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Benjamin Schoedinger, M.Sc.

Master Thesis Student at the Montanuniversität Leoben

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Short bio:

Research Interests

  • Robotics

Thesis

Contact

Benjamin Schoedinger, B.Sc
Master Thesis Student at the Chair of Cyber-Physical-Systems
Montanuniversität Leoben
Franz-Josef-Straße 18, 
8700 Leoben, Austria 

Email:   




Christoph Andres, B.Sc.

Bachelor Thesis Student at the Montanuniversität Leoben

Christoph_Andres

Short bio:

Christoph is a bachelor student in Mechanical Engineering at Montanuniversität Leoben. His fascination for industrial robotics and automation already started at high school, where he worked on a collaborative robotics project during his final thesis.

 

In June 2023, he finished his bachelor’s thesis at CPS.

Research Interests

  • Robotics

Thesis

Contact

Christoph Andres, B.Sc.
Bachelor Thesis Student at the Chair of Cyber-Physical-Systems
Montanuniversität Leoben
Franz-Josef-Straße 18, 
8700 Leoben, Austria  




Iye Szin Ang, M.Sc.

Doctoral Student at the Montanuniversität Leoben

Short bio: Iye Szin Ang join the CPS team in Nov. 2023 as doctoral student. Before that she completed her Master thesis at the chair within the Erasmus Mundus Joint Master Degree in Photonics for Security Reliability and Safety (PSRS). Her thesis topic was on human-robot interaction using sign language. 

Continuing her prior work, she aims in her doctoral study at creating a natural and intuitive way for humans to communicate with machines. This approach will not only make robots more inclusive and accessible, but also provide a non-verbal and non-intrusive way for people to control and communicate with them. With a passion for advancing the field of CPS through cutting-edge research and innovation, Iye Szin is dedicated to creating more meaningful and inclusive technology for everyone.

Research Interests

  • Robotics
  • Human-Robot-Interaction
  • Deep Learning

Thesis

Contact

Iye Szin Ang, B.Sc
Doctoral Student at the Chair of Cyber-Physical-Systems
Montanuniversität Leoben
Franz-Josef-Straße 18, 
8700 Leoben, Austria 

Email: iye.ang@unileoben.ac.at




Christopher Martin Shimmin, M.Sc.

Master Thesis Student at the Montanuniversität Leoben

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Short bio: Christopher is a master student in Industrial Engineering with a specialization in Data Science at the Polytechnic University of Catalunya (UPC BarcelonaTech) and, as of September 2023, finished his master thesis at the Chair of Cyber-Physical Systems in Montanuniversität Leoben.

Graduated in June 2020 from his Bachelor studies in Electronics Engineering from Tecnocampus Mataro (UPF) where he was a member of the Bytemaster Tecnocampus Racing Team, which participated in the 6th edition of the Motostudent competition. Furthermore, he is a current member of the Montan Factory Racing team in Montanuniversität Leoben, which will be participating in the 7th edition of the Motostudent competition in October 2023.

Research Interests

  • Bayesian optimization
  • Cyber-physical systems applied to Motorsports Mechatronic systems Digital twins

Thesis

Contact

Christopher Martin Shimmin, M. Sc.
Master Thesis Student at the Chair of Cyber-Physical-Systems
Montanuniversität Leoben
Franz-Josef-Straße 18,
8700 Leoben, Austria 

Email: : : christopher.martin@estudiantat.upc.edu

christopher.martin-shimmin@stud.unileoben.ac.at

 




Marco Schwarz

Bachelor Thesis Student at the Montanuniversität Leoben

Short bio: After starting his education in the field of mechanical engineering, Marco followed his growing passion domain of computer science, especially focusing on machine learning.

Currently, he is finishing his bachelor’s degree in Industrial Data Science at the Montanuniverstät Leoben. Since 2021 he is working at the Department of Information Technology. Additionally, since 2022 Marco works as a software developer at voestalpine Wire Austria GmbH.

In his thesis, he is developing a program to simplify the interaction between the ROS2 and the ESP32 microcontroller.

Research Interests

  • Robotics

Thesis

Contact

Marco Schwarz
Bachelor Thesis Student at the Chair of Cyber-Physical-Systems
Montanuniversität Leoben
Franz-Josef-Straße 18, 
8700 Leoben, Austria 




Pratheesh Nair, B.Sc.

Master Thesis Student at the Montanuniversität Leoben

Short bio:

Research Interests

  • Robotics

Thesis

Contact

Pratheesh, B.Sc
Master Thesis Student at the Chair of Cyber-Physical-Systems
Montanuniversität Leoben
Franz-Josef-Straße 18, 
8700 Leoben, Austria 

Email:   




Melanie Neubauer, M.Sc.

Ph.D. Student at the Montanuniversität Leoben

Hi! My Name is Melanie Neubauer and I started at the CPS-Chair in April 2023. 

I studied Industrial Logistics at the Montanuniversität Leoben, where I passed my  Master’s defense in March 2023.

In my doctoral work, I investigate  deep neural networks for image processing in cyber-physical-systems combined with inverse reinforcement learning techniques.

The title of my doctoral work is: Vision-based Deep Inverse Reinforcement Learning

Research Interests

  • Cyber-Physical-Systems 
  • Robotics
  • Machine Learning

Contact

M.Sc. Melanie Neubauer
Doctoral Student supervised by Univ.-Prof. Dr. Elmar Rueckert since April 2023.
Montanuniversität Leoben
Franz-Josef-Straße 18, 
8700 Leoben, Austria 

Phone:  +43 3842 402 – 1901 (Sekretariat CPS)

Email:   melanie.neubauer@unileoben.ac.at
Web Work: CPS-Page
Chat: WEBEX

Publications

Sorry, no publications matched your criteria.




01.03.2023 Meeting Notes

Meeting Details

Date: 1st March 2023

Time : 11:00 – 11:45

Location : Chair of CPS, Montanuniverität Leoben

Participants: Univ.-Prof. Dr. Elmar Rueckert, Vedant Dave

Agenda

  1. Finalise the formulation of Iterative Empowerment and implement it.
  2. Complete the Information Bottleneck formulation.

Topic 1: Iterative Empowerment

  1. Finalise the formulation.
  2. Implement the formulation.

Topic 2: Information bottleneck

  1. Continue on the current formulation.

Literature

To be added

Next Meeting

TBD 




Self-supervised Learning for Few-Shot Learning – Internship Position

Start date: Open

Location: Leoben

Job Type: Internship

Duration: 3-6 months, depending on the level of applicant’s proficiency on the asked qualifications.

Keywords: Self-supervised learning, Few-shot learning, Deep learning, PyTorch, Research

Supervisors:

Job Description

We are looking for a highly motivated research intern to work on the development of novel self-supervised learning algorithms to improve few-shot learning. The intern will be responsible for conducting research on self-supervised learning techniques such as contrastive learning and generative models, and their applications to few-shot learning. The intern will also be responsible for implementing and evaluating these algorithms on benchmark datasets.

Responsibilities

  • Conduct research on self-supervised learning techniques for few-shot learning.
  • Develop novel self-supervised learning algorithms and evaluate their performance on benchmark datasets.
  • Implement and fine-tune deep learning models for few-shot learning using self-supervised pre-training.
  • Collaborate with the research team to design and carry out experiments and analyze results.
  • Contribute to writing research papers and technical reports.

Qualifications

  • Currently pursuing a Bachelor’s or Master’s degree in Computer Science,
    Electrical Engineering, Mechanical Engineering, Mathematics or related
    fields.
  • Strong programming skills in Python and experience with deep learning frameworks such as PyTorch or TensorFlow.
  • Familiarity with self-supervised learning techniques such as contrastive learning and generative models.
  • Knowledge of few-shot learning and transfer learning is a plus.
  • Strong problem-solving skills and ability to work independently and collaboratively.
  • Good written and verbal communication skills in English.

Opportunities and Benefits of the Internship

This internship provides an excellent opportunity to gain hands-on experience in cutting-edge research on self-supervised learning for few-shot learning, working with a highly collaborative and supportive team. The intern will also have the opportunity to co-author research papers and technical reports, and participate in conferences and workshops.

Application

Send us your CV accompanied by a letter of motivation at fotios.lygerakis@unileoben.ac.at with the subject: “Internship Application | Self-supervised Learning”

Funding

We will support you during your application for an internship grant. Below we list some relevant grant application details.

CEEPUS grant (European for undergrads and graduates)

Find details on the Central European Exchange Program for University Studies program at https://grants.at/en/ or at https://www.ceepus.info.

In principle, you can apply at any time for a scholarship. However, also your country of origin matters and there exist networks of several countries that have their own contingent.

Ernst Mach Grant (Worldwide for PhDs and Seniors)

Find details on the program at https://grants.at/en/ or at https://oead.at/en/to-austria/grants-and-scholarships/ernst-mach-grant.

Rest Funding Resourses

Apply online at http://www.scholarships.at/




Meeting Notes February 2023

Meeting 02/02

Research

  • Follow up CR-VAE
    • Files on the papers folder
    • Create simple code to run experiments as described on paper
      • Upload on gitea
    • Create a webpage for CR-VAE paper
    • Wait for reviews (March 13)
    • Rebuttal (March 19)
  • Extend the representation learning work towards disentanglement
    • Literature Review
    • Dig deeper into Transformers
  • Literature Review on SOTA RL algorithms
    • Read and implement basic and SOTA RL algorithms
      • Can be the base of an RL course too.
  • Use CR-VAE with SOTA RL algorithms
    • First experiments with SAC
    • Explore sample efficiency
    • Explore gradient flow ablations
  • Develop an AR-ROS2 framework
    • Create a minimal working example of manipulating a physical robot (UR3) with Hololens2

M.Sc. Students/Interns

  • Melanie
    • Thesis Review
    • Code submission
  • Sign Language project
    • Define the project more clearly
      • Feedback needed
    • Send study details to the applicant
  • AR project
    • Is it within the scope of our research?

ML Assistantship

  • Syllabus
  • Prepare exercises 

Miscellaneous

  • Ph.D. registration
    • Mentor
      • Ortner Ronald?
      • Other UNI?
  • Retreats
    • expectations/requirements
  • Summer School
  • Neural Coffee (ML Reading Group)
    • When: Every Friday 10:00-12:00
    • Where: CPS Kitchen (?)
    • Poster
  • Floor and Desk Lamps

Meeting 16/02

Research

  • create a new research draft
    • implement CURL
    • substitute contrastive learning with CR-VAE representations
  • Literature review on unsupervised learning (Hinton’s work) to find out ankles that have room for improvement
    • write a journal on that

Summer School

  • Cv &  motivation letter feedback
  • Applied

M.Sc. Students/Interns

  • Melanie: thesis review done
  • Iye Szin:
    • Gave her resources to study (ML/NN/ROS2)
    • Discussed a plan for internship

Ph.D. registration

  • PhD in Computer Science
    • Not possible
    • probably doesn’t matter(?)
  • Call with Dean of Studies
  • Mentor
    • I would like someone exposed to sample-efficient and robust Reinforcement Learning. Hopefully to Robot Learning too
    • Someone that can also extend my scientific network of people  
    • Can I ask professors from other universities?
  • Mentor Candidates
    • Marc Toussaint, Learning and Intelligent Systems lab, TU Berlin, Germany
    • Abhinav Valada, Robot Learning Lab, University of Freiburg, Germany
    • Georgia Chalvatzaki, IAS, TU Darmstadt, Germany
    • Edward Johns, Robot Learning Lab, Imperial College London, UK
    • Sepp Hochreiter, Institute of Machine Learning, JKU Linz, Austria
  • Write a paper with a mentor

ML Course

  • Jupyter notebooks or old code? If Jyputer notebooks, why not google collab?
  • What will the context of lectures be so that I can prepare exercises accordingly?
    • lectures are up
  • 20% of the final exam is from the lab exercises
  • Decide on the lecture format
  • Find an appropriate dataset

Miscellaneous

Science Breakfast @MUL: 14/02 11:00-12:00

Anymal Robot at Mining chair on 15/02?

Effective Communication In Academia Seminar

  • Feedback on CPS presentation template:
    • Size: Make the slide size the same as PowerPoint (more rectangular).
    • Outline (left outline)
      • We could skip the subsections. Keep only the higher sections
      • Make the fonts darker. They are not easily visible on a projector
    • Colors
      • Color of boxes (frames) must become darker, otherwise it is not easily distinguishable from the white background on a projector
  • Idea: Create a Google Slide template
    • Easier to use
    • Can add arrows, circles, etc
    • Easier with tables

Meeting 28/02

Research

  • air-hokey challenge

M.Sc. Students/Interns

  • Iye Szin:
    • starts 2 March
    • Elmar has to sign documents (permanent position)
    • Allocation of HW
    • transpornder

Ph.D. registration

  • Mentor can be from anywhere
  • Mentor has to be a recognized scientist (with a “venia docendi” if he/she is from the German-speaking world)
  • No courses or ects needed
  • the mentor must not be a reviewer of your thesis. He can be an examiner, though.
  • Email to Marc Toussaint?
  • Officially: no obligations
  • Unofficially: propose common reasearch

ML Course

  • Google Collab
    • Uses the jupyter format.
    • Runs online
    • Even supports limited access to GPU/TPU
    • Speeds up learning process
  • Do we need latex?
    • yes
  • Update slides for the Lab accordingly
  • Submission at a folder in the cloud
    • ipynb file
    • report
    • zipped and named : firstname_lastname_m00000_assignment1.zip
  • Online lectures -> webex more stable
  • Google slides template
  • Grading
    • 100 pts
    • latex report: +10
    • optional exercise: +20
  • tweetback: 3 questions

Miscellaneous

    • IAS retreat
    • Melanie’s presentation