Prof. Dr.-Ing. Christian Bergler

Deep Learning applied to a broad spectrum of  data- and domain-specific research fields, with focus on a wide portfolio of novel and distinct algorithmic deep learning concepts:

• Data:
  • Images
  • Acoustics
  • Machine & Sensor Signals
  • Text Data

• Domain:          
  • Computer Vision
  • Acoustic Sound Analysis
  • Machine Signal Processing
  • Natural Language Processing

• Deep Learning Concept:   
  • Transfer Learning
  • Contrastive Learning
  • Distillation Learning
  • Federated Learning
  • Supervised, Semi-Supervised & Unsupervised Learning
  • Self-Supervised Learning
  • Generative Learning
  • Single-/Zero-/Few-Shot Learning
  • Representation Learning
  • Multimodal Learning
  • Causal Deep Learning
  • Reinforcement Learning

Promotion with highest distinction(summa cum laude) in the field of Deep Learning at the Pattern Recognition Lab (PRL), Friedrich-Alexander-University Erlangen-Nürnberg (FAU) - Dissertation title: "Deep Learning Applied to Animal Linguistics" available here:

Dissertation Christian Bergler

The joint efforts of the entire project team to decode the language of the Orcas was also recorded and featured on German television (3Sat/TerraX). The documentation can be watched under the following link:

https://www.3sat.de/wissen/wissenschaftsdoku/die-sprache-der-wale-102.html

GitHub Repository:  https://github.com/ChristianBergler

• Deep Learning - Master Module - Study Program: Artificial Intelligence (MKI), Artificial Intelligence for Industrial Applications (MAI)

• Data Engineering & Analytics - Bachelor Module - Study Program: Artificial Intelligence (KI), Artificial Intelligence - International (IK)

• Advanced Machine Learning - Master Module - Study Program: Artificial Intelligence (MKI), Artificial Intelligence for Industrial Applications (MAI)

• Natural Language Processing - Master Module - Study Program: Artificial Intelligence (MKI)

• AI Conference - Master Module - Study Program: Artificial Intelligence for Industrial Applications (MAI)

• AI Project - Master Module - Study Program: Artificial Intelligence for Industrial Applications (MAI)

• Programming Starter - Bachelor Module - Study Program: Artificial Intelligence - International (IK)

• Machine Learning - Bachelor Module - Study Program: Artificial Intelligence - National/International (KI, IK)

Bachelor's/Master's Theses: As part of my field of research - Deep Learning- there exist several opportunities for Bachelor's and Master's theses, either addressing differennt personal scientific topics (internal theses), or research questions in collaboration with industrial partners (external theses) .

The different topics cover the entire signal portfolio including image, audio, machine, and text signals, together with a wide variety of distinct deep learning concepts. If you are interested in a Bachelor's/Master's thesis in the field of Deep Learning, please contact me either via E-Mail or come to my office in person (Digital Campus, Room 1.13).

• Master Thesis
  • Photo2Material - A Deep Learning Approach for Physically Based Material Synthesis, MP, Summer Semester 2024 (completed)
  • Silent Signatures: Acoustic Watermarking Using Deep Learning, MKI, Summer Semester, 2024 (completed)
  • Unsupervised Anomaly Detection in Multivariate Time Series Data Using Deep Learning, MKI, Summer Semester, 2024 (completed)
  • Comparative Analysis of Design Choices for Production-Ready Deep Learning-based RAG Systems, MKI, Winter Semester, 2024/2025 (running)
  • Investigations Into Anomaly Detection and Error Classification in Screwdriving Processes Based on Deep Learning, MKI, Winter Semester, 2024/2025 (running)
  • Evaluation of Self-Supervised Learning Methods for CAD Embedding Models, MKI, Winter Semester, 2024/2025 (running)
  • Evaluating Picture Description for Alzheimer’s Disease Patients Using LLMs, MKI, Winter Semester, 2024/2025 (running)

• Bachelor Thesis

• DFG Project (under review): "Deep Animal Insights and Understanding (DAIU)"
• StIL Lehrarchitektur (under review): "ALADIN: Adaptive LehrArchitektur, Datenbasiert INdividuell"
• OTH Best Project 2025 (granted): "Künstliche Intelligenz als Wegbereiter zur Entschlüsselung von Tierkommunikation: KI-Detektive der OTH-AW auf den Spuren von Dr. Dolittle!"
• VHB-Classic-Course (under review): "Fundamentals of Speech Processing"
• INTERREG (in progress): "HIST-AI-RY-Historische Entdeckungsreise durch Kloster Speinshart: Aufleben der Vergangenheit mittels KI-basierter multimodaler Rekonstruktion"

• Joint spin-off from OTH, together with the support of the official OTH-internal start-up team
• Focus on a broad portfolio of applications from the field of artificial intelligence to support the daily (operational) business across multiple industrial and service divisions
• Design and implementation of domain- and task-specific machine (deep) learning algorithms together with respect to a broad signal spectrum, including audio, image, text, and sensor signals

• Barnhill A., Noeth E., Maier A., Bergler C., ANIMAL-CLEAN – A Deep Denoising Toolkit for Animal-Independent Signal Enhancement, 25th Annual Conference of the International Speech Communication Association, INTERSPEECH 2024 (Kos Island, Greece, September 1st, 2024 - September 5th, 2024), Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2024, DOI: 10.21437/Interspeech.2024-1151

• Lopez-Santander D. A., Rios-Urrego C. D., Bergler C., Nöth E., Orozco-Arroyave J. R., Robust Classification of Parkinson’s Speech: an Approximation to a Scenario With Non-controlled Acoustic Conditions, 27th International Conference on Text, Speech, and Dialogue, TSD 2024 (Brno,Czech Republic, September 9th, 2024 - September 13, 2024), Text, Speech, and Dialogue, 27th International Conference, TSD 2024, Brno, Czech Republic, September 9-13, 2024, Proceedings 2024, DOI: 10.1007/978-3-031-70566-3

• Barnhill A., Towers J. R., Nöth E., Maier A., Bergler C., Utilizing Deep Incomplete Classifiers to Implement Semantic Clustering for Killer Whale Photo Identification Data, 27th International Conference on Pattern Recognition, ICPR 2024 (Kolkata, India, December 1st, 2024 - December 5th, 2024), Proceedings of the 27th International Conference on Pattern Recognition 2024, ICPR 2024

• Hauer C., Nöth E., Barnhill A., Maier A., Guthunz J., Hofer H., Cheng RX., Barth V., Bergler C., ORCA-SPY: Killer Whale Sound Source Simulation and Detection, Classification and Localization in PAMGuard Utilizing Integrated Deep Learning Based Segmentation, Scientific Reports 13 (2023), p. 1-17, ISSN: 2045-2322, 11106, DOI: 10.1038/s41598-023-38132-7

• Bayerl SP., Gerczuk M., Batliner A., Bergler C., Amiriparian S., Schuller B., Nöth E., Riedhammer K., Classification of stuttering – The ComParE challenge and beyond, Computer Speech and Language 81 (2023), Article No.: 101519, ISSN:  0885-2308, DOI: 10.1016/j.csl.2023.101519

• Coppock H., Akman A., Bergler C., Gerczuk M., Brown C., Chauhan J., Grammenos A., Hasthanasombat A., Spathis D., Xia T., Cicuta P., Han J., Amiriparian S., Baird A., Stappen L., Ottl S., Tzirakis P., Batliner A., Mascolo C., Schuller BW., A summary of the ComParE COVID-19 challenges, In: Frontiers in Digital Health 5 (2023), Article No.: 1058163, ISSN: 2673-253X, DOI: 10.3389/fdgth.2023.1058163

• Brinkløv SM., Macaulay J., Bergler C., Tougaard J., Beedholm K., Elmeros M., Madsen PT., Open-source workflow approaches to passive acoustic monitoring of bats, Methods in Ecology and Evolution (2023), ISSN: 2041-210X, DOI: 10.1111/2041-210X.14131

• Bergler C., Smeele SQ., Tyndel SA., Barnhill A., Ortiz ST., Kalan AK., Cheng RX., Brinkløv S., Osieka AN., Tougaard J., Jakobsen F., Wahlberg M., Nöth E., Maier A., Klump BC., ANIMAL‐SPOT enables animal‐independent signal detection and classification using deep learning, Scientific Reports 12 (2022), p. 1-16, ISSN: 2045-2322, 21966, DOI: 10.1038/s41598-022-26429-y

• Bergler C., Barnhill A., Perrin D., Schmitt M., Maier A., Nöth E., ORCA-WHISPER: An Automatic Killer Whale Sound Type Generation Toolkit Using Deep Learning, 23nd Annual Conference of the International Speech Communication Association, INTERSPEECH 2022 (Incheon, Korea, September 18, 2022 - September 22, 2022), Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2022, DOI: 10.21437/interspeech.2022-846

• Bergler C., Schmitt M., Maier A., Cheng RX., Barth V., Nöth E., ORCA-PARTY: An Automatic Killer Whale Sound Type Separation Toolkit Using Deep Learning, International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (Singapore, May 22, 2022 - May 27, 2022), ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2022, DOI: 10.1109/icassp43922.2022.9746623

• Bergler C., Gebhard A., Towers JR., Butyrev L., Sutton GJ., Shaw TJH., Maier A., Nöth E., FIN-PRINT a fully-automated multi-stage deep-learning-based framework for the individual recognition of killer whales, Scientific Reports 11 (2021), p. 1-16, ISSN: 2045-2322, DOI: 10.1038/s41598-021-02506-6

• Bergler C., Schmitt M., Maier A., Symonds H., Spong P., Ness S., Tzanetakis G., Nöth E., ORCA-SLANG: An Automatic Multi-Stage Semi-Supervised Deep Learning Framework for Large-Scale Killer Whale Call Type Identification, 22nd Annual Conference of the International Speech Communication Association, INTERSPEECH 2021 (Brno, Czechia, August 30, 2021 - September 3, 2021), Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2021, DOI: 10.21437/Interspeech.2021-616

• Marzahl C., Aubreville M., Bertram CA., Maier J., Bergler C., Kröger C., Voigt J., Breininger K., Klopfleisch R., Maier A., EXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control, Scientific Reports 11 (2021), Article No.: 4343, ISSN: 2045-2322, DOI: 10.1038/s41598-021-83827-4

• Jiang G., Biswas A., Bergler C., Maier A., InSE-NET: A Perceptually Coded Audio Quality Model based on CNN, 151st Audio Engineering Society (AES) Convention (Las Vegas, Nevada, USA, October 11, 2021 - October 13, 2021), Audio Engineering Society Convention 151 2021

• Schuller B., Batliner A., Bergler C., Mascolo C., Han J., Lefter I., Kaya H., Amiriparian S., Baird A., Stappen L., Ottl S., Gerczuk M., Tzirakis P., Brown C., Chauhan J., Grammenos A., Hasthanasombat A., Spathis D., Xia T., Cicuta P., Rothkrantz LJM., Zwerts JA., Treep J., Kaandorp C., The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates, 22nd Annual Conference of the International Speech Communication Association, INTERSPEECH 2021 (Brno, Czechia, August 30, 2021 - September 3, 2021), Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2021, DOI: 10.21437/Interspeech.2021-19

• Mohamed MM., Nessiem MA., Batliner A., Bergler C., Hantke S., Schmitt M., Baird A., Mallol-Ragolta A., Karas V., Amiriparian S., Schuller BW., Face mask recognition from audio: The MASC database and an overview on the mask challenge, Pattern Recognition 122 (2021), p. 108361, ISSN: 0031-3203, DOI: 10.1016/j.patcog.2021.108361

• Schuller BW., Batliner A., Amiriparian S., Bergler C., Gerczuk M., Holz N., Larrouy-Maestri P., Bayerl S., Riedhammer K., Mallol-Ragolta A., Pateraki M., Coppock H., Kiskin I., Sinka M., Roberts S., The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoes, 30th ACM International Conference on Multimedia (Lisbon, Portugal, October 10, 2022 - October 14, 2022), Proceedings of the 30th ACM International Conference on Multimedia 2022, DOI: 10.1145/3503161.3551591

• Bergler C., Schmitt M., Maier A., Smeele S., Barth V., Nöth E., ORCA-CLEAN: A Deep Denoising Toolkit for Killer Whale Communication, 21th Annual Conference of the International Speech Communication Association: Cognitive Intelligence for Speech Processing, INTERSPEECH 2020 (Shanghai, China, October 25, 2020 - October 29, 2020), Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2020, DOI: 10.21437/Interspeech.2020-1316

• Schuller B., Batliner A., Bergler C., Messner EM., Hamilton A., Amiriparian S., Baird A., Rizos G., Schmitt M., Stappen L., Baumeister H., MacIntyre AD., Hantke S.: The INTERSPEECH 2020 Computational Paralinguistics Challenge: Elderly Emotion, Breathing & Masks, 21th Annual Conference of the International Speech Communication Association: Cognitive Intelligence for Speech Processing, INTERSPEECH 2020 (Shanghai, China, October 25, 2020 - October 29, 2020), Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2020, DOI: 10.21437/Interspeech.2020-0032

• Bergler C., Schröter H., Cheng RX., Barth V., Weber M., Nöth E., Hofer H., Maier A., ORCA-SPOT: An Automatic Killer Whale Sound Detection Toolkit Using Deep Learning, Scientific Reports 9 (2019), p. 1-17, ISSN: 2045-2322,  DOI: 10.1038/s41598-019-47335-w

• Bergler C., Schmitt M., Cheng RX., Maier A., Barth V., Nöth E., Deep Learning for Orca Call Type Identification – A Fully Unsupervised Approach, 20th Annual Conference of the International Speech Communication Association: Crossroads of Speech and Language, INTERSPEECH 2019 (Graz, September 15, 2019 - September 19, 2019), Gernot Kubin, Thomas Hain, Bjorn Schuller, Dina El Zarka, Petra Hodl (ed.): Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2019, DOI: 10.21437/Interspeech.2019-1857

• Bergler C., Schmitt M., Cheng RX., Schröter H., Maier A., Barth V., Weber M., Nöth E., Deep Representation Learning for Orca Call Type Classification, 22nd International Conference on Text, Speech, and Dialogue, TSD 2019 (Ljubljana, September 11, 2019 - September 13, 2019), Kamil Ekštein (ed.): Text, Speech, and Dialogue, 22nd International Conference, TSD 2019, Ljubljana, Slovenia, September 11–13, 2019, Proceedings 2019, DOI: 10.1007/978-3-030-27947-9_23

• Schröter H., Nöth E., Maier A., Cheng R., Barth V., Bergler C., Segmentation, Classification, and Visualization of Orca Calls Using Deep Learning, International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (Brighton, May 12, 2019 - May 17, 2019), ICASSP - IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2019, DOI: 10.1109/ICASSP.2019.8683785

• Mustafa A., Biswas A., Bergler C., Schottenhamml J., Maier A., Analysis by adversarial synthesis - A novel approach for speech vocoding, 20th Annual Conference of the International Speech Communication Association: Crossroads of Speech and Language, INTERSPEECH 2019 (Graz, AUT, September 15, 2019 - September 19, 2019), In: Gernot Kubin, Thomas Hain, Bjorn Schuller, Dina El Zarka, Petra Hodl (ed.): Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2019, DOI: 10.21437/Interspeech.2019-1195

• Schuller B., Batliner A., Bergler C., Porkony FB., Krajewski J., Cychosz M., Vollmann R., Roelen SD., Schnieder S., Bergelson E., Cristia A., Seidl A., Warlaumont AS., Yankowitz L., Nöth E., Amiriparian S., Hantke S., Schmitt M., The INTERSPEECH 2019 Computational Paralinguistics Challenge: Styrian Dialects, Continuous Sleepiness, Baby Sounds & Orca Activity, 20th Annual Conference of the International Speech Communication Association: Crossroads of Speech and Language, INTERSPEECH 2019 (Graz, AUT, September 15, 2019 - September 19, 2019), Gernot Kubin, Thomas Hain, Bjorn Schuller, Dina El Zarka, Petra Hodl (ed.): Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2019, DOI: 10.21437/Interspeech.2019-1122