Cape Hoorn, 14th February 2013

Dr. Harald von Fellenberg
PhD, MSc Physics
Schützenrütistr. 19
CH-8044 Gockhausen

Email: hvf (at) hvf (dot) ch



DON'T MISS: my programs in Astronomy, Physics, and other themes here.

I try to write this web page according to the current HTML5 specs - a small exercise, so to speak. I am now in retirement and have given up my professional activities, but I follow the technical and social developments with vivid interest. Internet courses (MOOCs) and lectures at universities are part of my activities.


Security - My Experience

My first contact with the topic of computer security was in 1986, when first reports about computer viruses appeared in the newspapers. I tried then to create a self-replicating malware code, and I was surprised how simple this turned out to be. After that I started to analyze the security mechanisms of the operating system (UNIX System V) from the view point of a nuclear engineer (principle of barriers). From then on, I was always considered a UNIX security expert.

During my time with UBS I authored the OpenLAN Security Concept and was project manager of the Umbrella Project OpenLAN Security. During this time the bank's in-house smartcard solution PERSAUTH was being developed and deployed on some 40'000 workstations. PERSAUTH was used to securely manage logins and passwords for the numerous banking applications.

Here is my sales pitch from that time.

Security technology has degenerated to a pure product selling business over recent years. The relevant questions, namely the meaning of security, the definition of threats and countermeasures to be taken, are not asked anymore. This leads to a false sense of security. Quacksalvers and charlatanes profit from it.

However, if you are interested in real security for your IT infrastructure, I will be happy to write a security concept with you that is up to standards with the leading Swiss banking institution.

I like interesting projects in the realm of C, C++ on Linux, Solaris, FreeBSD and all other UN*X platforms, which the younger generation is not enthusiastic about (Perl, Fortran, Make). Windows and GUI programming are not on my radar.


Nuclear Calculations

My first job after my PhD graduation was with Electrowatt Enginnering in Zurich, where I worked in the realm of nuclear fuel management. For a project about the planned German nuclear waste repository in Gorleben I performed calculations about the composition of nuclear waste (nuclide inventories and their evolution over time). Some years ago some friends and I wrote an important treatise about the complete inventory of nuclear waste in the Federal Republic of Germany (including the new East-German Länder). This work was sponsored by the Federal Office of Radiation Protection, Braunschweig.

Here my sales pitch about my nuclear skills.

As a trained nuclear engineer with long standing experience I perform nuclide inventory calculations for radioactive waste, that are used in the assessment of security relevant questions for planned nuclear waste repositories. I also perform criticality calculations for spent nuclear fuel transport casks. All these calculations are done with internationally recognized and licensed codes.


My Services

Here my offering in the realm of consulting, training, programming.

Top Level Security Consulting




Programming (Selection)


My Assets


Professional Experience




Staying Up-to-date in Retirement

I am interested both in topics from computer science and topics from physics and astrophysics. Therefore the two areas are listed separately. Topics that apply to both areas (like quantum computing) are listed within computer science.

Courses from Physics and Astrophysics

  1. Advanced Fluid Mechanics 1: Fundamentals, MITx - 2.25.1x (2022) - Introduction into theoretical fluid mechanics for incompressible and inviscid fluids, Euler equation and Bernoulli equation on

  2. An Intuitive Introduction to Probability, University of Zürich, Prof. Karl Schmedders (2021) on
    A refreshing course that conveys the concepts of probability with good examples.

  3. Data Driven Astronomy, University of Sydney (2019) - on
    Starting with problems from radio astronomy and the classification of galaxies, the course shows methods and mistakes in the analysis of large data sets and gives an introduction to machine learning for the classification of galaxies.

  4. Statistical Mechanics: Algorithms and Computations, by École normale supérieure, Paris (2019) - on
    A fascinating yet difficult course to learn the application of Monte Carlo methods in the area of statistical mechanics. All sample programs are written in Python2, I have converted them to Python3.

  5. The Discovery of the Higgs Boson, The University of Edinburgh (2018) - on
    The evolution of basic ideas and models in physics from Maxwell over Einstein up to the standard model of high energy physics plus the description and discovery of the Higgs Boson are nicely explained. Peter Higgs comments his memories for each of the topics in the course.

  6. Particle Physics: an Introduction, University of Geneva (2018) - on
    Here I could refresh and expand my knowledge on the fast track about the discoveries since my student days, especially about the Standard Model, electroweak interaction, and the Higgs Boson.

  7. Introduction to Aeronautical Engineering, TU Delft (2017), AE111x on
    Up to now one of the most challenging and rewarding courses for me as a (non-active) pilot.
    One of the assignments was the development of a computational model for a water rocket, as we have known it as children. My physical model is here.

  8. The Sun and the Total Eclipse of August 2017, University of Colorado Boulder.

  9. Nuclear Reactor Physics Basics, National Research Nuclear University MEPhI (Moscow Engineering Physics Institute) (2017), MEPHI005x on

  10. Understanding Einstein: The Special Theory of Relativity, Stanford University (2017) on

  11. From the Big Bang to Dark Energy, The University of Tokyo (2017) on

  12. Exploring Exoplanets, second online course of the lecture series of the Australian National University (2021), ANUx - ANU-ASTRO2x on

  13. The Violent Universe, third online course of the lecture series of the Australian National University (2016), ANUx - ANU-ASTRO3x on

  14. Greatest Unsolved Mysteries of the Universe, first online course of the lecture series of the Australian National University (2015) ANUx-ANU-ASTRO1x on, with the course certificate ANU-Astro1x

  15. Cosmology, fourth online course of the lecture series of the Australian National University (2015) on with the course certificate ANU-Astro4x.

  16. Symmetries in Physics, by Prof. Matthias Gaberdiel, lecture and lab, ETHZ (2013)

  17. Quantum Field Theory I, by Prof. Matthias Gaberdiel, lecture and lab, ETHZ and UZH (2011)

  18. Statistical Methods and Analysis Techniques in Experimental Physics, by Prof. Christoph Grab, lecture and lab, ETHZ and UZH (2010)


Courses in Computer Science

  1. The Building Blocks of a Quantum Computer: Part 1, TU Delft, DelftX: QTM2x (2018) - on
    Introduction into four different technologies that are research topics for qubits and later quantum computers, including the required quantum mechanics for spin operations in ket notation. After the course I can better assess the potential of QC.

  2. Addressing Large Hadron Collider Challenges by Machine Learning, National Research University, Higher School of Economics, Moskau, Russland (2018) - on
    The Large Hadron Collider (LHC), CERN, Geneva, Switzerland is the largest data generation machine for the time being, it produces terabytes of data every second. The course elucidates modern methods for patteren recognition, particle identification, triggers, and the search for rare decays.
    Upon completion of the course I understand both the principles of the Experimental Physics and Machine Learning much better.

  3. Python for Data Science, University of San Diego California (2017), DSE200x
    This course uses modern tools like Jupyter notebooks and powerful libraries like numpy, pandas, matplotlib for processing of large datasets. Text and Twitter analysis is also included. Two individual projects have to be made, which are then graded in a peer review.

  4. Using Python for Research, Harvard University (2017) PH526x

  5. HTML5 Part 1: HTML5 Coding Essentials and Best Practices, W3Cx - HTML5.1x (2016)

  6. HTML5 Introduction, W3Cx - HTML5.0x (2016)

  7. Introduction to Computational Thinking and Data Science, Online Kurs The Massachusetts Institute of Technology (2016) MITx - 6.00.2x

  8. Enabling Technologies for Data Science and Analytics: The Internet of Things, Online Kurs der Columbia University, New York (2016) DS 103x

  9. Machine Learning for Data Science and Analytics, Online Kurs der Columbia University, New York (2016) DS 102x

  10. Statistical Thinking for Data Science and Analytics , Online Kurs der Columbia University, New York (2016) DS 101x

  11. Introduction to Computer Science and Programming Using Python, Online Kurs The Massachusetts Institute of Technology (2015) MITx 6.00.1x

  12. Cyberwar, Surveillance and Security, Online Kurs der University of Adelaide (2015) Cyber 101x


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