Mind Meets Machine: Global

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Mind Meets Machine explores the evolving relationship between neurotech, artificial intelligence, human cognition, mental health and leadership. From AI systems and strategy to neurotechnology, brain-computer interfaces, and human augmentation, this podcast examines how intelligent machines are reshaping decision-making, leadership, and the future of work. Through thoughtful conversations and deep dives, we ask: How do we build intelligence that amplifies human potential, not replaces it? For builders, leaders, and thinkers shaping the Intelligence Era.

  1. 1d ago

    Building Decision-Grade Evidence for Health Product Success with Bahareh Kardeh

    Many health products look solid on paper and still fall apart in the real world. Often the gap is not the technology. It is the evidence behind the decisions. In this episode, I sat down with @Bahareh Kardeh, founder and principal consultant at BrightPath Consulting, to talk about how health product teams can move from assumptions to confident decisions. Bahareh brings a rare combination to this conversation: a physician’s training and research into why people choose to adopt or reject technology. She walks through ProofStack, her framework for turning messy inputs into evidence teams can actually act on, from early discovery through long-term growth. We also get into the question she wishes more clients would ask, and why it matters more than most teams realize.Some of the key topics we discussed: 🔹 What separates “decision-grade evidence” from the data most teams already have🔹 Why technology adoption in healthcare depends as much on clinicians, workflows and procurement as on the end user🔹 What startups often misread about how hospitals and health authorities make decisions, and how governance shapes the path to a greenlight🔹 What a well-run device evaluation looks like, and the risks teams take on when they skip it For anyone building, funding or buying health technology, this is a practical look at reducing risk before it becomes expensive.

  2. Oct 23

    Keeping the Brain in Balance: Neurons, Noise and Healing Scars with Ankit Roy

    Your neurons are constantly working to stay in balance. When that balance slips, the consequences can be serious. I spoke with neuroscientist Ankit Roy about how the brain keeps its activity in check, and what happens when it doesn't. A few insights that stood out: 🔹 Too little activity and the brain can't convey information properly. Too much and it becomes unstable, as seen in epilepsy. 🔹 A neuron's "set point" isn't fixed. It varies by neuron type, brain region and stage of life.🔹 Noise in the brain is a "necessary evil." It can push weak signals over the threshold and make brain activity more robust. This matters for anyone building brain-computer interfaces.🔹 Astrocytes, long seen as mere support cells, actively contain damage by forming scars.

  3. Oct 14

    Sound Meets Signal: Jean Rintoul on Ultrasound Neuromodulation, Open-Source Hardware, and Bridging the Translation Gap

    My latest guest on Mind Meets Machine: Global is Jean Rintoul, founder of Minds Eye Labs, who has built hardware across multiple biosensor products and is now working on non-invasive ways to sense and stimulate the brain using ultrasound. A few insights that stood out: 🔹 Translation needs its own funding model. Academic grants reward novel findings, and VC funding looks for products. The unglamorous engineering in between, making a prototype reliable and repeatable, often falls through the gap. Jean argues for staged funding as evidence gets stronger, and for rewarding replication, negative results, and the engineers behind the shiny clinical result. 🔹 Open, affordable tools change who gets to participate. Jean built and crowdfunded Spectra, an open-source Electrical Impedance Tomography kit that uses the same reconstruction approach as a CT scan. It makes no medical claims. It puts a research technique, usually locked inside papers and expensive equipment, into people's hands. Users have explored everything from fruit ripeness to tooth cavities to lung imaging. 🔹 Lead through uncertainty by removing it step by step. Uncertainty is core to science, but many failed experiments come from uncharacterized hardware or unexpected timing. Solidify everything else iteratively, so all that's left is the big question you set out to answer.

  4. Oct 13

    Signals with Purpose: Reza Khanbabaie on Seizure Prediction, Pharma-Backed Innovation and Patient-Centred Neurotech

    I sat down with Reza Khanbabaie a former founder and CEO with over 20 peer-reviewed papers and four patents, who has spent 25 years turning brain signals into technology for patients. Today he is at Mentis Care AI, building AI to detect and predict seizures for people living with epilepsy. A few insights that stood out: 🔹 Who backs you shapes what you build. Mentis Care AI is pharma-backed rather than venture-backed. A backer that knows the patient population helps you avoid costly mid-course changes in design and strategy, and gives the work a clearer long-term direction. 🔹 Clinical usefulness beats scientific novelty. A scientifically interesting signal isn't always a clinically useful one. With wearables, the question isn't how to replicate a clinical EEG with fewer sensors, but what information the task actually needs. 🔹 Leadership doesn't mean having all the answers. It's much more about creating an environment where other people can do their best work, helping the team ask better questions, removing obstacles, and creating the conditions for good ideas to emerge.

  5. Sep 14

    Turning a life altering facial paralysis into a remarkable career in neuroengineering: my conversation with Nilou Hashemi

    This week on Mind Meets Machine: Global, I sat down with Nilou Hashimi, whose path into neuroengineering started with an 11-hour emergency brain surgery. We covered a lot of ground: → How a decade of medical uncertainty, from a facial paralysis to a life-altering surgery, shaped Nilou's decision to pursue rehabilitation engineering and neuroscience → A parallel reflection on navigating health uncertainty and what it does to your sense of time and control → The unglamorous realities of running pediatric neuroscience studies: recruitment, attention spans, and getting clean signal from young, disabled participants → Where AI is already changing the pace of EEG and signal processing research, and where the field is still catching up → Whether we're close to predicting anxiety or panic states before they escalate, and why individual variability makes this harder than it sounds → The emerging (and still niche) world of space neuroscience, and what microgravity might teach us about the nervous system

  6. Sep 9

    From XR to EEG: Atif Mahmud on Turning Brainwaves into Actionable Signals

    This week: the gap between reading a brain signal and understanding what it means. I spoke with Atif Mahmud, a computational neuroscience researcher building real time EEG neurofeedback tools for children's emotional regulation, about the hard problems in translating brain data into usable insight. We cover:→ Why brain activity readings can be misleading without context→ How gaming architecture solved real time neurofeedback delivery→ Mindful, an EEG tool helping children self regulate→ The rigor gap between engineering and science→ A closing thought experiment on privacy versus collective safety A sharp look at what it takes to build trustworthy neurotech.

  7. Aug 14

    Biotech At The Crossroads: Trade, War & the Future of Medical Innovation

    While GLP-1 drugs and established medtech pulled in billions and shrugged off tariffs, early-stage biotech funding hit a five-year low and neurotech startups were left fighting for scraps. → Political leverage is now a balance sheet asset. Novo Nordisk and Eli Lilly negotiated directly with the White House and walked away with three years of tariff relief. That's not luck. That's strategic positioning translating straight into capital insulation. → The companies best placed to benefit from reshoring incentives are the least likely to need them. Large pharma has the balance sheet to onshore and negotiate. The startups actually driving the next wave of innovation, especially in BCI and neurotech, have none of those levers. → Uncertainty is more expensive than bad news. The moment the MFN deal structure became visible, capital that had been sitting on the sidelines moved fast. Leaders who resolved ambiguity early outperformed the ones who waited for clarity to arrive on its own. → BCI is now a patient capital game. No revenue, no reimbursement, no seat at the negotiating table. The investors still in this space are underwriting a 7 to 10 year horizon, not a quarter. If you're leading, regulating, or investing anywhere near biotech or neurotech, the through-line is the same: the market is rewarding decisive adaptation, not wait-and-see. REFERENCES: [1] FDA API sourcing data, via DelveInsight (Sep 2025).[2] Grassi Advisors (Jun 2025).[3] DCAT Value Chain Insights (Apr 2025).[4] DCAT Value Chain Insights (Jul 2025).[5] Pharmaceutical Technology (Apr 2026) — source for BIO CEO John Crowley quote and pharma reshoring commitments.[6] Pharmaceutical Technology (Apr 2026) — 16 MFN companies incl. Pfizer, Eli Lilly, MSD.[7] White House Presidential Proclamation, Adjusting Imports of Pharmaceuticals (Apr 2026).[8] White House Proclamation [7]; Pharmaceutical Technology [5] — generics/biosimilars exemption.[9] ING analyst Diederik Stadig, via Pharmaceutical Technology [5].[10] Morrison Foerster, BIOSECURE Act Update (Dec 2025).[11] Baker McKenzie, The BIOSECURE Act Becomes Law (Jan 2026).[12] Latham & Watkins, BIOSECURE Act Becomes Law.[13] DelveInsight [1] — 4-in-10 generics/Chinese APIs; reshoring announcements.[14] BIO member survey (Mar 2025), via DCAT VCI [4] and HubXchange (Apr 2025).[15] DelveInsight [1] — 25% Canada/Mexico device tariffs.[16] Janus Henderson Investors, Why Healthcare Stocks Could Excel in 2026 (Dec 2025).[17] EY, Pulse of the MedTech Report 2025 (Sep/Oct 2025).[18] Granted AI, FY2026 Science Budget Scorecard (Feb 2026); FABBS, FY26 Budget Request (Jun 2025) for proposed-cut context.[19] MDC Associates, NIH Budget Cuts and Realignment (2025).[20] Andersen Lab, BCIs in 2025: Trials, Progress, and Challenges (Jul 2025).[21] Fortune Business Insights, Brain Computer Interface Market.[22] Prime Therapeutics, GLP-1 Pipeline Update (Nov 2025).[23] IQVIA, Outlook for Obesity in 2026 (Jan 2026).[24] EY, Pulse of the MedTech Report 2025 [17].[25] BioPharma Dive / HSBC Innovation Banking (Jul 2025).[26] Ropes & Gray LLP, From Volatility to Vitality (Mar 2026).[27] Janus Henderson Investors [16].[28] William Blair, The Quarterly Rx: Q2 2025 Recap (Jul 2025).[29] Pharmaceutical Technology, Biotech Recovery in Q3 2025 (Oct 2025).[30] PitchBook Q2 2025 MedTech VC Trends, via HTD Health (Jan 2026).[31] IQVIA [23].[32] Labiotech.eu, Six Key Obesity Deals of 2025 (Dec 2025).[33] IQVIA [23].[34] J.P. Morgan, Weight Loss Drug Supply and Demand in 2026 (Feb 2026).[35] Paradromics, Healthtech and the FDA (Nov 2025).

  8. Aug 6

    10 NeuroTech Use Cases That Could Put You Ahead of Your Own Mind

    What if a headset could tell you an anxiety attack was coming, moments before you felt it? That's not ten years out. In this episode of Mind Meets Machine: Global, I go through 10 potential and real use cases for non-invasive brain-computer interfaces: anxiety, addiction, trauma therapy, ADHD, insomnia, loneliness, even early psychosis detection.And then I paint a highly detailed scenario and ask the question I couldn't stop thinking about: if this same technology could flag when someone nearby is entering a violent mental state, would you want to know? Would you agree to share your own neural data in exchange for that alert? REFERENCES: Davidson, R. J. (1995). Cerebral asymmetry, emotion, and affective style. In Brain Asymmetry. MIT Press. Thibodeau, R., Jorgensen, R. S., & Kim, S. (2006). Can EEG asymmetry patterns predict future development of anxiety and depression? Biological Psychology. https://doi.org/10.1016/j.biopsycho.2005.09.003 Scientific Reports. (2025). The power spectrum and functional connectivity characteristics of resting-state EEG in patients with generalized anxiety disorder. Frontiers in Psychiatry. (2025). Neurofeedback in substance and non-substance-related addictions: A mini review of current evidence and future directions. Peniston, E. G., & Kulkosky, P. J. (1989, 1990). Alpha-theta brainwave training for alcoholism. Snyder, S. M., et al. (2013). FDA-cleared NEBA System for ADHD assessment. Neurology. https://doi.org/10.1212/WNL.0000000000003265 Neurosity. (2026). EEG Biomarkers for ADHD: What Are We Looking For? Sleep Medicine. (2025). Estimation of the global prevalence and burden of insomnia: A systematic literature review-based analysis. World Health Organization. (2023). WHO Commission on Social Connection. Morrish, N., et al. (2025). How loneliness relates to health, wellbeing, quality of life, and healthcare resource utilisation and costs across multiple age groups in the UK. PLOS ONE. https://doi.org/10.1371/journal.pone.0327671 Schall, U., et al. (2015). Mismatch negativity as biomarker predicting psychosis in clinically at-risk individuals. Bodatsch, M., et al. (2013). Mismatch negativity as a translatable brain marker toward early intervention for psychosis. Roth, M., et al. (2018). Resting-state brain fluctuation and functional connectivity dissociate moral injury from PTSD. bioRxiv. Holroyd, C. B., & Coles, M. G. H. (2002). The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review. Fortune. (2026). A decade after the Godfather of AI said radiologists were obsolete, their salaries are up to $571K and demand is growing fast. Mousa, D. (2025). AI Isn't Replacing Radiologists. Works in Progress / Understanding AI. CNN Business. (2026). Worried about AI replacing your job? This job has become the ultimate case study for why it won't. Towards New Human Rights in the Age of Neuroscience and Neurotechnology — Ienca, M., & Andorno, R. (2017). (Springer) Neurorights Foundation. UNESCO. (2021). Recommendation on the Ethics of Artificial Intelligence. (unesdoc.unesco.org)

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Mind Meets Machine explores the evolving relationship between neurotech, artificial intelligence, human cognition, mental health and leadership. From AI systems and strategy to neurotechnology, brain-computer interfaces, and human augmentation, this podcast examines how intelligent machines are reshaping decision-making, leadership, and the future of work. Through thoughtful conversations and deep dives, we ask: How do we build intelligence that amplifies human potential, not replaces it? For builders, leaders, and thinkers shaping the Intelligence Era.

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