Stage-oe-small.jpg

Systems, Data, Simulation & Energy: Unterschied zwischen den Versionen

Aus Aifbportal
Wechseln zu:Navigation, Suche
 
(111 dazwischenliegende Versionen von 3 Benutzern werden nicht angezeigt)
Zeile 10: Zeile 10:
  
 
'''Keywords:''' Modeling and Simulation • Data-driven Simulation • Data Analytics • Digital Twins • Energy Efficiency • Reliability Modeling and Analysis
 
'''Keywords:''' Modeling and Simulation • Data-driven Simulation • Data Analytics • Digital Twins • Energy Efficiency • Reliability Modeling and Analysis
|Forschungsgruppenleiter=Sanja Lazarova-Molnar
+
|Beschreibung EN=The research group Systems, Data, Simulation & Energy (SYDSEN, pronounced "side-sin") is dedicated to advancing the field of Modeling and Simulation by developing new methods to utilize the abundant data from readily accessible Internet of Things (IoT) devices. Additionally, the research group investigates the synergies between Artificial Intelligence and Simulation to enhance both fields.
 +
 
 +
The application areas focus on cyber-physical systems, including smart factories and energy systems, with the aim of improving various performance metrics such as energy efficiency, production, and reliability. Our research contributes to optimizing the use of these systems and harnessing the benefits of IoT technology.
 +
 
 +
We take pride in being a research group that is at the forefront of this field and are always open to opportunities to collaborate with other researchers and interested parties. If you have any further questions or are interested in collaborating, please do not hesitate to contact us.
 +
 
 +
 
 +
'''Keywords:''' Modeling and Simulation • Data-driven Simulation • Data Analytics • Digital Twins • Energy Efficiency • Reliability Modeling and Analysis
 +
|Forschungsgruppenleiter=Sanja_Lazarova-Molnar
 
|Bild=logo_sydsen_small1.png
 
|Bild=logo_sydsen_small1.png
 
|Logo=logo_sydsen_hor1.png
 
|Logo=logo_sydsen_hor1.png
 
|Ehemalige Forschungsgruppe=Nein
 
|Ehemalige Forschungsgruppe=Nein
 
}}
 
}}
{{Rubrik|Open PhD and PostDoc positions}}
+
{{Forschungsgruppe Projektliste}}
We are in the process of building the research group. If you find the topics of digital twins, simulation, modelling, data analytics & energy, exciting, and would like to undertake a PhD or a PostDoc position with us, please send an email to <b>[https://aifb.kit.edu/web/Sanja_Lazarova-Molnar Prof. Sanja Lazarova-Molnar]<b>.
+
{{Rubrik|Active Projects}}
 +
* [https://aifb.kit.edu/web/One4All One4All]
 +
* [https://aifb.kit.edu/web/Project_Tyre_Road_Noise Tyre Road Noise]
 +
 
 +
{{Rubrik|Publications}}
 +
You can find the publications of our team at [https://researchgate.net/lab/KIT-SDU-Joint-Lab-with-focus-on-Simulation-Data-Digital-Twins-Sanja-Lazarova-Molnar here].
 +
 
 +
 
 +
{{Rubrik|Open Positions}}
 +
{| class="wikitable" style="margin:auto"
 +
|-
 +
| Student Assistant (HiWi) || [https://aifb.kit.edu/web/Stellenausschreibung213 Student Research Assistant (f/m/d) for Statistical and Machine Learning on Raod Traffic Noise]
 +
|-
 +
| Student Assistants(HiWi) || [https://aifb.kit.edu/web/Stellenausschreibung189 Student Assistants (HiWi)(f/m/d) in the Research Group Systems, Data, Simulation & Energy (SYDSEN)]
 +
|-
 +
| Open Ph.D. and PostDoc positions|| [https://aifb.kit.edu/web/Stellenausschreibung216 Open PhD and PostDoc positions at SYDSEN]
 +
|}
 +
 
 +
 
 +
{{#ask:[[Kategorie:Neuigkeit]][[Forschungsgruppe::Systems, Data, Simulation & Energy]]
 +
| ?Titel DE
 +
| ?Datum#ISO
 +
| sort=Datum
 +
|order=DESC
 +
|link=none
 +
|template=Neuigkeit kurz inline
 +
|format=template
 +
|intro={{Rubrik|News}}<table>
 +
|outro=</table>
 +
|limit=5
 +
}}
 +
 
 +
 
 +
{{Rubrik|Media & Press}}
 +
* [09. March 2024] Prof. Sanja Lazarova-Molnar quoted on [https://www.deutschlandfunk.de/hype-schaden-der-grosse-boom-der-ki-laesst-projekte-schnell-scheitern-dlf-052ec84a-100.html  Deutschlandfunk] on the topic "Hype-Schaden: Der große Boom der KI lässt Projekte schnell scheitern".
 +
 
 +
 
 +
{{Rubrik|Courses & Seminars}}
 +
We offer the following courses and seminars:
 +
* WS2023/24
 +
** [https://www.wiwi.kit.edu/mhbDetails.php?type=event&id=03BF3F00-46B9-422D-A801-B27BFCFE7DFF Grundlagen der Informatik II]
 +
** [https://ilias.studium.kit.edu/ilias.php?ref_id=2203532&cmdClass=ilrepositorygui&cmdNode=x1&baseClass=ilrepositorygui Data-driven Simulation for Industrial Systems (Seminar)]
 +
* SS2023/24
 +
** [https://campus.kit.edu/campus/lecturer/event.asp?gguid=0x4EED1A8245D34C7B934A001C983E284C&tguid=0xF75A1C1081B043628B5A1FBB5F6CDE30  Modeling and Simulation]
 +
** [https://campus.kit.edu/campus/all/event.asp?gguid=0x89FC4691CC884902982AC636CF29473C&from=&tabID=1&tguid=0xF75A1C1081B043628B5A1FBB5F6CDE30 Digital Twins (Seminar)]
 +
 
 +
{{Rubrik|Open Thesis Topics}}
 +
 
 +
 
 +
We are open for inquiries for supervision of Master and Bachelor projects. In particular, we would supervise thesis in the following broad topics:
 +
 
 +
* Modeling and Simulation: This topic involves developing mathematical models and creating computer simulations to represent real-world phenomena or systems. A thesis in this area could focus on the development of novel modeling techniques, simulation algorithms, or the application of modeling and simulation to solve specific problems in fields like engineering, economics, or healthcare.
 +
* Data-Driven Simulation: With the abundance of data available today, data-driven simulation focuses on utilizing data to improve the accuracy and realism of simulations. A thesis in this area may explore techniques for data integration, analysis, and validation to enhance simulation models, as well as investigating ways to leverage machine learning or statistical methods to optimize simulations based on real-world data.
 +
* Digital Twins: Digital twins are virtual replicas of physical systems, enabling real-time monitoring, analysis, and prediction. A thesis in this area could involve creating digital twin models, developing methods to synchronize digital twins with their physical counterparts, or exploring applications of digital twins in industries such as manufacturing, healthcare, or urban planning.
 +
* Process Mining: Process mining involves analyzing event logs to discover, monitor, and improve processes within organizations. A thesis in this area may focus on developing process mining algorithms, techniques for process discovery or conformance checking, or applying process mining to specific domains such as supply chain management or healthcare.
 +
* Simulation and Modeling for Energy Efficiency: This topic centers on using simulation and modeling techniques to optimize energy consumption, identify energy-efficient solutions, and evaluate the impact of different energy-related strategies. A thesis in this area could involve developing simulation models for energy systems, investigating energy management algorithms, or evaluating the effectiveness of energy-efficient technologies or policies.
 +
* Reliability Modeling and Analysis: Reliability modeling and analysis involve assessing the performance and dependability of systems to ensure smooth operations and minimize failures. A thesis in this area may focus on reliability modeling techniques, fault diagnosis methods, or reliability-based optimization approaches, with applications in fields such as manufacturing, energy systems, or critical infrastructures.
 +
 
 +
We are also interested in supervising theses that align with our research interests and involve collaborations with companies. Please contact us for more information and to discuss potential thesis opportunities.
 +
 
 +
{{Rubrik|Persons}}
 +
* [https://aifb.kit.edu/web/Sanja_Lazarova-Molnar Prof. Dr. Sanja Lazarova-Molnar] (Prof.)
 +
* [https://aifb.kit.edu/web/Min-Bin_Lin Dr. Min-Bin Lin] (Postdoctoral researcher)
 +
* [https://www.aifb.kit.edu/web/Atieh_Khodadadi Atieh Khodadadi] (Ph.D. Candidate)
 +
* [https://www.aifb.kit.edu/web/Manuel_G%C3%B6tz Manuel Götz] (Ph.D. Candidate)
 +
* [https://aifb.kit.edu/web/Michelle_Jungmann Michelle Jungmann] (Ph.D. Candidate)
 +
* [https://www.aifb.kit.edu/web/Elisabeth_Lieder Elisabeth Lieder] (Secretary)
 +
 
 +
{{#ask:[[Kategorie:Aktive_Lehrveranstaltung]][[Forschungsgruppe:Systems, Data, Simulation & Energy]][[Semester::SS]]
 +
| ?Titel DE
 +
| ?Lehrveranstaltungstype
 +
|sort=Lehrveranstaltungstype, Titel DE
 +
|order=DESC
 +
|link=none
 +
|template=Zeige Lehrveranstaltungen Systems, Data, Simulation & Energy
 +
|format=template
 +
|intro=<br />{{Rubrik|Lehrveranstaltungen im SS}}
 +
}}
 +
 
 +
{{Rubrik|Visiting Students }}
 +
SYDSEN welcomes visiting students from all over and seeks international partnerships.
 +
 
 +
We have hosted the following students:
  
  
[https://aifb.kit.edu/web/Stellenausschreibung178 Open Positions as SYDSEN]
+
* Rob Bemthuis, Ph.D. candidate at the [https://www.utwente.nl/en/ University of Twente], Netherlands.
 +
* Samuel Sanft, Bachelor student at the [https://www.princeton.edu/ University of Princeton], United States.
 +
* Behrouz Adibimanesh, Ph.D. candidate at [https://pg.edu.pl/ Gdańsk University of Technology], Poland.

Aktuelle Version vom 19. März 2024, 06:30 Uhr

Systems, Data, Simulation & Energy

Logo sydsen small1.png
Logo sydsen hor1.png




Sekretariat:
 
Beschreibung

The research group Systems, Data, Simulation & Energy (SYDSEN, pronounced "side-sin") is dedicated to advancing the field of Modeling and Simulation by developing new methods to utilize the abundant data from readily accessible Internet of Things (IoT) devices. Additionally, the research group investigates the synergies between Artificial Intelligence and Simulation to enhance both fields.

The application areas focus on cyber-physical systems, including smart factories and energy systems, with the aim of improving various performance metrics such as energy efficiency, production, and reliability. Our research contributes to optimizing the use of these systems and harnessing the benefits of IoT technology.

We take pride in being a research group that is at the forefront of this field and are always open to opportunities to collaborate with other researchers and interested parties. If you have any further questions or are interested in collaborating, please do not hesitate to contact us.


Keywords: Modeling and Simulation • Data-driven Simulation • Data Analytics • Digital Twins • Energy Efficiency • Reliability Modeling and Analysis


Active Projects


Publications

You can find the publications of our team at here.


Open Positions
Student Assistant (HiWi) Student Research Assistant (f/m/d) for Statistical and Machine Learning on Raod Traffic Noise
Student Assistants(HiWi) Student Assistants (HiWi)(f/m/d) in the Research Group Systems, Data, Simulation & Energy (SYDSEN)
Open Ph.D. and PostDoc positions Open PhD and PostDoc positions at SYDSEN


News
… weitere Ergebnisse
21. Februar 2024: 2024 SYDSEN Retreat - Bad Herrenalb
25. Januar 2024: The third consortium of the ONE4ALL Project
12. Januar 2024: Welcome Dr. Min-Bin Lin to SYDSEN!
3. November 2023: The second participation of SYDSEN in the EPICUR Programme between SDU and KIT
4. September 2023: Welcome Michelle Jungmann to SYDSEN!


Media & Press
  • [09. March 2024] Prof. Sanja Lazarova-Molnar quoted on Deutschlandfunk on the topic "Hype-Schaden: Der große Boom der KI lässt Projekte schnell scheitern".


Courses & Seminars

We offer the following courses and seminars:


Open Thesis Topics


We are open for inquiries for supervision of Master and Bachelor projects. In particular, we would supervise thesis in the following broad topics:

  • Modeling and Simulation: This topic involves developing mathematical models and creating computer simulations to represent real-world phenomena or systems. A thesis in this area could focus on the development of novel modeling techniques, simulation algorithms, or the application of modeling and simulation to solve specific problems in fields like engineering, economics, or healthcare.
  • Data-Driven Simulation: With the abundance of data available today, data-driven simulation focuses on utilizing data to improve the accuracy and realism of simulations. A thesis in this area may explore techniques for data integration, analysis, and validation to enhance simulation models, as well as investigating ways to leverage machine learning or statistical methods to optimize simulations based on real-world data.
  • Digital Twins: Digital twins are virtual replicas of physical systems, enabling real-time monitoring, analysis, and prediction. A thesis in this area could involve creating digital twin models, developing methods to synchronize digital twins with their physical counterparts, or exploring applications of digital twins in industries such as manufacturing, healthcare, or urban planning.
  • Process Mining: Process mining involves analyzing event logs to discover, monitor, and improve processes within organizations. A thesis in this area may focus on developing process mining algorithms, techniques for process discovery or conformance checking, or applying process mining to specific domains such as supply chain management or healthcare.
  • Simulation and Modeling for Energy Efficiency: This topic centers on using simulation and modeling techniques to optimize energy consumption, identify energy-efficient solutions, and evaluate the impact of different energy-related strategies. A thesis in this area could involve developing simulation models for energy systems, investigating energy management algorithms, or evaluating the effectiveness of energy-efficient technologies or policies.
  • Reliability Modeling and Analysis: Reliability modeling and analysis involve assessing the performance and dependability of systems to ensure smooth operations and minimize failures. A thesis in this area may focus on reliability modeling techniques, fault diagnosis methods, or reliability-based optimization approaches, with applications in fields such as manufacturing, energy systems, or critical infrastructures.

We are also interested in supervising theses that align with our research interests and involve collaborations with companies. Please contact us for more information and to discuss potential thesis opportunities.


Persons



Visiting Students

SYDSEN welcomes visiting students from all over and seeks international partnerships.

We have hosted the following students: