Data & AI/ML Entrepreneur | Early Stage Investor

Over a decade of experience within AI/ML and Data Infrastructure as a founder, operator and investor.Passionate about bringing new and paradigm-shifting technologies to market. This passion has led me to a over decade-long entrepreneurial career focused on emerging software industries and global markets - from AI &amp; Data Infrastructure startups and venture capital funds to Fortune 500 technology leaders such as Google. Raised +$50M in early-stage funding from top VCs as a founder and operator. A big believer in people, data, design and telling a story. Passionate about building new products with the right GTM, messaging and growing teams that do so.Deep understanding of the venture capital, private equity, SaaS, cloud, data and AI ecosystems with solid global relationships at all levels.Frequent keynote speaker on topics around data, AI, startups and venture capital. Considered as one of the top AI &amp; data thought leaders in the Nordics.

Oliver Molander

How quickly Norwegian (and soon Danish) founders leave the country when the government sets a tax on unrealized gains.

Let’s make this clear:

Any developed government that thinks citizens should pay unrealized capital gains tax on illiquid assets is simply anti-entrepreneur and anti-business.

#founders

Sweden is not only becoming the AI application capital of Europe, but also Europe's new capital of capital.

But why does Sweden have so many unicorns? And why does it feel like we have more momentum than ever during the AI platform shift?

I’ve been saying for years that it’s a mix of factors that have compounded over decades.

Early role models who went for the global maximum (e.g. Niklas Zennström, Daniel Ek). Strong founder factories producing highly technical talent (e.g. Spotify, King, Klarna, iZettle). A new wave of AI-native founder factories (Depict AI). Strong technical institutions like KTH. Early grassroots communities for builders like Stockholm AI. Strong UX and product taste.

Add liquidity events that created a strong angel culture combined with a campus-like density of talent, founders and capital (almost everyone is a 10-minute walk from each other). That’s when things start compounding fast.

And as a final catalyst: a new generation - what we call the YC generation - showing what’s possible and becoming role models themselves (e.g. Anton at Lovable, Max at Legora).

But there’s another piece that doesn’t get talked about enough: tax policy.

Luis Garicano (Professor of Public Policy at LSE, PhD in Economics from UChicago and ex-Member of the European Parliament) wrote a good post about this (link in comments).

Tax policy reflects what a society values. If you value production and creation, you reward it. If you value redistribution more, you extract and redistribute.

Sweden had a solid first wave of tech companies (Skype, Spotify, King, iZettle, Klarna). What really mattered is what happened next. Alumni from those companies went on to start a huge number of new ventures.

One reason is a 2003 tax reform that allows corporate capital gains from selling shares in unlisted companies to be deferred as long as the money is reinvested into other unlisted companies. Since Swedish founders and early employees often hold their shares through a company, this created a strong incentive to recycle capital after an exit.

Sweden didn’t create angel investors through subsidies. It created the conditions for them to emerge naturally: exits, reinvestment incentives, and a culture where starting again is normal.

Sweden also scrapped the wealth tax (2007) and inheritance and gift taxes (2005). The ISK account (introduced in 2012) made equity investing simpler and more accessible. By 2023, Sweden’s market cap was 169% of GDP - more than double the EU average.

And importantly: startups need exits. 

Sweden has deep, multi-layered public markets. Between 2016 and 2023, Sweden had 823 IPOs - the most in the EU - with nearly 90% on SME growth markets.

None of this happened overnight. It compounded.

And now we’re seeing the result combined with a generational AI opportunity.

#artificialintelligence

What if HF0 Residency and the Thiel Fellowship had a baby?

We’ll never know.

What we do know is this:

The Nordics and Baltics have a long history of producing technical outliers - and billion-dollar outcomes.

Now the AI platform shift is triggering a fundamental mindset reset across the region.

More ambitious.
More technical.
More fearless.
Younger than ever.

Enter Frontier Residency.

This is extreme signal-to-noise.

10 young technical outliers from the New Nordics. 5 frontier AI companies.

This is about catalyzing the next generation.

Letting them see where the global maximum is early.

And creating clear second- and third-order effects across the ecosystem.

More to come.

Change will never be this slow again.

#artificialintelligence

Given everything that’s happened over the past few months, it feels more evident than ever that we chose the right slogan for Inception Fund.

We’re still early.

PS. Here's a great blog post by Kenneth on the importance of technical founders in this day and age: https://lnkd.in/dpfmjRDv

"If anything, the bar for technical leadership is higher now. It's no longer enough to be a great engineer who can write clean code and lead humans.

You need someone who understands the current AI landscape, who can evaluate when to use agents versus when to write code by hand, who can make the right build-versus-buy decisions, and most importantly: who can help you stay ahead of the curve, in a world where the options are compounding exponentially."

#artificialintelligence

Medical University of South Carolina

Head of Data Analytics & Statistics Unit at the Institute of Psychiatry and Behavioral Science
Member of the Sleep and Anxiety, Olfactory Function, PTSD Research Groups 

Present Research Foci: Brain Dynamics, Signaling in the Brain, Sleep, MRI/fMRI, Data Analysis Methodology, Complexity Science and Complex Networks, Statistics and Extreme Value Statistics, Machine Learning, Neuronal Networks, Pattern Recognition.

Research Assistant Professor & Center Statistician

Computational Neuroscience, Neuroimaging, MRI/fMRI Research:
Analyzed full-brain, high-resolution (0.8mm^3) fMRI data using
GLM and stochastic noise models, multivariate regression
analysis, and machine learning (deep learning, neural networks). Implemented an
automated fMRI-data preprocessing pipeline combining various alignment- and
dynamic time-space warping methods. Improved a 3D-visualization toolbox for fMRI data (VTK based). Outreach: Supervised senior research projects for local high-school students.

Postdoctoral Researcher - Computer Vision

College of Charleston

Assistant Professor for Mathematics & Statistics

The Citadel

Regularly taught lecture courses and labs on all topics of college physics.
Since 2016 more than one-thousand contact hours of instruction.

Courses taught each semester, multiple sections:
PHYS 203 - Algebra-based College Physics I - Introductory Physics for the Liberal Arts - Mechanics
PHYS 204 - Algebra-based College Physics II - Thermodynamics, Electromagnetism, SRT, Intro to Quantumphysics, Nuclear Physics, Modern Topics of Physics
PHYS 221 - Calculus-based College Physics I for Engineers and Physicists- Introductory Physics for the Liberal Arts - Mechanics
PHYS 222 - Calculus-based College Physics II for Engineers and Physicists - Thermodynamics, Electromagnetism, SRT, Intro to Quantumphysics, Nuclear Physics, Modern Topics of Physics
PHYS 253 - College Physics I Labs - Mechanics (Labs complementing PHYS 203)
PHYS 254 - College Physics II Labs - Thermodynamics, Electricity, Optics (Labs complementing PHYS 204 )
PHYS 271 - Calculus-Based Physics Labs I for Physicists and Engineers - Mechanics (Labs complementing PHYS 221)
PHYS 272 - Calculus-Based Physics Labs I for Physicists and Engineers - Thermodynamics, Electricity und Electromagnetism, Optics (Labs complementing PHYS 222)
PHYS 343 - Applied Climatology

Adjunct Professor for Physics

University of Lethbridge

Managed, preprocessed, and analyzed ~100TB time series data from multivariate electrophysiology; researched and implemented image analysis- and pattern recognition algorithms to study statistical properties of travelling waves in voltage sensitive dye imaging.
Utilized 768-core computing cluster (C++/OpenMP, Matlab). Designed and budgeted a petabyte
storage and computing system for optical brain imaging group.

Expert for Big Data Analytics, computational neuroscience, software & method development:
1. Research on pattern recognition in whole cortex in-vivo optical imaging data (e.g. voltage sensitive dye imaging, 2-photon calcium imaging) in mice with interest in evoked and spontaneous brain activity.
2. Research on functional brain networks using high-resolution, high-density, invasive, in-vivo electrophysiology in behaving rats
3. Cluster cutting algorithms for tetrode recordings
4. Hippocampal memory formation, consolidation, retrieval
5. Sleep physiology in behaving rats (EEG-data based)

Scientist at Canadian Centre for Behavioural Neuroscience / Polaris Group for Brain Dynamics

University of Calgary

Visiting Scholar at Complexity Science Group

Avatar EEG Solutions Inc.

Served as external scientific advisor on time series analysis, artifact removal, noise filtering and noise mitigation in EEG signals for a startup company developing a portable electro-physiological monitoring device until the company was acquired by EGI Inc. Secured R&D Funding for 2 Undergraduates and a Postdoctoral Associate in excess of $200,000 from Canadian and German Governments. Represented the Canadian Province of Alberta and Avatar EEG Inc. on an economic trade mission to Germany in 2013.

Scientific Consultant

Large Data Analysis
Scientific computing
Extreme Value Statistics
Stochastic Modeling, Prediction, and Forecasting
Functional Networks
Persistence, Fractals
Seismic Data Processing
Earthquake research (e.g. Epidemic-type aftershock sequence model)
Sleep research, Physiological Data

Researched statistics of correlated heavy-tailed probability distributions (Levy-walks, Levy-flights). Studied statistics of extreme values and return intervals in simulated persistent alpha-stable
stochastic processes (Frechet, Weibull, Gumbel, Pareto -> GEV classes) and in seismic-, solar-, and physiological data. Implemented and studied probabilistic spatio-temporal epidemic-type earthquake models and fitted those models to historic seismic data from Southern California and Asia to statistically characterize and classify the underlying dynamics. Developed novel network analysis methods to extract causality, directionality, and weight of signal interdependence from multivariate time series. Teaching: Obtained Faculty Teaching Certificate & Instructional Skills Workshop Certificate from University of Calgary; taught lectures in introductory and graduate physics.

Postdoctoral Researcher Physics & Complex Systems

Martin Luther University Halle-Wittenberg

Stochastic Processes & Forecasting
(Multivariate) Time Series Analysis
Large Data and Databases
Extensive C/C++ programming
Financial Mathematics
Network Analysis
Focused on Complex System, in particular, on complex physiological systems.
Risk Assessment in Cardiology
Sleep Research
Teaching
Proposal Writing
Publications

Developed and implemented novel multivariate data analysis- and statistics tools for risk assessment and classification tasks in cardiology and sleep research. Studied and exploited statistical and fractal properties of long-term correlated noise fluctuations and
volatility time series by means of (Vector-)AR-, FARIMA-, GARCH-processes, and various (multifractal-)fluctuation analysis methods. Developed and deployed multivariate phase rectified signal averaging to study quasi-oscillations in time series. Designed surrogate
models for statistical hypothesis testing when analyzing real-world data. Supervised B.Sc. and M.Sc. theses, taught lectures in computer science, nonlinear dynamics + time series analysis, physics. Supervised physics labs for physics-, medical physics-, and medical students.
Served on Data Analytics and Methodology Team in European Union Project DAPHNET. Took post-completion analysis lead of European Union Project SIESTA. Presented results to European Commission.

Researcher & Ph.D. Student

Justus-Liebig University Giessen

See Martin-Luther University Halle-Wittenberg; joint appointment within EU project DAPHNET.

UC San Diego

C/C++ Programming
Coupled oscillator models
Stochastic Forecasting
Stochastic Modeling
Synchronization Analysis

Worked on perturbation models for phase- and general synchronization
in chaotic attractor systems with applications to weather-forecasting
models. Analyzed complex weather data (in collaboration with NCAR
Boulder, C.O. and University of Maryland); developed and implemented
real-time, data-driven weather prediction models in C/C++ using Lyapunov
vectors and Bred vectors to reduce dimensionality by only capturing fast-growing 
dynamical instabilities.

Visiting Scholar with M.Sc.

Experienced Head of Data Analysis and Statistics Unit | Assistant Professor
Theoretical Physicist with 15+ years experience in data science and engineering, data analytics, and methodology development with applications to real-world complex systems. Expert in Physics of Complex Systems, classical and advanced statistics, Bayesian statistics, multivariate time series and image analysis, stochastic processes and modeling, extreme values, Monte Carlo, and nonlinear dynamics applied across diverse fields of research, including projects in financial mathematics, weather modeling, climate research, probabilistic earthquake simulations, network dynamics, space physics, material science and fabrication processes, human cardiology and sleep physiology, public health, and in systems neuroscience of the brain.

Experienced in biomedical research and medical-device industry, and pharmaceutical organizations in Europe, Canada, and the United States. Skilled in building, leading, and managing diverse research- and analysis teams, study design, request for proposals, budgeting, demonstrating communication skills, and the ability to make critical decisions when needed.

taplio

The Battle

Oliver Molander

Aicko Yves Schumann, Dr. rer. nat.

Followers

Posts

Engagements

Likes

Performance ScoreOliver Molander's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Oliver Molander

Aicko Yves Schumann, Dr. rer. nat.

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Oliver Molander's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreOliver Molander's LinkedIn Performance