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Dr. Duygu Sarikaya

Dr. Duygu Sarikaya

  • Position: Assistant Prof in Computer Science
  • Areas of expertise: surgical vision and perception; computer assisted surgery; medical image computing; computer vision; generative learning; vision-language models, deep learning; machine learning
  • Email: D.Sarikaya@leeds.ac.uk
  • Location: 3.34 Sir William Henry Bragg Building
  • Website: Googlescholar

Profile

My research interests span defining the technologies of future, artificial intelligence powered, healthcare applications. More specifically, I work on surgical vision and perception and medical image computing.

I received my MS and PhD from Computer Science and Engineering, University at Buffalo, State University of New York. I am a Fulbright alumna.

Research Fellows:

  • Jiashu Liao, SpectraSpace, Attention Models for Molecular Spectroscopy and Digital Histopathology

Current Students:

  • Lucy Fothergill, 6 DoF Pose Estimation in Surgical Videos (supervising with Dominic Jones and Pietro Valdastri)
  • Yushi Guo, Surgical Video Understanding and Anticipation (supervising with Pietro Valdastri)
  • Nanzhu Chen, Representation Learning for Human Action Recognition (supervising with He Wang and Brandon Bennett)
  • George Baker, Medical Image Understanding through Vision-Language Models (supervising with Nishant Ravikumar, Marc De Kamps, and Kieran Zucker)
  • Jing Li, Medical Vision Language Models (supervising with Nishant Ravikumar)
  • Arpita Saggar, A Virtual Patient to Support Medical Training (supervising with David Hogg, Vania Dimitrova, and Jonathan Darling)
  • Dr. Xin Ci Wong, How much ‘Real Data’ do you need Really? (supervising with Nishant Ravikumar, Marc De Kamps, and Kieran Zucker)
  • Handan Zhang, Vision-Language Models, MS Student

* in order of supervision and starting date

MIRAI Research group

MIRAI Research group

Formerly I was:

  • I like kpop, indie, alternative, modern rock, postmodern art, science fiction, fiction (soul swap, time travel, time hopping, alternative timelines, after life, past lives, supernatural, reincarnation, fantastical, magic realism), cities, architecture ...
  • My current favorite artist is James Jean.
  • DC > Marvel

Responsibilities

  • Admissions Tutor

Research interests

News:

  • May 2025: Arpita has won People’s Choice Prize at UCL Computer Science London Hopper 2025 Research Spotlight with her project on AI-generated virtual patients to support medical training.
  • May 2025: Jiashu presented our work Spectraspace: Spectral–Spatial Attention Models for Molecular Spectroscopy and Digital Histopathology at CLIRPath-AI.
  • April 2025: Welcome to our new member, Jing Li, who will be working on Medical Vision Language models!
  • March 2025: AE-CAI | CARE | OR 2.0 Joint MICCAI Workshop is accepted. See you in Daejeon!
  • February 2025: Handan will be attending BCSWomen Lovelace Colloquium in April!
  • February 2025: George will be attending ELLIS Winter School on Foundation Models (FoMo) in March!
  • January 2025: Welcome to our Research Fellow Jiashu Liao, who will be working on SpectraSpace project!

  • November 2024: Congratulations to my MSc project advisee, Jing Li, for winning the MSc Prize in Computing, awarded to the student with the best overall performance across all MSc taught programs within the School of Computing!
  • October 2024: We are seeking PhD candidates to join an exciting project on Medical Vision-Language Models. This is a fully-funded offer open to all nationalities (App. due 31st of October): Medical Vision-Language Models | Project Opportunities | PhD | University of Leeds
  • October 2024: We are looking for a Research Fellow for our SpectraSpace project. Applications are open now (App. due 20th of October): https://jobs.leeds.ac.uk/Vacancy.aspx?ref=EPSCP1161
  • October 2024: We will present Tugberk’s work PlutoNet: An Efficient Polyp Segmentation Network with Modified Partial Decoder and Decoder Consistency Training at AECAI workshop, MICCAI.
  • September 2024: Umit Mert Caglar, PhD candidate from the Graduate School of Informatics, METU visited us as part of an Erasmus traineeship.
  • July 2024: Congratulations to my project advisee, Kieran Cunningham, who won the Individual Project Prize with his project titled “Using Deep Reinforcement Learning to Develop Game Playing Agents”!
  • July 2024: I delivered a lecture at the UCL Medical Image Computing Summer School (MedICSS) 2024.
  • March 2024: I will start my Aurora Women’s Leadership Development Programme.
  • March 2024: AE-CAI | CARE | OR 2.0 Joint MICCAI Workshop is accepted. See you in Morocco!
  • Feb 2023: SpectraSpace is awarded by the CLIRPath-AI Network funded by EPSRC.
  • Jan 2024: I delivered a talk at Robotics at Leeds Workshop.

I organized the First and Second International Workshops on Context-Aware Operating Theaters in conjunction with MICCAI, the second International Surgical Data Science Workshop in conjunction with CARS, MIcro-Surgical Anastomose Workflow Recognition on Training Sessions (MISAW) Challenge, part of the Endovis Grand Challenge in conjunction with MICCAI, Computer Vision and Augmented Reality in Surgery Workshop in conjunction with Hamlyn Symposium on Medical Robotics, and a series of the Joint AE-CAI, CARE and OR 2.0 Workshops in conjunction with MICCAI.

I am Vice President of University at Buffalo, State University of New York Turkey Network – Alumni. I served as a board member of Women in MICCAI, and formerly was a member of the Student Board and the Educational Initiative at MICCAI.

Public Datasets:

ATLAS Dione Dataset for Robot-Assisted Surgery Video Understanding
ATLAS Dione dataset provides video data (86 full subject study videos (~910 action clips)) of ten surgeons from Roswell Park Cancer Institute (RPCI) (Buffalo, NY) performing six different surgical tasks on the daVinci Surgical System® (dVSS) with annotations of robotic tools per frame (for a subset of 99 action clips), actions taking place and their timestamps. It also provides information on the surgeon expertise levels based on the Dreyfus model.

MISAW (MIcro-Surgical Anastomose Workflow recognition on training sessions)
The MISAW data set is composed of 27 sequences of micro-surgical anastomosis on artificial blood vessels performed by 3 surgeons and 3 engineering students. The dataset contained video, kinematic, and procedural descriptions synchronized at 30Hz. The procedural descriptions contained phases, steps, and activities performed by the participants.

I am a reviewer for Proceedings of IEEE, IEEE Transactions on Medical Imaging, Medical Image Analysis, ArtifiĀ€cial Intelligence in Medicine, The International Journal of Computer Assisted Radiology and Surgery, Computer Methods and Programs in Biomedicine, Computer Assisted Surgery, Medical Image Computing and Computer Assisted Interventions Conference (MICCAI), Computer Assisted Radiology and Surgery Conference (IJCARS), International Conference on Information Processing in Computer-Assisted Interventions (IPCAI).

Current Opportunities:

1. We are seeking PhD candidates with a strong interest in computer vision, machine learning, and deep learning to join an exciting project on Medical Vision-Language Models.

This is a fully-funded offer open to all nationalities. You will have a chance to become part of the MIRAI Research Group (Medical Imaging and GeneRative AI).
You can find more information about the project, the team, and how to apply here: Medical Vision-Language Models | Project Opportunities | PhD | University of Leeds

Application Deadline: Thursday, 31 October 2024
Start Date: Saturday, 1 February 2025

2. We are looking for a Research Fellow for our SpectraSpace project. Applications will be on an ongoing basis and are open now, fist round is due 20th of October!: https://jobs.leeds.ac.uk/Vacancy.aspx?ref=EPSCP1161

Potential projects I am advertising:

I am always looking for students with a good knowledge of fundamental topics in computer vision, machine learning and deep learning, along with strong coding skills. Experience with advanced deep learning topics such as generative learning, deep reinforcement learning will be preferred.

Qualifications

  • PhD in Computer Science and Engineering, University at Buffalo, State University of New York
  • MS in Computer Science and Engineering, University at Buffalo, State University of New York
  • BS in Computer Engineering, TOBB University of Economics and Technology

Professional memberships

  • AFHEA
  • MICCAI Society
  • IEEE
  • IEEE Robotics and Automation Society
  • Aurora (Advance HE)

Student education

Data Science (Fall 2024, Fall 2023), Intelligent Systems and Robotics (Spring 2024)

Past: Data Science, Deep Learning, Computer Vision, Image Processing, Machine Learning, Artificial Intelligence in Medicine, Expert Systems

Data Science Module 2023-2024 Cohort

Data Science Module 2023-2024 Cohort

Current postgraduate researchers

<h4>Postgraduate research opportunities</h4> <p>We welcome enquiries from motivated and qualified applicants from all around the world who are interested in PhD study. Our <a href="https://phd.leeds.ac.uk">research opportunities</a> allow you to search for projects and scholarships.</p>
Projects
    <li><a href="//phd.leeds.ac.uk/project/1858-effectively-using-hyperspectral-imaging-for-tissue-characterisation">Effectively Using Hyperspectral Imaging for Tissue Characterisation</a></li> <li><a href="//phd.leeds.ac.uk/project/1859-learning-to-automate-surgical-tasks-from-demonstration">Learning to Automate Surgical Tasks from Demonstration</a></li> <li><a href="//phd.leeds.ac.uk/project/1857-medical-vision-language-models-for-visual-question-answering">Medical Vision-Language Models for Visual Question Answering</a></li> <li><a href="//phd.leeds.ac.uk/project/1651-modelling-surgical-motion-and-activities">Modelling Surgical Motion and Activities</a></li>