Compiler Research group brought deep expertise in scalable systems and performance optimisation. They implemented the mechanistic framework within BioDynamo, improving scalability and computational robustness while preserving biological fidelity.

Crystal Boxes in a Machine Learning Era

Because we are living in a machine learning renaissance, it is important to clarify what this approach is — and what it is not.

Machine learning models excel at pattern detection and prediction across large, high-dimensional datasets. In imaging and genomics, they have transformed what is possible. They are often described as black boxes: powerful but internally opaque.

Agent-based models operate differently.

They are crystal boxes. Every rule is explicit. Every assumption is encoded. When unexpected behaviour emerges, it can be traced back to the mechanisms that generated it.

This distinction is not about superiority. It is about purpose. Machine learning is exceptional at identifying correlations and making predictions within observed data regimes. Mechanistic models are designed to interrogate dynamics under perturbation — to ask how system behaviour changes when assumptions shift.

A hammer and a screwdriver are both indispensable. Confusing one for the other weakens the work.

CARTopiaX deliberately implements a mechanistic crystal box because refining immunotherapies often requires understanding not only what happens, but why.

Beyond Proximity

Cross-disciplinary research is often described optimistically. It conjures images of mathematicians, biologists, engineers, and clinicians gathered around a table, exchanging ideas. But proximity does not guarantee integration.

Imagine trying to solve a global crisis with a room full of monolingual experts from different countries. Each person is brilliant. Each perspective is valuable. Without shared language, progress stalls.

Scientific collaboration faces the same structural constraint.

In the Nature exchange between Kenneth Kosik [2] and Sarah Bohndiek [3], the biologist and physicist each articulate what “understanding” means in their own fields. For a biologist, understanding gene transcription may involve identifying transcription factors and binding sites. For a physicist, understanding may involve probability distributions and force quantification. Those are not competing definitions. They are orthogonal planes.

Chris Ponting emphasises that interdisciplinary work requires trust and acknowledgement of differing expertise [4]. Sean Eddy argues that many breakthroughs emerge when individuals step outside disciplinary identity entirely [5]. In my own experience, learning to build mechanistic models required recognising when “I don’t understand” meant I lacked biological context, and when it meant I lacked mathematical formalism. It also required resisting the temptation to fit models to whatever data happened to be available. Instead, it often meant asking: what data would make this model defensible?

Translation operates in both directions. Quantitative scientists should learn biological language. Biologists should become comfortable with abstraction, equations and uncertainty. Neither side can remain monolingual if the goal is mechanistic understanding. However, in practice, we cannot expect every biologist to learn stochastic modelling, nor every engineer to master immunology. Cross-disciplinary scientists therefore act as translators between monolingual specialists. But they are not merely translators. They are integrators. They connect formalisms, expose hidden assumptions and ask structural questions that neither discipline would independently frame. They are often the missing piece — not because they know everything, but because they know enough to move between frameworks.

This movement is not only technical; it is psychological. Stepping into a new field can mean knowing less than a master’s student in that domain. It tests confidence. It requires comfort with temporary incompetence. It forces humility without surrendering authority (You can read more about this here).

But it also reveals which skills are transferable: abstraction, structured reasoning, the ability to formalise intuition.

The in-between demands both fluency and resilience.

Curiosity and Reframing

What made the collaboration behind CARTopiaX effective was not only technical strength. The Compiler Research group does not simply gather engineering talent; they cultivate curiosity.

They did not only ask what to implement. They asked why the question existed — what biological assumption motivated a rule, what constraint justified a parameter, what failure mode might invalidate a prediction.

They brought computational robustness.
I brought the mechanistic and biological framework.

The result was not a pipeline from biology to code. It was an iterative loop.

There is a persistent assumption that innovation comes from asking practitioners what they need and incrementally improving workflows. But as is often (perhaps apocryphally) attributed to Henry Ford: if he had asked people what they wanted, they would have said faster horses.

Mechanistic modelling does not simply accelerate existing experiments. It reframes the question.

What dynamics are invisible in static assays?
What system-level behaviour emerges from local rules?
What happens under perturbations we cannot easily test in the lab?

Because biology contains unknown processes, new perspectives are not optional additions. They are instruments for revealing structure where none has yet been formalised.

Why the In-Between Matters

For systems like CAR T-cell therapy — multiscale, stochastic, spatially structured — cross-disciplinary integration is not stylistic preference. It is a structural necessity.

Mechanistic modelling without biological grounding becomes abstraction detached from consequence.
Biology without formalisation struggles to interrogate dynamics.
Computation without architecture collapses under scale.

But something else is also true.

The scientific questions that will define the next generation of therapies will not wait for our institutional categories to stabilise. They will demand formalisation, simulation, calibration and iteration across scales.

If we insist on staying inside disciplinary comfort zones, we risk mischaracterising the system itself.

The in-between is not an intellectual compromise. It is where abstraction meets consequence. It is where unknown processes become structured hypotheses. It is where simulation informs experiment and experiment refines simulation.

If you are looking for questions worthy of your training, do not look for a department.

Look for the in-between.

[1] Zugasti, Inés, et al. "CAR-T cell therapy for cancer: current challenges and future directions." Signal transduction and targeted therapy 10.1 (2025): 210. https://doi.org/10.1038/s41392-025-02269-w
[2] Kosik, Ken. "Thirteen tips for engaging with physicists, as told by a biologist." Nature 577.7789 (2020): 281-284. https://doi.org/10.1038/d41586-019-03960-z
[3] Bohndiek, Sarah. "Twelve tips for engaging with biologists, as told by a physicist." Nature 577.7789 (2020): 283-285. https://doi.org/10.1038/d41586-019-03961-y
[4] Ponting, Chris P. "Genetics Needs Non-geneticists." Trends in Genetics 36.9 (2020): 629-630. https://doi.org/10.1016/j.tig.2020.06.015
[5] Eddy, Sean R. "“Antedisciplinary” science." PLoS computational biology 1.1 (2005): e6. https://doi.org/10.1371/journal.pcbi.0010006

]]><![CDATA[Early Detection of Burnout: Stay in the Zone Where Ideas Breathe]]>Wed, 19 Nov 2025 15:34:42 GMThttps://www.lmluque.com/blog/early-detection-of-burnout-stay-in-the-zone-where-ideas-breatheHi there, I'm finally back.

After a few months of silence, I’m ready to talk about why I disappeared—and what I’ve learned about burnout along the way. This post isn’t just about stress or exhaustion; it’s about the small, quiet signs that show up before things fall apart. The ones we often ignore.

With help from therapy, my brilliant mentor Julia, and some painful trial and error, I’ve started learning how to spot those early warnings—and how to protect the space where creativity, clarity and joy can actually survive.

If you’ve been feeling a little off lately, maybe this post is for you.

Blogging is one of the things I enjoy most. Not just because someone out there might benefit from my experience, but because writing helps me too. It gives shape to the swirl of thoughts in my head—puts a frame around the chaos. Because sometimes, when you put something into words, it becomes real.

It’s been nearly four months since my last post. Not for lack of trying. I can’t tell you how many times I sat in front of the computer, ready to write, only to find myself empty. Not of ideas—those were screaming inside my head—but of strength. Too tired to let them out. That, my friend, is burnout.

Burnout is that strange space where "I really want to" turns into "but I just can’t." It’s wanting to do everything and feeling paralysed instead. It’s being told you’re doing great but still hearing the voice that says, “You’re not enough.” It’s the ache in your bones when you try to get out of bed. The brain fog that turns simple tasks into steep hills. And life? It doesn’t pause. Responsibilities march on, deadlines loom, inboxes overflow. So we push. We say things like, “I’ll sleep after I finish this analysis,” or “I’ll take a break once this grant is in.”

But here’s something we don’t say enough: there is a point of no return.

And yes, that sounds dramatic. I wish it were. I’ve seen people—bright, passionate, committed people—end up in hospital wards, unable to continue their work. Burnout doesn’t tap gently on your shoulder. It hits hard and fast. And often, you don’t see it coming until you’re already on the floor.

That’s why, while talking to Julia—my brilliant mentor in the Women of Influence programme—this idea emerged: early detection of burnout.

I work in cancer research, and in that world, we know that early detection saves lives. Spotting symptoms early means there’s still time to act. Burnout, it turns out, follows the same rule.

The Burnout Curve: Not What You Think

Let’s start with the basics. What are the symptoms we all know? Let’s make a list—I love lists:

Exhaustion
Negative thoughts
Can’t get out of bed
Can’t focus

That’s textbook burnout. If you’re reading this and recognising those signs in yourself, you’re probably already in the thick of it.

But if you’re not there yet—this is the post you need.

You’ve probably seen the standard curve of productivity vs stress—a nice, smooth bell shape. This is known as the Yerkes–Dodson Law: with too little stress, we’re bored; too much, we crumble; but somewhere in the middle lies the sweet spot, where motivation and output peak.

Great in theory.

But in my experience, that curve doesn’t fall off gently. The climb is gradual, yes—but the drop? It’s sudden and steep. And sometimes, recovery isn’t just hard. It’s not even possible.

That’s why we need to stay in the healthy zone—and for that, we need regular mental check-ups.

What Early Detection Looks Like

Unfortunately, all of my grandparents died of cancer. Some close friends, too. Even some of my pets. So I learnt early the importance of screening. You don’t wait until you're in pain—you act ahead of it. You run tests, you slow down enough to listen to your body.

I firmly believe burnout deserves the same.

But it’s tricky. Because, just like cancer, early burnout symptoms are subtle. And mine might not be yours. So here’s where I get personal, hoping it helps you spot patterns in yourself.

If you know me, you know my life runs FAST. It’s packed with research, meetings, mentoring, social time, alone time—all of it. To make it all work, I rely on structure. My weeks are carefully planned: exercise three times a week, two “blank evenings” for nothing at all, two social evenings, and the rest is routine. My days are timed too.
Here’s what an average Monday looks like:

5:30 am – Wake up
5:30 – 6 am – Stretching and positive affirmations
6 – 6:45 am – Breakfast and an online course (English, Leadership, Immunology… you name it)
6:45 – 7 am – Skincare and face yoga (yes, face yoga)
7 – 7:30 am – Get ready for work
7:30 – 8 am – Walk to work
8 am – 5 pm – Work
5 – 5:30 pm – Walk home
5:30 – 6:30 pm – Chill
6:30 – 8 pm – Spinning class
8 – 9:30 pm – Shower and dinner
9:30 pm onward – Read until I fall asleep (eventually)

Intense? Maybe. But it works for me--until it doesn’t.

Why am I oversharing all this? Because burnout doesn’t usually arrive with a bang. It creeps in. And for people like me, the early signs hide in the smallest changes to that carefully structured life, regardless of the intensity.

With Julia’s help, I started mapping those signs using what she calls the Four Areas of Resilience:

Physical: How’s your sleep, diet, exercise? Are you fuelling the body or running on fumes?
Mental: Are you thinking clearly? Do problems feel solvable or impossible?
Emotional: How’s your inner voice? Compassionate or cruel?
Social: Are you connecting with others or withdrawing?

So retrospectively, here’s what early burnout looked like for me:

Skipping exercise. One missed class is fine. But skipping the whole week? Symptom.
Borrowing sleep. Staying up late to work. Telling myself “I’ll just finish this one thing”, then going to bed at 2 am. Again, one day is fine, the whole week? Symptom.
Caffeine spikes. If I need more and more coffee to get through the day? Symptom.
Replacing blank days with work. No more go-with-the-flow time? Symptom.
Mood shift. Negative self-talk creeps in: “I won’t be able to do this”, “Why did I accept this?”, “I’m not exercising enough”, “I don’t look good.” That harsh voice is my first red flag.
Cancelling all social plans. A quiet week is fine. A quiet month? Symptom.

It’s easy to think, “It’s just this week.” But academia rarely slows down next week. If I don’t notice the signs, they compound—fast. So take a moment every week to check how those four areas are.

What You Can Do (and What I Do Now)

Spotting burnout isn’t enough. You need to act. And that action will be different for everyone.

For me, it starts with making priority lists (a blog post on that is coming soon). It also helps to remember what my Fellowship Director once told me:

“Will the sky fall down if I don’t finish this today?”

I know what you’re thinking: “Easy for you to say. But the deadline won’t wait.”

Maybe. But have you ever asked? What if you emailed the editor and asked for a few more days? What if you re-prioritised your well-being?

Slowing down often feels like falling behind. But 99.9% of the time, that fear is louder than the truth—let that figure for tomorrow. I promise you'll finish it better and faster. And the 0.01% when it does cost something? You may want to think, does this deserve your mental health? I can tell you the answer straight away. No. Nothing is worth your mental health.

Because burnout doesn’t just steal your energy—it steals your joy. And in science, we need joy. We need clear minds, curious minds. That’s the zone where new ideas breathe. Where you connect the dots that no one else sees.

That’s the space we need to stay in.

I know this post may feel a bit blurry, and that’s okay. Burnout isn’t a one-size-fits-all story. There’s no universal checklist. But here’s my message:

Learn your signs. Respect your rhythm. Take early warnings seriously.

Again, and I can't repeat this enough, nothing is worth your mental health. Science needs healthy minds.

Your future self will thank you. Your science will thank you. And maybe, just maybe, you’ll never have to climb out of that deep hole again.

Let’s not wait for the crash.
Let’s catch it while it’s still a whisper.

And if you don’t know where to start—get in touch. Let’s share experiences. Let’s figure it out together. I’m still learning too.

We all are.

]]><![CDATA[Ada Lovelace: The Enchantress of Number, and the greenhouse we owe]]>Mon, 13 Oct 2025 23:00:00 GMThttps://www.lmluque.com/blog/ada-lovelace-the-enchantress-of-number-and-the-greenhouse-we-oweI had the pleasure of being invited by the Institute of Genetics and Cancer in Edinburgh to write for Ada Lovelace Day. The post can be found here, but I thought about sharing it here as well.
Coming from a computational background, Ada is a huge inspiration to me—she taught me to pair imagination with method, and to fight for the time and space ideas need.
In this piece I talk about the conditions that make creativity possible—and how often they’re withheld, especially from women—and share practical ways to open up space and time for each other.
I hope you enjoy reading it as much as I loved writing it. If it resonates, get in touch—I’m always up for this conversation.

A couple of weeks ago I was asked to write something for Ada Lovelace Day, and I felt that bright, unmistakable jolt—thrilled, grateful, a little awed. I would take any chance to honour this woman. But I want to honour her properly—not with a polite nod to a portrait on the wall, but by letting her story do what good stories do: slip a hand into yours and say, “Come on—let’s make a difference.” Ada didn’t just belong to history; she belongs to anyone who’s ever felt an idea tap on the shoulder and ask to be taken seriously. That’s why I’m here: to pass on the nudge she gave me, and to invite whoever needs it to answer back.

A little bit of context. Ada (1815–1852) was the daughter of the poet Lord Byron and Annabella Milbanke. Her parents separated when she was a baby, and her mother—determined to steady the Byron drama—steered Ada towards mathematics and logic. As a young woman she grew close to Mary Somerville, who opened doors and introduced her to Charles Babbage. He showed Ada his designs for a mechanical computer and she was hooked. He admired her fiercely and nicknamed her the Enchantress of Number. Tell me that isn’t an invitation to be bold. In 1843 she translated Luigi Menabrea’s paper about that machine and—and this is the important bit—added her own long Notes. Those Notes explained how such a machine could be programmed, including a step-by-step example for Bernoulli numbers. Think of it this way: Babbage invented it, Menabrea wrote the guide, Ada translated the guide and then wrote the first hands-on tutorial. Yes—this is exactly why she’s so often hailed as the world’s first computer programmer. If you’d like to dive deeper, Zoe Philpott tells Ada’s story (and those of other brilliant women) beautifully.

But the thing that makes Ada burn bright for me is her creative discipline. She didn’t just see a clever calculator; she imagined a general machine that could manipulate symbols—even music—if you fed it the right rules. She called her approach “poetical science”: let imagination open the door, then pin it down with a method. That’s my north star as a cross-disciplinary scientist, and that’s why I find Ada so inspiring. Creativity is not garnish; it’s the engine. And yet access to that engine isn’t handed out fairly—particularly to women.

People sometimes say, “Creativity is genderless; anyone can be creative. Look at Ada.” I agree in theory. In practice, creativity needs conditions. It needs a little greenhouse around the fragile beginning of an idea. Elizabeth Gilbert, in Big Magic [1], says ideas behave like living things—restless, opportunistic, looking for a committed human to collaborate with. If you’re open and faithful to the work, the idea will stay and grow. If not, it will fly on to someone else. I love that image. It dignifies the spark and also the labour. It says: your commitment is the invitation.

And this is where the real world walks in with mud on its boots. Because commitment needs space and time. Not just the calendar kind, but the inner kind—the kind where the voices in your head quieten and a thought has room to take its first breath. John Cleese once described creativity as needing five deceptively simple conditions: space, time, time (yes, twice), confidence, and humour. He’s right. I didn’t learn them from a seminar; I learned them by noticing when my work actually worked.

Here’s how that looks for me:

Space is a door that shuts—and, more importantly, a culture that respects the door is shut. It’s the choice to sit with a hard problem without apologising for the silence it requires.

Time (the first kind) is the patience to let the noise drain from your head. The first twenty or thirty minutes are full of chatter about shopping lists, unread emails, heroic plans to sort paperclips. Because, as we all know, it’s easier to do trivial things that are urgent than important things that are not; easier to do what we can already do than to start the big uncertain thing. I don’t fight those voices; I outlast them. Then the mind changes gear—almost audibly.

Time (the second kind) is what happens after the quiet arrives. A spark lands. You don’t yank yourself back to the inbox; you protect the next hour so the spark can be shaped into something testable. The longer you play with a problem, the more original your solution becomes. Thirty minutes won’t do it. An hour and a half might.

Confidence is permission to be gloriously wrong for a while. It’s the faith that a wonky prototype is not an embarrassment but a bridge. At this stage I grant myself amnesty from perfection: nothing is a mistake while I’m discovering.

Humour is lightness—the oxygen in the greenhouse. If we can laugh, we can try. And if we can try, we can make.

Now, if you’ve spent time in academia, you can see the trap forming, right? Many women have less protected time and less empty space. We carry more “invisible” service and admin which pulls time away from research [2,3]. Parenthood penalises women’s time and energy far more than men’s [4]. Credit gaps mean we often work harder for the same recognition [5], which erodes confidence—the very fuel creativity feeds on. And yes, on average, women report higher impostor feelings [6]. When you’re busy proving you deserve to be in the room, it’s hard to relax enough to make something new in it. That’s the quiet, costly disadvantage no one puts on a slide.

I don’t say this to make anyone defensive. I say it because science needs more Ada energy—more poetical science—and that means building the greenhouse on purpose. We can do this. In fact, we must.

So how? Not with slogans, but with everyday architecture. Shall we brainstorm together? We could start projects with a clear credit plan—who is doing what, how authorship will be decided, when decisions are revisited—so no one has to over-perform for visibility. We could rotate admin and teaching fairly and write the rota down, so generosity doesn’t become a trap. We could defend no-meeting deep-work blocks as research time, not “nice to have”, and keep those blocks for everyone, not just the loudest. We could pair mentoring with sponsorship—not only advice, but saying women’s names in rooms they’re not in and attaching our reputations to their opportunities. In talks and figure captions, we can name the people who made the work possible—technicians, data stewards, early-career scientists—because accuracy is justice and justice is culture. And on the human level, we can practise the small disciplines that keep confidence intact: an evidence list of what we built or learned this month; a tiny peer quorum to rehearse with; the safety to ask the so-called naïve question out loud; recovery scheduled with the same seriousness as experiments. None of this is grand. All of it is powerful.

Ada didn’t do it alone, either. Somerville widened the doorway. Babbage treated her as an intellectual partner and amplifier. Mentorship and advocacy created the conditions; Ada’s imagination and method filled them. That’s the equation I believe in: community enables; courage executes.

If you’re reading this and feel overwhelmed, begin smaller than small. Borrow a corner of quiet—a seminar room between bookings, a library desk, even noise-cancelling headphones and a do-not-disturb note. Claim some time on your calendar that you will protect like an experiment. Pick one playful thread to tug—write a messy first page, sketch the outline, run the simplest test. And if “one person who will back your name” feels impossible, ask for a micro-favour: “Could we swap an hour so I can focus?” or “Would you glance at this draft?” The ally often appears after the ask. Start there. It won’t solve everything, but it’s enough to invite an idea to stay.

Ada was brilliant, yes—but look closely and you’ll see what kept that light burning: a circle that made room for her to build her greenhouse, and her brave decision to step into it. If we want to honour her, let’s do it in the present tense—make room, hold it open, and help the women around us build the greenhouse their ideas deserve. More poetical science is possible, and it’s ours to grow—together.

References

[1] Gilbert, Elizabeth. Big magic: Creative living beyond fear. Penguin, 2016.
[2] O’Meara, KerryAnn, et al. "Asked more often: Gender differences in faculty workload in research universities and the work interactions that shape them." American Educational Research Journal 54.6 (2017): 1154-1186. https://doi.org/10.3102/0002831217716767
[3] Misra, Joya, et al. "Gendered and racialized perceptions of faculty workloads." Gender & Society 35.3 (2021): 358-394. https://doi.org/10.1177/08912432211001387
[4] Morgan, Allison C., et al. "The unequal impact of parenthood in academia." Science advances 7.9 (2021): eabd1996. https://doi.org/10.1126/sciadv.abd1996
[5] Ross, M.B, et al. Women are credited less in science than men. Nature 608, 135–145 (2022). https://doi.org/10.1038/s41586-022-04966-w
[6] Price, Paul C., et al. "Gender differences in impostor phenomenon: A meta-analytic review." Current Research in Behavioral Sciences 7 (2024): 100155. https://doi.org/10.1016/j.crbeha.2024.100155

]]><![CDATA[The Expert Illusion: Building Confidence Across Disciplines]]>Sat, 05 Jul 2025 22:57:24 GMThttps://www.lmluque.com/blog/the-expert-illusion-building-confidence-across-disciplinesBeing cross-disciplinary is a gift but it can also trigger a deep identity crisis. Am I a physicist? A biologist? An image analyst? An expert… in what, exactly?
Here I dive into what I think it really means to be an expert when you work between fields, and how I’ve learned to stop apologising for it.
If you’ve ever felt like you don’t quite fit, this one’s for you.

Hi there! I’m back.

These past few months have been wild. Back-to-back conferences, talks, panels, seminars... moments in the spotlight that leave you a little breathless. If you know me, you know that public speaking doesn’t come naturally to me. Not because I don’t like to talk, I do, but because deep down I still struggle to believe I’m the right person to be speaking at all. I still struggle to believe I’m ‘the expert’.

So when people come up to me after a talk and say, “You’re so confident!” or “I wish I could speak like you,” I want to take them by the hand and whisper the truth: What you’re seeing isn’t confidence. It’s scaffolding, something I build brick by brick, every single time. Because the hardest part of being cross-disciplinary isn’t the learning curve. It’s the identity crisis.

I know I’m not the only one feeling this way, so today I want to take you behind the scenes of that scaffolding. I want to share some of the strategies I’ve learned to feel more like an expert; how to recognise my value in context, stop undermining myself, and learn to present my expertise with confidence.

Living in the In-Between

Let me rewind. I started out as a physicist. A proper, hard-core, chalk-dusted theoretical physicist. I could model the hell out of a universe. But somewhere along the way, life nudged me down a path I didn’t expect...into biology. Cancer research, to be precise. That shift was not just a career move, it was a seismic shift in identity.

Today, I live in the space between physics, computational science, and immuno-oncology. I’m a cross-disciplinary scientist, which means I’m always learning, always translating, always negotiating between worlds.
And that’s beautiful. And brutal.

Because when you’re working across disciplines, you often feel like you belong fully to none. I’m no longer proving theorems or inventing new physics. So part of me thinks: I’m not a "real" physicist anymore. And I’m certainly not classically trained in biology. I know the narrow slice I work on, yes, but not everything else. So part of me thinks: I’m not a "real" biologist.

And here’s where it gets dangerous: just like that, I’m standing in a room full of specialists: physicists, computational biologists, immunologists, and I assume they all know better than me.

Turns out, this feeling isn’t rare. It’s epidemic among cross-disciplinary researchers. Especially women. Especially those of us who grew up being praised for being "hard-working" more than for being "brilliant."

Redefining Expertise

One day I met Julia. She’s my mentor in the Women of Influence programme, a mentoring scheme that pairs researchers with top UK businesswomen, offering support and guidance from outside academia. Julia is a powerhouse of a woman: the Global Head of Coaching at one of the most prestigious law firms in the world. Not an academic. Not a scientist. Just incredibly wise.

One day, in a conversation about expertise and credibility, I said something like, “Well, I’m not an expert in biology…”
She stopped me. And then she asked, “What does it mean to be an expert in biology?”

It sounds like such a small question. But I swear, it cracked the floor open under me.
Because really, what is an expert?

Biology is huge. No one knows all of it. Just like no physicist knows every subfield of physics. Just like no coder knows every language. Most people are deeply specialised in a narrow corner of their domain. They say, "I study autophagy in breast cancer," not, "I know biology."

So I thought… what’s my narrow corner? And I realised: I understand immuno-oncology better than many classically trained biologists. I’ve taken dozens of courses — online, in person, in labs — to learn what I needed to learn. I know how to build physical and computational frameworks to study these biological processes.
That is expertise.
That is mine.

From Undermining to Owning It

But here’s the trap: I didn’t always present myself that way.

In biological conferences, I used to introduce myself by saying, “Hi, I’m Luciana — I’m a physicist, so please bear with my biology.” Or, “I’m not really an expert in this, I’m just trying to help.”

I thought I was being honest. I thought I was building trust by lowering the bar. But in reality? I was undermining myself before the conversation even began.

Julia spotted this in me immediately. She said, “Move away from the generics. Don’t say what you’re not. Say what you do. Be specific. Be contextual. Be smart about it."

She was right. I know it because I saw it in action.

At a microscopy conference, one of my favourite people/scientists in the whole world — Maddy Parsons — introduced me to someone by saying: “This is Lu. She’s a super-duper image analyst.” And something clicked. That was exactly what I was in that moment. Not a physicist. Not a biologist. A damn good image analyst. And suddenly, people leaned in. They listened. They asked questions.

Maddy knows I’m a physicist. She knows my journey. But in that room, in that moment, the relevant truth was: I analyse high-plex images, with a particular focus on immuno-oncology. That’s my expertise. And that’s what people needed to hear.

It's not enough to know what’s my narrow corner, I also need to know what's relevant in the context. So now, before I introduce myself, I ask:

What is my expertise in this room?
What do I do here that makes me valuable?

It’s all about focusing the lens.

Reinforcing the Scaffolding

Yes, knowing my expertise is key, but it's not enough. Here are a few shifts that helped me reinforce that scaffolding. Small, practical things that changed the way I carried myself.

You don’t need to apologise for not knowing everything. Even the most seasoned experts say, “Sorry, I’m not familiar with that, can you explain?” It doesn’t make them look weak. It makes them look interested. Curious. Capable of learning.

Accept praise. When someone came up to me after a talk and said, “Luciana, that was brilliant,” I used to say something like, “Oh gosh, really? I was actually very nervous.” (accompanied by an awkward, I-want-to-disappear smile). Not exactly expert energy, right?

Now I try to say something like: “Thank you. Do you work on something similar?”

Praise, received. Connection, built. Doors, opened.

Don’t deflect. When someone called me brilliant in a room full of people, I used to deflect, say they were being overly kind. That’s not humility. That’s self-sabotage. By saying that, I wasn’t just putting myself down, I was also questioning the other person’s credibility.

Now I simply smile and say: “Thank you.”

Small things that make a huge difference.

The Takeaway

There’s a reason we look to experts. They give us something to lean on. Not because they know everything — but because they sound like they know what matters. And in science, that kind of presence is powerful. It opens doors. It secures funding. It gives patients hope.

Well, good news: we are all experts, just in different things. Expertise isn’t about knowing everything. It’s about knowing your thing. It’s about showing up prepared, curious, and open. It’s about standing tall in the weird little intersection you’ve carved out for yourself.

We can be experts in multiple things. Learning to identify your expertise in a way that fits the context is what helps you feel like an expert and look like one too.

Don’t put yourself down for not knowing everything. It’s OK not to know. Imagine how boring life would be if we did.

So yes: fake it till you make it. Confidence isn’t built in a day. But these small shifts, these little reframings, helped me more than I ever expected.

If any of this resonates with you, and you want to talk about it or share your story, get in touch. And if you have tips of your own for reinforcing the scaffolding, I’d love to hear them. :)

]]><![CDATA[From Whispers to Fire: Melting the Iceberg of Academic Sexism]]>Fri, 25 Apr 2025 19:46:27 GMThttps://www.lmluque.com/blog/from-whispers-to-fire-melting-the-iceberg-of-academic-sexismHi there. I’m back.

I’ve been trying to write this piece for almost two months now. I’ve started and deleted and started again so many times. I knew what I wanted to say. The truth was never the hard part—what was hard was allowing myself to say it. Every time I sat down to write, I felt the sting of old wounds rise up again. I had to stop, breathe, cry, walk away. Because remembering isn’t neutral—it hurts. Revisiting the things I’ve been through was like touching bruises I thought had faded. But today, I’ve decided: enough. I’m letting it go. I’m telling the story—not because it’s easy, but because it matters.
It’s time to speak.

Originally, I thought I’d begin this entry with data. You know the kind—about how women in science are abundant in classrooms but rare in boardrooms. How our work is cited less, funded less, celebrated less. How our presence thins out the higher up we climb, like air in the mountains. I wanted to show the leaky pipeline with charts and reports and bullet points.

But then, on International Women’s Day, my institute screened a documentary: Picture a Scientist. And one image from that film tattooed itself onto my memory. It was called the "Iceberg of Academic Sexism". You’ve seen that iceberg too, haven’t you?

At the top: the loud stuff. Harassment. Groping. The grotesque. But beneath the waterline lives the real mass—the quiet stuff. The being passed over, the invisible no’s, the polite exclusions. The meetings where you speak and nobody hears you until a man repeats your point. The collaborations you’re not invited into. The feeling of being in the room, but never belonging there.

And when I saw that iceberg, something in me said—Oh. There I am.

Because I have lived every layer of that cold, heavy structure. Not once, but over and over again, across continents and titles and job descriptions. And in that moment, I realised: anyone can write about statistics. But not everyone can write about what it feels like to be swallowed by the iceberg. So here we are.

I am writing this for two reasons:

Because when you name the thing that’s been dragging you down, you start to lift it.
Because I want to offer my voice to anyone out there who still thinks they’re overreacting. You’re not. I promise you, you’re not.

So come closer. Let’s talk.

The Whisper: “Am I Overreacting?”

Not that long ago, sexism didn’t even try to hide. It swaggered through the halls of academia, bold and bored, fully aware there would be no consequences.

Things are changing now. Slowly. There’s more awareness, more training, more eyes on behaviour.
But the sexism didn’t disappear. It just changed shape. It got quieter. It started dressing up as decorum. It learned how to whisper. And the worst part about whispers? Sometimes you’re the only one who hears them. So you start wondering: Was that comment inappropriate, or am I being too sensitive? Was I left out of that project, or did I just imagine it? Should I laugh it off? Should I “be cool”? Should I be grateful?

This inner dialogue will eat you alive if you let it. Because here’s the dirty little secret: we are taught to be pleasant. To be accommodating. To be grateful. So when we experience harm, we smile through it. We doubt our instincts. We question our reactions. We become our own silencing agents.

But something powerful happens when another woman looks you in the eye and says, “That happened to me too.” Suddenly, your shame shrinks. Your gut grows louder. You start reclaiming your own voice.

That is the first spark of revolution.

Speak Up… They Say

Here’s the thing they don’t tell you about speaking up: it costs.

Every time I’ve spoken, someone has warned me.

Be careful.
They might come after you.
Don’t name names.
Don’t tell stories.
Don’t ruin your career.
Don’t be “that woman.”

And here’s the gut-wrenching part: they’re not wrong. Not entirely.
Especially when you don’t have tenure. Especially when your future depends on recommendation letters and closed-door conversations.

So yes—I thought about backing down. I thought about watering down the truth. I considered writing a neutral little blog post full of statistics and soft edges. But then I remembered what silence does to the soul. Silence doesn’t keep you safe. Silence keeps you small.

I’ve been to therapy. I’ve healed some wounds. I’ve stared down shame and told it to go to hell. And what I’ve learnt is this: Speaking costs. But silence costs more.

So I’m writing this. Not to name names. Not to seek revenge. But to reclaim my story—and to make space for yours.

I have been told I’m not clever enough to have my own ideas—this, whilst sitting at the top of my class.
I’ve watched my male colleagues get praised for work that was objectively less thoughtful, less rigorous, less original than mine.
And the voice in my head whispered: Maybe they’re right. Maybe I’m just good at memorising things. Maybe I don’t have real ideas. Maybe I’m only here because I try hard—not because I belong.

All lies.

That was sexism. Wearing a nice tie and using your first name like you’re friends.

I once entered a poster competition. One of the judges—a man with too many titles and not enough shame—told me he wanted to talk more about my research. I was over the moon. I was a student. A senior scientist cared about my work! I waited beside my poster with notes in hand, heart thudding with anticipation.

He came back and offered to give me higher marks if I danced for him in his hotel room.
He wasn't interested on my research at all.

I was crushed.

But the real heartbreak came later, when I told people. They shrugged. “Did you really think he wanted to talk about your science?” they said. And the voice in my head whispered:

Of course not.
You’re just a girl.
Not even a clever one.

Again: lies.

That was sexism. Ugly, sharp, and familiar.

I’ve been harassed whilst teaching. A senior professor—well-known, well-liked—used to sit in on my classes “just to stare at me”. He said so openly. He bragged about it. Other professors knew. No one intervened.

When I said I was uncomfortable, they laughed. Told me I was overreacting. So did the voice in my head.

Too emotional.
Too sensitive.
Don’t make a scene.

Never mind that this man already had a stack of complaints in his file. Still my fault, apparently. Still my drama.

Lies. All of it.

That was sexism. Polished and institutionalised.

I could fill a book with stories like these (and worse ones too). I wish I couldn’t. But I could. And the worst part is—they don’t go away.

Now, when someone asks to meet me later to “talk science,” I freeze.
Now, when someone says my work isn’t good enough, I wonder if it’s my ideas—or my gender.

The voices haven’t left. But here is something you want to hear, they’ve been joined by new ones.
Kinder ones.
Wiser ones.
Louder ones.
The more I speak, the less shame I carry. The more I name, the harder it becomes for others to look away.

We Need Allies

We are still so far from equity. From being believed. From being safe.
I wasn’t going to talk about statistics—but let’s not pretend the numbers lie.
Every time I tried to report abuse, there were no gender committees. Just men. Lots of men. Sitting behind desks, listening with crossed arms and closed minds. So I helped build something different. A gender committee. A safe space for women to talk, report, be heard. And would you believe it? We met resistance.

Because the moment you try to centre women’s voices, someone always asks: “But what about the men?”
Listen. Equity isn’t about giving women extra. It’s about restoring what’s been stolen. Men have had a head start for centuries. We’re not attacking—we’re correcting. And we can’t do it alone, because unfortunately, most of the people in power are still men. We need them on our side—not just with slogans, but with sleeves rolled up. Hire us. Mentor us. Fund us. Believe us.

We are already doing the labour. We sit on committees. We mentor students. We rewrite entire cultures in our spare time. We shouldn’t have to survive a broken system and be the ones to fix it. We need shared responsibility. That’s what justice looks like.

So if you’re a man reading this: lean in. Show up. Be safe. Be kind. And if you don’t know where to start—ask. We’ll figure it out together.

There Is a Light

I’ve read this piece so many times, trying to make it sound less heavy. But here’s the truth: It is heavy.

And yet—there is a light at the end of this long tunnel.

Things are changing. There are more policies now. More consequences. More brave people in rooms that used to be closed.

Personally—I am changing too.

I was raised in a culture that taught me to shrink. That taught me to smile through pain. That made me doubt myself even when I was winning. Those voices are still in my head. But they no longer get the final word. Now, there are other voices. Gentler. Braver. Mine.

Sexism in academia is real. And every woman I know has faced some version of it. It’s not you. It’s the system. And systems can be rewritten.

To the Ones Still Whispering

If you’re still whispering your pain—I hear you.

If you’re afraid to speak—I believe you.

You don’t need to shout. Start with a whisper. Tell a friend. Tell yourself. Find someone who will say, “Me too.” Because here’s what they never told us: You are not alone.

They say women “leave” academia. We don’t leave. We’re pushed out—by a thousand tiny cuts.
So if you’re thinking of leaving, let me say this:

You belong here.
You deserve joy.
You deserve safety.
You deserve to be heard.

And if the system says otherwise? Then it’s the system that’s broken—not you.

Let’s keep going. For us. For each other. For the ones who haven’t arrived yet.

We are not just surviving. We are building a new world.

Final note: if you’re a man reading this, thinking I might be talking about you — I hope you’ll sit with that discomfort. Reflect. Grow. Change.

]]><![CDATA[Just Lu]]>Sun, 16 Feb 2025 21:17:02 GMThttps://www.lmluque.com/blog/just-luI could start this by listing my credentials, my achievements, the institutions I’ve worked at, the awards, the papers—all the usual stuff people parade around to prove they’re worth listening to. But honestly? That’s not what I want this space to be about.

So let’s start again.

Hi, I’m Lu.

Just Lu. Not the accomplished scientist, not the overachieving girl from a small town who made it big, not the one who survived. I’m just me. If you asked my friends to describe me in one word, they’d say “resilient.” And sure, I get it. But in my head, I’ve always just been a survivor. The less glamorous cousin of resilience, right?

Survival is what I’ve done, not just in academia but in life. I’ve been through things I don’t often talk about—things that nearly ended me before I even turned twenty. And yet, here I am. Sixteen years later, still standing. Still fighting. And for a long time, I thought that was just… normal. That this daily battle in my head wasn’t anything special. But maybe, just maybe, I don’t give myself enough credit.

So why this blog? Why now?

Because at some point, I realised that being open about my struggles—my mental health, my experiences in academia, the sheer exhaustion of having to prove myself over and over—made a difference. Every time I spoke up, people thanked me. They felt seen. They felt less alone. And that’s when it hit me: I don’t need to be a therapist to help people. I just need to be real. I just need to say, “Hey, I see you. I get it. And I’m here.”

Science, as much as I love it, has a way of chewing people up and spitting them out. It convinces you that if you’re not working 24/7, you’re not dedicated enough. That if you care about your life outside the lab, you’re not a real scientist. That if you take a step back, someone else—someone more ruthless, more “serious”—will take your place.

And to that, I say: bullshit.

You can be a great scientist and still have a life. You can have boundaries. You can have hobbies. You can want more than just an h-index to define you. I know because I do. And I refuse to let anyone make me feel like that makes me less worthy of being here.

But I didn’t always feel this way. There was a time, not so long ago, when I let powerful, well-respected scientists—people from prestigious institutions around the world—convince me I wasn’t good enough. That fear was a better motivator than support. That I owed them my time, my energy, my well-being. That the only way to succeed was to give them everything.

And then one day (after lots of therapy), I stopped. I stood up to them. I chose myself. And in that moment, I realised: I don’t just belong here. I’m damn good at what I do.

So, here we are.

This blog is my way of reclaiming space—not just for me, but for anyone who’s ever felt like they don’t belong, like they’re not enough, like they have to fit into some impossible mold to make it in this world. It’s a place where science meets life, where honesty trumps perfection, where we can talk about the things that actually matter.

So, I’ll be writing about my life inside and outside academia, about the situations that made me who I am today, etc. If anything here resonates with you, stick around. Let’s have conversations that academia doesn’t always make room for. Let’s remind each other that we’re more than our CVs. And let’s prove that science doesn’t have to be a brutal, joyless grind to be worth it.

You in?

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​CARTopiaX and the Land of the In-Between

​From Mechanistic Model to CARTopiaX

​Why Formalisation Forces You to Cross Disciplines

​Implementation Is Not Secondary

​Crystal Boxes in a Machine Learning Era

​Beyond Proximity

​Curiosity and Reframing

​Why the In-Between Matters

​The Burnout Curve: Not What You Think