Hacking Academia

🍕 Free leftover food in the kitchen – first come, first served!

As a PhD student, those emails were great - I’d drop everything and sprint to the tea room. Free food - what's not to love!

Two decades later, I still have that instinctive reaction - despite the circumstances (and need for) free food being very different.

It’s a somewhat frivolous example, but it captures something that happens a lot in academia: we don't always consciously change our behaviour, activities and priorities when our circumstances change.

In this Hacking Academia episode, I look at what happens when we forget to adapt – after a big win or during a tough stretch.

Say you’ve just landed a major fellowship, a big promotion, or secured a long runway of funding. It’s easy to celebrate 🎉 (as you should), thank 🙏 your supporters and collaborators... but then often 𝐠𝐨 𝐛𝐚𝐜𝐤 𝐭𝐨 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐚𝐬 𝐮𝐬𝐮𝐚𝐥. 

But that 𝐦𝐢𝐬𝐬𝐞𝐬 𝐭𝐡𝐞 𝐦𝐨𝐦𝐞𝐧𝐭, which is often your best shot to step back, reassess, and ask:

💡 What *can* I do now that wasn’t possible before?

💡 What should I be having a crack at that I didn't have the time, the resources or the career breathing space to do before? What risks should I be deliberately taking?

💡 What should I be changing about my priorities and behaviour now, so when I look back at the end of this opportunity, I'm unlikely to 𝐫𝐞𝐠𝐫𝐞𝐭 that 𝐈 𝐝𝐢𝐝𝐧'𝐭 𝐭𝐚𝐤𝐞 𝐭𝐡𝐞 𝐜𝐡𝐚𝐧𝐜𝐞 𝐭𝐨 𝐫𝐞𝐚𝐥𝐥𝐲 𝐜𝐡𝐚𝐧𝐠𝐞 𝐰𝐡𝐚𝐭 𝐈 𝐚𝐦 𝐝𝐨𝐢𝐧𝐠?

The same goes in reverse.

When life gets difficult – illness, caregiving, personal upheaval – many people don't think to not keep going at full pace, not realising that hitting pause or slowing down on the non-critical work is okay. In fact, it’s often necessary.

This is very understandable of course: sometimes there's legitimately a lot of pressure. But much of the time it's an unnecessarily-self-imposed pressure (high achievers being over-represented in certain careers...) that doesn't actually need to be there. Sometimes a gentle nudge from a colleague, supervisor or mentor - "hey you can drop that for a while" - is all that's needed. 

This video shares a few types of situations where this arises from my own career and from colleagues around the world. 

👉 Watch the full video on YouTube: https://lnkd.in/dwateatr

#HackingAcademia #AcademicLife #CareerDevelopment #PhDLife #Promotion #ResearchCareers #LeadershipInAcademia #Adaptability #RegretMinimization #HigherEd #Mentoring

🎓 Did you know there are (at least) four ways to combine supervisors and PhD students for your regular meetings — and that each serves a different purpose?

That's the topic of today’s 𝐇𝐚𝐜𝐤𝐢𝐧𝐠 𝐀𝐜𝐚𝐝𝐞𝐦𝐢𝐚 video – and meeting type number three is a doozy: super useful and rarely done.

👇 Here are the four types:

1) 🧑‍🏫👩‍🎓 𝐀𝐥𝐥 𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐨𝐫𝐬 + 𝐒𝐭𝐮𝐝𝐞𝐧𝐭

Your classic setup. Everyone's in the room, alignment is clear, but don’t overdo it. Alternate weeks works well - or try a 𝟑-𝟏 structure, with three solo (meeting type 2 below) meetings and one all-in meeting per month.

2) 🧑‍🏫👩‍🎓 𝐏𝐫𝐢𝐦𝐚𝐫𝐲 𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐨𝐫 + 𝐒𝐭𝐮𝐝𝐞𝐧𝐭

Lets the less experienced supervisor lead solo. Builds confidence and gives them the space to grow as an independent mentor.

3) 🧑‍🏫🤝🧑‍🏫 𝐒𝐞𝐧𝐢𝐨𝐫 𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐨𝐫 + 𝐏𝐫𝐢𝐦𝐚𝐫𝐲 𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐨𝐫 (𝐍𝐨 𝐒𝐭𝐮𝐝𝐞𝐧𝐭)

The underrated gem. A private space to speak frankly, mentor behind the scenes, and stay aligned on how best to support the student.

4) 👩‍🎓🧑‍🏫 𝐒𝐞𝐧𝐢𝐨𝐫 𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐨𝐫 + 𝐒𝐭𝐮𝐝𝐞𝐧𝐭 (𝐍𝐨 𝐏𝐫𝐢𝐦𝐚𝐫𝐲 𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐨𝐫)

Use sparingly and thoughtfully – but it has 𝐭𝐰𝐨 valuable modes:

One is a circuit-breaker meeting to address specific issues or enable the student to confide in a safe space.

The other is higher-level mentoring: sharing experience, career advice, and helping the student think longer-term about their trajectory.

📌 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲:

Get your meeting mix right, and everyone wins – the student, the supervisors, and the broader mentoring relationship.

👉 Watch the full video on YouTube: https://lnkd.in/dGgGbUJ5

#HackingAcademia #PhDLife #PhDSupervision #AcademicMentoring #GradSchoolTips #ResearchCulture #HigherEd #AcademiaUnpacked #PhDChat

🎥 New #HackingAcademia episode just dropped – and it's a sensitive but hopefully somewhat cathartic one, perfect for a Friday afternoon:

𝐅𝐚𝐤𝐞𝐬, 𝐅𝐫𝐚𝐮𝐝𝐬 𝐚𝐧𝐝 𝐅𝐚𝐥𝐥𝐚𝐜𝐢𝐞𝐬

🤯 “That guy sounds like a total fraud.”
😠 “I have no idea how they got that role – they're a disaster.”
🤔 “If they’re taking advice from her, they’re in real trouble.”

We’ve probably all heard variations of these. Maybe even said them on occasion.

My intent in today's video is to unpack the key issues and concepts that arise in these situations, and some suggestions on how to approach them.

In trying to ⚽ play the ball, not the person, I'd emphasize almost everyone has lots to offer: this is about their portrayal, and other's portrayal of them, and the perceptions of others that sometimes arise that the portrayal is wildly inappropriate or fraudulent.

Key points covered in the video:

🎭 Most accused of fakery are actually good at something - but sometimes they just haven’t found the right niche yet. It's also not easy: there's a lot of work to keep up the charade!

🪞 Bias about what an expert shoud "look like" and "sound like" are widespread and not helpful here

A two for one:

1) 🔍 Experts often overestimate how much expertise a role really needs.

AND

2) 🧪 Decision-makers often underestimate the depth required - this can be CATASTROPHIC.

💼 People need to earn a living, and those hustling outside the safety net of secure jobs often face somewhat unfair criticism from those in secure positions.

😶 A BIG one: ELOQUENCE IS NOT EXPERTISE. OMG 🤯

📉 But conversely, expertise without some semblance of communication ability limits its utility.

👋 When complaining about someone in a role, remember sometimes they're the only person who put their hand up!!!

🧠 It takes an expert to validate another expert.

🌐 Professional careers run on relationships - trust is often extended more easily to people we know.

🤝 many roles require expertise paired with networks, influence, to be effective

👥 For every person you think is a fraud, there’s others who think they’re brilliant.

🔁 Your opinions - and others of you - will likely will change over time, based on new experiences or context.

⏳ "Truth will (mostly) out (eventually". Promises fail, tech doesn’t work, good or bad reputations are established. That doesn't mean some genuinely fraudulent individuals can't do a lot of damage in the meantime.

🌱 A little 🧂 patience in judging can go a long way. Calling everything out, often wrongly, will burn you out, won't actually help, and you'll be miserable in the process.

---

👉 Watch the full video on YouTube: https://youtu.be/eOs2VgIrfI8

#AcademicLife #ResearchCulture #Careers #Fraud #Fake #Misrepresentation #Trust #Expertise #communication #reputation #biases #ProfessionalDevelopment #Leadership #CareerAdvice

They say you should see the forest for the trees 🌲🌳 - to understand the larger context rather than getting lost in the details without grasping this vital bigger picture 🧩

That’s what today’s hashtag#HackingAcademia video is all about 🎥: the types of context-setting questions you can ask in early-stage discussions with an industry or government organization that has approached you about a working on a problem or opportunity they have🤝

Context like financial 💰, historical 🕰️, or delivery-related 📦 information is critical to making sure that the detailed conversation that follows is actually productive. Without context, you risk wasting a huge amount of everyone’s time ⌛ going down paths that context would have immediately ruled out as viable.

These questions also increase the chances that the organization finds a good solution, whether or not that includes you. The goal isn’t to win the project. The goal is to help them get a good outcome, and sometimes that means you’re part of it.

So what kinds of questions help build this context? 🤔

❓ Why are we sitting here? Why is this not already a solved problem, and how do you know that / how have you come to that conclusion?

❓ Most problems aren’t unique. Others have tried, maybe solved, or abandoned similar issues. Why?

❓ Is this a case of “more resources will fix it,” “we have a solution but want it cheaper,” or “we need major breakthroughs to make any progress”?

❓ Is this a one-off problem or a recurring one? That affects the solution space and which partners might be relevant and commercially interested 🤖

❓ Who cares, and who pays? Are people already throwing money at this out of self-interest, or is it more of a greater-good or government issue? 🏛️

❓ Why aren’t startups all over this already proposing solutions? Are there big barriers, or is the perceived incentive just not strong enough?

❓ Even if the core problem is solved, how will the solution be delivered reliably in a form the partner can use? Can the university do that entirely by themselves? Does an OEM or external provider need to be involved as well?

❓ How much is currently being spent on this problem? Are they trying to reduce that spend or get more value for the same amount? A $100k per year problem is very different from a $100M one 💵

❓ What assumptions or outdated beliefs are they operating under? In fast-moving tech spaces, (gently) making sure their understanding is current really matters 🔄💡

As colleagues who lead industry engagement at QUT and who've been in thousands of these meetings, what other context-shaping questions would you add Deon de Saldanha, Ray Johnson, Holli Evans, Kate Taylor, Melissa Nikolic and Erin Rayment?

🖥️ YouTube: https://youtu.be/sgf9_nRkRqQ

#industry #government #startups #solutions #translationalresearch #commercialresearch #research #university #academia #technology #solutions #ideation #problemscoping

There's a laundry list of phrases that trigger me in #academia and related professions: one of the most frequent ones is "I don't have time" / "They don't have time."

The reason it triggers me so often isn't so much that the statement doesn't reflect a stark reality: today's academic and research world has arguably never been more of a pressure cooker to perform, and with less and less resources to do so.

My problem with the statement is what then usually happens: a deep dive into the metaphorical weeds of why that person doesn't have enough time , when usually it's two larger issues that are at play.

Modern, professional careers never have enough time to do everything - "not enough time" is a truism at this stage. Careers are a constant balancing act of prioritization* 

What "I don't have enough time" often in fact boils down to is one or more of two issues:

1) "I don't perceive enough value or return on investment on that activity in order to prioritise it highly enough to get done", 

and/or

2) "I perceive too many barriers or obstacles in the way in order to be remotely feasible of fitting it into my hectic schedule"

Neither reason 1 or 2 is explicitly about time (of course time is involved): they're about priorities and barriers. Any response by a manager or leader hoping to encourage said individuals into making time for an activity should take into account these very real possibilities, rather than just fixating on the pure time issue.

There needs to be some give and take too: if you manage to show the value proposition (1) and remove some of the barriers (2), the individual may well prioritise the thing you're encouraging them to do. But they have finite time, so this shift in focus may come at the cost of some attention to some other existing activities. It's your job as leader or manager to be ready for and account for this: if at this stage you penalize them for a slight shift in focus, you'll undo all your good work and more...

🖥️ YouTube: https://youtu.be/WPrSZbeRcA4

* at least for those who go about their careers in deliberative ways: some people wing it and appear to go spectacularly well - but perhaps not recommended as an approach for all people 

#timemanagement #leadership #management #workload #working #planning #motivation #priorities #barriers #obstacles #careeradvice

When is having a good awareness of the "big picture" in a PhD or general research not helpful?

When you need to focus in on the "little picture", to preserve your sanity, lower your sky high stress levels, and make some concrete, tangible progress forwards.

When things get tough in research, researchers, including PhD students, can have a (natural) tendency to try to focus on trying to achieve too many things at once, with the natural result of achieving nothing at all, and getting ever more frustrated as a result.

For research fields like robotics, computer vision and machine learning: yes the eventual aim of many PhDs is to create a new method or set of techniques that improves the state-of-the-art in some meaningful way, including demonstration across many datasets / domains / robots and in the case of "helper" pre-processing / post-processing techniques, potentially across many different techniques.

But when you're struggling, trying to tick all those boxes simultaneously: that novelty box, that generality box - both for domains and for techniques - is completely overwhelming, and usually counterproductive to both your sanity and your progress.

What I often do with students in these situations is reset: dial back the ambition, come up with a simple proof-of-concept of the proposed ideas, often using old statistical or ancient machine learning techniques, and demonstrate that it makes a meaningful difference on .

That won't in of itself be the research they need, the contributions they need, or enable them to publish (probably), but it will be a massive confidence booster and provide them with a rock solid, well understood foundation to build on, rather than floundering in a sea of too many conflicting goals.

🖥️ YouTube: https://lnkd.in/dNZVQzDE

#PhD #research #reset #careeradvice #academia #university

This week I had coffee with a new colleague and the conversation got onto the realities and challenges of recruiting, and retaining, the talent you want to work with and need to fulfill all those exciting research, industry and government projects you've got going. Especially in topical fields with lots of competition for talent, and sky high salaries... 💲💲💲 

So late on this Friday afternoon and heading into yet another long weekend here in Brisbane, here's my newest #HackingAcademia video covering talent strategy, including recruiting and retention considerations, and some of the things you can do about it, both now and longer term.

I cover:

🎓 In a typical academic career, you'll run many research projects - fundamental, applied, with industry, government, or startups.

🧑‍🔬 Much of the work is done by recruited talent: PhD students, postdocs, RAs, engineers - so your ability to attract and retain talent is critical.

❤️ Some people are passion-driven - motivated by causes or purpose - and may be more tolerant of the inevitable imperfections in any role.

💼 Others are interest-aligned but pragmatic - and will not take a role, or leave, if conditions aren't sufficiently attractive.

🌐 Your field’s opportunity landscape matters - are there lots of alternatives or only a few?

📣 Recruitment strategies vary. 🤝 Direct outreach and word-of-mouth can work in niche fields. 📢 For hot topics like AI, you may need (and benefit more from) broad, public exposure and a large network.

👤 Your reputation, your group’s alumni outcomes, and the broader ecosystem (faculty, university, country) all influence your appeal.

🌴 Culture and location can sometimes tip the balance, even if you can’t compete directly on salary.

🧱 Culture takes years to build - early-career academics should consider this before joining a new institution.

💰 Universities can’t match industry salaries - but be smart when writing grants. ✍️ Don’t under-budget salaries just to win the grant. ⚠️ Cutting salaries may create recruitment problems later.

🎯 Pitch a mix of projects. 🧪 Some high-risk, high-reward ones needing top-tier talent. 🛠️ Some more achievable ones suited to a broader skill range.

🌱 Avoid 100% “green fields” projects where neither you nor the student knows how to proceed when the going gets difficult.

🔄 Consider autonomy required, and provided. 🏃‍♂️ Some projects and talent that can operate without constant supervision are essential as you scale up.

🧮 Expand your recruitment pool. e.g. in a tech field: 🧑‍🏫 don’t only seek CS grads - consider rapidly upskilling engineers or mathematicians, who may come from (somewhat) less-in-demand talent pools.

🔁 Retention is just as important as recruitment. 🧲 Keeping good people saves time and effort. 🧳 But some turnover is healthy and inevitable.

🏡 Support retention by offering 🚀 growth pathways and professional development, and 🌏 a strong social and work environment - especially for newcomers.

💡 When designing a project or grant, always ask: 👥 What kind of talent will it require? 🔍 Is the pool broad or narrow? 🧠 How competitive is this space?

🖥️ YouTube: https://youtu.be/FcbQ9GpwJEU

#recruiting #jobs #careers #PhDs #salary #retention #work #opportunities #academia #universities #robotics #computervision #computerscience #artificialintelligence #machinelearning #AI #automation #autonomy #industry #government #options #funding #strategy #careeradvice #careerstrategy #postdoc #researchfellow #softwareengineer #researchassistant #PhD #Masters #gradudatestudent #gradstudent

This meeting is driving me INSANE 😡🤯

I regularly take requests for my #HackingAcademia series: today's request was one of many about how to deal with meetings where you're frustrated beyond belief, and want to tear your hair out.

As someone who was driven nuts by this for much of my early career, but less often now, I have no easy solutions. I can however contribute a bunch of different perspectives that might help a little, as they did for me, when those wiser than me shared them.

These include:

✅ validating that many people feel this way regularly: it's a very normal feeling of frustration

🧩 the meeting organizer / runner may well not have wanted the gig in the first place, or felt like they're not capable: they've nevertheless offered to step up when asked: this is a distinct and frequent occurrence that won't always be obvious to you as attendee

💬 if the organizer is doing a noticeably horrendous job (goes for anything, not just meetings): they could just be having a really bad day: check that they're OK!

🔄 the shoe has been on the other foot at some stage: whilst you'll be aware of others getting frustrated in some of the meetings you've run, I can guarantee there are other occasions where you didn't pick up on the frustration

🧠 sanity preserving tip: whilst it's tempting (and true to some extent) to directly equate the 2 hours you spent in a meeting as wasted time you could have used to do other important things, if you do this too often and too much you'll go insane. Check out a little bit mentally!

⚖️ whilst in theory being surrounded by super colleagues who are amazing and much better than you at everything sounds nice, it's also overwhelming, and often demoralizing - how can you contribute? So when someone isn't that good at something, remind yourself it's an inevitable byproduct of being somewhere where you can provide real value and contribution.

📢 provide tactful and polite feedback and suggestions to improve processes, but don't break yourself, especially as an early career individual, to completely transform an organization's entire process culture overnight (unless you're in the executive!)

🎯 meeting frustration is partly a byproduct of the perspective and role you bring to a meeting: senior mentors and leaders are often more likely to see fumbled meetings and missteps as an essential development opportunity for the individual: learning often has a bit of "collateral damage" - you in the meeting - obviously getting the balance right is key.

🎈 for yourself, aim for "good enough" engagement rather than excelling, to depressurize the situation and lower your expectation bar

🗣️ once you've cooled off, talk to the more experienced meeting-goers for a second perspective!

💻 YouTube link: https://youtu.be/y6l4UxhLvo8

#meetings #organization #frustration #stress #timemanagement #leadership #collegiality #communication #careeradvice

🤔 𝐖𝐡𝐲 𝐌𝐞? 🤷‍♂️ 𝐖𝐡𝐲 𝐍𝐨𝐭 𝐌𝐞?

In your career, you’ll regularly hit moments where your confidence doesn’t match everyone else’s.

🤔 “Why Me?”

 Someone suggests nominating you for an award - and you think, “No way I’m worthy of that!”

🤷‍♂️ “Why Not Me?”

You’re convinced you’re ready for a promotion - so you’re shocked when those involved say you’re not quite there.

In today's #HackingAcademia video, I dive into these two situations, particularly focusing on a few key points:

🛠️ That you won’t always be able to “solve” the situation: nevertheless, how you act is important.

🌐 That you don’t always have the big picture: the person putting you up for something (the Why Me? situation) may know stuff that you don’t; likewise, when knocked back for something you were sure of (the Why Not Me? situation), the individuals involved may know much more of the broader context than you do.

🗣️ The importance of (as calmly as possible in the Why Not Me? situation) explaining that you’re surprised, that you’d been expecting to be suitable because of X, Y, and Z, and asking for feedback as to why they assess the situation differently to you—often this information is best processed later on at leisure, rather than on the spot in the heat of the moment.

🏆 the reassurance that that imposter syndrome / I'm not worthy feeling often exists even after people win the award! It's very normal...

🚫 The need (in the Why Not Me? situation) to avoid outright threats and shouting matches at all costs: these are often near-irretrievable outcomes from which all parties involved will struggle to recover.

🧩 That the “Why Not Me?” situation will sometimes have an overarching reason for the outcome: when going through the individual details it may feel like none of those in isolation is enough reason or you have a response to, but often it’s about the aggregate.

In a professional workplace there will, on occasion, be situations where someone is very clearly being screwed over (talk to an external objective expert for a second opinion if you suspect this is the case): the vast majority of situations though will be less explicit and often more fuzzy.

If you can keep the process as professional as possible, find out as much as possible, explain your viewpoint as clearly and objectively as possible, you'll be in a much better situation to (sometimes) resolve the situation directly, but more generally be better prepared (and better informed, both you and the other parties) for the next time it comes up.

💻 YouTube link: https://youtu.be/4jPXsNYRWms

#careeradvice #confidence #promotion #awards #fellowships #jobs #feedback #criticism #evaluation #judgement #critical #growth #learning #advice #advising #mentoring

Time for an update on #ArtificialIntelligence, from my personal perspective in a professional context: my continued exploration of its intense usage in a day-to-day career (2 and a bit years and counting).

Key concepts include:

🧠 Force Multiplying Experts More Than Beginners

In my experience, these AI tools are helping experts more than anyone else. If three things come together:

🔹 an expert who knows very well how to do the task entirely themselves
🔹 someone experienced at giving detailed, nuanced, and error-robust instructions to achieve an overall goal and sub-goals
🔹 someone who can effortlessly glance at output and judge whether it’s correct (again, they need to be an expert in the task they're using AI to assist with)

✨ Then these tools are like adding a superpower – but their benefit diminishes if even one of those components is missing.

🛠️ There’s a good and bad way to integrate AI into your workflow: forcing it through a rigid list of steps is risky. The best results come from flexibly exploring where it can help most and adapting around its shortcomings.

⚡ They’re great at helping maintain momentum when you’re tired, sick, unmotivated, or just not feeling it. It takes a lot less to “get over the hump” with AI assistance than when it’s all on you.

🔄 I can iterate and work with these tools guilt-free – no etiquette, no need to provide fulfilling work like I would with a colleague. That freedom to rapidly try and discard half-baked ideas without wasting someone’s time is huge.
(Yes, I know some would say that’s already how some profs treat students, but I hope that’s the exception, not the rule.)

🚧 Key challenges that remain:

🧩 Knowing how much to pre-prepare and modularize a task – especially as newer tools reduce that need
 🧪 Knowing whether repeated failures are from bad prompting or fundamental limitations of the tool
 🛑 Knowing when to go manual-only – particularly at the polishing stage – and accepting that this varies project to project

🔮 I also share some thoughts on where I see all this heading, based on 2.5 years in a post-ChatGPT world.

💻 YouTube link: https://youtu.be/39Sz5ipFoqg 

#artificialintelligence #AI #technology #disruption #prediction #chatgpt #OpenAI #Anthropic #MidJourney #AdobeFirefly #Firefly #Suno