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Harshita Sharma

Senior Researcher • Machine Learning • Artificial Intelligence • Biomedical Imaging • Computer Vision • Multimodal Data • Engineering

Microsoft

Biography

Dr. Harshita Sharma is a Senior ML Researcher in the Biomedical Imaging team at Microsoft. She explores machine learning solutions for improving patient outcomes and clinical workflows. Harshita’s research interests include machine learning, AI, large multimodal models, image analysis, computer vision, biomedical imaging, and multimodal clinical data analysis for healthcare.

Until June 2021, Harshita worked as a PostDoc in the Department of Engineering Science at the University of Oxford, and was a member of the Biomedical Image Analysis (BioMedIA) group, advised by Prof. Alison Noble. She worked in the interdisciplinary ERC Project PULSE (Perception Ultrasound by Learning Sonographic Experience) with the aim to develop multi-modal analysis methods to model sonographic experience and make obstetric ultrasound imaging easier for non-specialists.

In 2017, Harshita obtained her Ph.D. (Dr.-Ing.) in Computer Vision from Technische Universität Berlin advised by Prof. Olaf Hellwich, after being awarded a full-time DAAD Ph.D. Scholarship (2013-17). She was a member of the Computer Vision and Remote Sensing group (CVRS) at TU Berlin. She collaborated with Charité University Hospital, VMScope GmbH Berlin, and University Hospital Schleswig-Holstein. She analysed histopathological whole slide images of gastric carcinoma to develop methods in computational pathology for automatic cancer grade classification, necrosis detection and cell nuclei classification.

In 2012-13, Harshita was a lecturer in electronics and communication engineering at the Jaypee Institute of Information Technology. In 2011-12, she was fortunate to be an exchange research scholar at Technical University Berlin under the DAAD-IIT Master Sandwich Programme, where she explored histopathological breast cancer biopsies for content-based image retrieval and collaborated in the Virtual Specimen Scout project of Charité University Hospital Berlin, TU Berlin, VMscope GmbH Berlin and NEXUS AG Villingen-Schwenningen. In 2012, Harshita obtained her Masters degree (M.Tech.) in electrical engineering from the Indian Institute of Technology Roorkee, and in 2010, and Bachelors degree (B.Tech.) in electronics and communication engineering from the Indira Gandhi Delhi Technical University of Women.

Interests

  • Machine Learning and AI
  • Biomedical Imaging
  • Computer Vision
  • Large Multimodal Models
  • Image Analysis
  • Signal Processing

Education

  • Ph.D.(Dr.-Ing.) in Computer Vision, 2017

    Technische Universität Berlin

  • M.Tech. in Instrumentation and Signal Processing, 2012

    Indian Institute of Technology Roorkee

  • B.Tech. in Electronics and Communication Engineering, 2010

    Indira Gandhi Delhi Technical University for Women

Publications

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Nur Yildirim, Hannah Richardson, Maria Teodora Wetscherek, Junaid Bajwa, Joseph Jacob, Mark Ames Pinnock, Stephen Harris, Daniel Coelho De Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme (2024). Multimodal healthcare AI: identifying and designing clinically relevant vision-language applications for radiology. Proceedings of the CHI Conference on Human Factors in Computing Systems.

DOI Arxiv BibTeX

Kenza Bouzid*, Harshita Sharma*, Sarah Killcoyne, Daniel C Castro, Anton Schwaighofer, Max Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O’Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle (2024). Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology. (KB and HS contributed equally.)Nature Communications.

DOI Nature MedArxiv BibTeX

Fernando Pérez-García*, Harshita Sharma*, Sam Bond-Taylor*, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel C Castro, Anton Schwaighofer, Matthew P Lungren, Maria Wetscherek, Noel Codella, Stephanie L Hyland, Javier Alvarez-Valle, Ozan Oktay (2024). RAD-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision.

arXiv BibTeX

Fernando Pérez-García, Sam Bond-Taylor, Pedro P Sanchez, Boris van Breugel, Daniel C Castro, Harshita Sharma, Valentina Salvatelli, Maria TA Wetscherek, Hannah Richardson, Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse (2023). RadEdit: stress-testing biomedical vision models via diffusion image editing.

arXiv BibTeX

Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya V Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle (2023). Exploring the Boundaries of GPT-4 in Radiology. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing.

DOI arXiv BibTeX

Shruthi Bannur, Stephanie Hyland, Qianchu Liu, Fernando Perez-Garcia, Maximilian Ilse, Daniel C Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Wetscherek, Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay (2023). Learning to exploit temporal structure for biomedical vision-language processing. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

DOI BibTeX

Shruthi Bannur, Stephanie Hyland, Qianchu Liu, Fernando Pérez-García, Max Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anton Schwaighofer, Maria Teodora Wetscherek, Hannah Richardson, Tristan Naumann, Javier Alvarez Valle, Ozan Oktay (2023). MS-CXR-T: Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing. PhysioNet.

DOI BibTeX

Robail Yasrab, Zeyu Fu, He Zhao, Lok Hin Lee, Harshita Sharma, Lior Drukker, Aris T Papageorgiou, J. Alison Noble (2022). A Machine Learning Method for Automated Description and Workflow Analysis of First Trimester Ultrasound Scans. IEEE Transactions on Medical Imaging.

DOI IEEE BibTeX

Mohammad Alsharid, Yifan Cai, Harshita Sharma, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble (2022). Gaze-assisted automatic captioning of fetal ultrasound videos using three-way multi-modal deep neural networks. Medical Image Analysis.

DOI Elsevier BibTeX

Mohammad Alsharid, Harshita Sharma, Lior Drukker, Aris T. Papageorgiou, J. Alison Noble (2022). Weakly Supervised Captioning of Ultrasound Images. Annual Conference on Medical Image Understanding and Analysis (MIUA) 2022.

DOI Springer BibTeX

Mohammad Alsharid, Lior Drukker, Harshita Sharma, J. Alison Noble, Aris T. Papageorghiou (2022). A picture is worth 1000 words: textual analysis of routine 20‐week scan. Ultrasound in Obstetrics & Gynecology.

DOI Wiley BibTeX

Lior Drukker*, Harshita Sharma*, J. N. Karim, Richard Droste, J. Alison Noble, Aris T. Papageorghiou (2022). Clinical workflow of sonographers performing fetal anomaly ultrasound scans: deep learning-based analysis. (LD and HS contributed equally.)Ultrasound in Obstetrics & Gynecology.

DOI Wiley BibTeX

Clare Teng, Harshita Sharma, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble (2022). Visualising Spatio-Temporal Gaze Characteristics for Exploratory Data Analysis in Clinical Fetal Ultrasound Scans. Symposium on Eye Tracking Research and Applications (ETRA) 2022.

DOI ACM BibTeX

Clare Teng, Harshita Sharma, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble (2021). Towards Scale and Position Invariant Task Classification Using Normalised Visual Scanpaths in Clinical Fetal Ultrasound. International Workshop on Advances in Simplifying Medical Ultrasound - ASMUS 2021, Medical Image Computing and Computer Assisted Intervention – MICCAI 2021.

DOI Springer BibTeX

Arijit Patra, Yifan Cai, Pierre Chatelain, Harshita Sharma, Lior Drukker, Aris T Papageorghiou, J Alison Noble (2021). Multimodal Continual Learning with Sonographer Eye-Tracking in Fetal Ultrasound. International Workshop on Advances in Simplifying Medical Ultrasound - ASMUS 2021, Medical Image Computing and Computer Assisted Intervention – MICCAI 2021.

DOI Springer BibTeX

Lior Drukker*, Harshita Sharma*, Richard Droste, Pierre Chatelain, J. Alison Noble, Aris T. Papageorghiou (2021). Transforming obstetric ultrasound into data science using eye tracking, voice recording, transducer motion and ultrasound video. (LD and HS contributed equally.)Scientific Reports (Nature).

DOI Springer BibTeX

Harshita Sharma, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble (2021). Machine Learning-based Analysis of Operator Pupillary Response to Assess Cognitive Workload in Clinical Ultrasound Imaging. Computers in Biology and Medicine.

DOI Elsevier BibTeX

Harshita Sharma, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble (2021). Multi-Modal Learning from Video, Eye Tracking, and Pupillometry for Operator Skill Characterization in Clinical Fetal Ultrasound. IEEE 18th International Symposium on Biomedical Imaging (ISBI) 2021.

DOI IEEE BibTeX

Mohammad Alsharid*, Rasheed El-Bouri*, Harshita Sharma, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble (2021). A Course-Focused Dual Curriculum For Image Captioning. (MA and RE contributed equally). IEEE 18th International Symposium on Biomedical Imaging (ISBI) 2021.

DOI IEEE BibTeX

Harshita Sharma, Lior Drukker, Pierre Chatelain, Richard Droste, Aris T. Papageorghiou, J. Alison Noble (2021). Knowledge Representation and Learning of Operator Clinical Workflow from Full-length Routine Fetal Ultrasound Scan Videos. Medical Image Analysis (Elsevier).

DOI Elsevier BibTeX

Harshita Sharma, Lior Drukker, Richard Droste, Pierre Chatelain, Aris T. Papageorghiou, J. Alison Noble (2020). OC10.02: Task‐evoked pupillary response as an index of cognitive workload of sonologists undertaking fetal ultrasound. Ultrasound Obstet Gynecol, 56: 28-28.

DOI Wiley BibTeX

Lior Drukker*, Harshita Sharma*, Richard Droste, J. Alison Noble, Aris T. Papageorghiou (2020). OC10.11: The data science of obstetric ultrasound: automatic analysis of full‐length anomaly scans using machine learning algorithms. (LD and HS contributed equally.) Ultrasound Obstet Gynecol, 56: 31-31.

DOI Wiley BibTeX

Mohammad Alsharid*, Rasheed El-Bouri*, Harshita Sharma, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble (2020). A Curriculum Learning Based Approach to Captioning Ultrasound Images. (MA and RE contributed equally.) Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis. ASMUS 2020, PIPPI 2020. Workshop at the Medical Image Computing and Computer Assisted Intervention (MICCAI 2020). Best Presentation Award.

DOI Springer BibTeX

Yipei Wang, Richard Droste, Jianbo Jiao, Harshita Sharma, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble (2020). Differentiating Operator Skill During Routine Fetal Ultrasound Scanning Using Probe Motion Tracking. Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis. ASMUS 2020, PIPPI 2020. Workshop at the Medical Image Computing and Computer Assisted Intervention (MICCAI 2020).

DOI Springer BibTeX

Yifan Cai, Richard Droste, Harshita Sharma, Pierre Chatelain, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble (2020). Spatio-Temporal Visual Attention Modelling of Standard Biometry Plane-Finding Navigation. Medical Image Analysis (Elsevier).

DOI Elsevier BibTeX

Richard Droste, Pierre Chatelain, Lior Drukker, Harshita Sharma, Aris T. Papageorghiou, J. Alison Noble (2020). Discovering Salient Anatomical Landmarks by Predicting Human Gaze. 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), Iowa City, IA, USA, 2020, pp. 1711-1714. Best Paper Awards Runner Up.

PDF DOI arXiv ORA IEEE BibTeX

Pierre Chatelain, Harshita Sharma, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble (2020). Evaluation of Gaze Tracking Calibration for Longitudinal Biomedical Imaging Studies. IEEE Transactions on Cybernetics.

DOI ORA IEEE BibTeX

Harshita Sharma, Richard Droste, Pierre Chatelain, Lior Drukker, Aris T. Papageorghiou, J.Alison Noble (2019). Spatio-Temporal Partitioning And Description Of Full-Length Routine Fetal Anomaly Ultrasound Scans. IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

DOI ORA IEEE BibTeX

Mohammad Alsharid, Harshita Sharma, Lior Drukker, Pierre Chatelain, Aris T. Papageorghiou, J. Alison Noble (2019). Captioning Ultrasound Images Automatically. Medical Image Computing and Computer Assisted Intervention – MICCAI 2019.

DOI ORA Springer BibTeX

Richard Droste, Yifan Cai, Harshita Sharma, Pierre Chatelain, Aris T. Papageorghiou, J. Alison Noble (2019). Towards Capturing Sonographic Experience: Cognition-Inspired Ultrasound Video Saliency Prediction. Medical Image Understanding and Analysis (MIUA 2019). Best Paper Award.

PDF DOI ORA Springer BibTex

Richard Droste, Yifan Cai, Harshita Sharma, Pierre Chatelain, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble (2019). Ultrasound Image Representation Learning by Modeling Sonographer Visual Attention. In Information Processing in Medical Imaging (IPMI 2019).

PDF DOI arXiv ORA Springer BibTeX

Lior Drukker, Richard Droste, Pierre Chatelain, Harshita Sharma, Yifan Cai, Jaan Toots, Mohammad Alsharid, Aris T. Papageorghiou, J. Alison Noble (2019). Monitoring Sonographer Performance: The Perception Ultrasound by Learning Sonographer Experience (PULSE) study. In: Special Issue: Official Proceedings of the 2019 AIUM Convention, Journal of Ultrasound in Medicine, 38, S1–S214, 2019.

DOI Wiley

Arijit Patra*, Yifan Cai*, Pierre Chatelain, Harshita Sharma, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble (2019). Efficient Ultrasound Image Analysis Models with Sonographer Gaze Assisted Distillation. (AP and YC contributed equally.)Medical Image Computing and Computer Assisted Intervention – MICCAI 2019.

DOI Springer BibTeX

Yifan Cai, Harshita Sharma, Pierre Chatelain, J. Alison Noble (2018). Multi-task SonoEyeNet: Detection of Fetal Standardized Planes Assisted by Generated Sonographer Attention Maps. Medical Image Computing and Computer Assisted Intervention – MICCAI 2018.

DOI ORA Springer BibTeX

Yifan Cai, Harshita Sharma, Pierre Chatelain, J. Alison Noble (2018). SonoEyeNet: Standardized fetal ultrasound plane detection informed by eye tracking. 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

DOI ORA IEEE BibTeX

Harshita Sharma, Norman Zerbe, Iris Klempert, Olaf Hellwich, Peter Hufnagl (2017). Deep convolutional neural networks for automatic classification of gastric carcinoma using whole slide images in digital histopathology. Computerized Medical Imaging and Graphics (Elsevier CMIG).

PDF DOI BibTeX

Harshita Sharma, Norman Zerbe, Christine Böger, Stephan Wienert, Olaf Hellwich, Peter Hufnagl (2017). A Comparative Study of Cell Nuclei Attributed Relational Graphs for Knowledge Description and Categorization in Histopathological Gastric Cancer Whole Slide Images. IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) 2017.

PDF DOI IEEE BibTeX

Harshita Sharma (2017). Medical image analysis of gastric cancer in digital histopathology: methods, applications and challenges. PhD Thesis.

PDF DOI BibTeX

Harshita Sharma, Norman Zerbe, Daniel Heim, Stephan Wienert, Sebastian Lohmann, Olaf Hellwich, Peter Hufnagl (2016). Cell nuclei attributed relational graphs for efficient representation and classification of gastric cancer in digital histopathology. SPIE Medical Imaging 2016. Best Student Paper Award Finalist and Best Poster Award.

DOI Link BibTeX

Harshita Sharma, Norman Zerbe, Iris Klempert, Olaf Hellwich, Peter Hufnagl (2016). Deep Convolutional Neural Networks for Histological Image Analysis in Gastric Carcinoma Whole Slide Images. Diagnostic Pathology, ECDP Conference Proceedings 2016.

Link DOI BibTeX

Harshita Sharma, Norman Zerbe, Iris Klempert, Sebastian Lohmann, Bjorn Lindequist, Olaf Hellwich, Peter Hufnagl (2015). Appearance-based necrosis detection using textural features and SVM with discriminative thresholding in histopathological whole slide images. IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE) 2015.

DOI IEEE BibTeX

Harshita Sharma, Norman Zerbe, Sebastian Lohmann, Klaus Kayser, Olaf Hellwich, Peter Hufnagl (2015). A review of graph-based methods for image analysis in digital histopathology. Diagnostic Pathology.

DOI Link BibTeX

Harshita Sharma, Norman Zerbe, Daniel Heim, Stephan Wienert, Hans-Michael Behrens, Olaf Hellwich, Peter Hufnagl (2015). A Multi-resolution Approach for Combining Visual Information using Nuclei Segmentation and Classification in Histopathological Images. Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP) 2015.

PDF DOI Link BibTeX

Harshita Sharma, Norman Zerbe, Daniel Heim, Stephan Wienert, Hans-Michael Behrens, Olaf Hellwich, Peter Hufnagl (2014). Histopathological Image Analysis for Determining Tissue Composition in Gastric Cancer. Digital Pathology Congress 2014.

PDF

Harshita Sharma, Alexander Alekseychuk, Peter Leskovsky, Olaf Hellwich, RS Anand, Norman Zerbe, Peter Hufnagl (2012). Determining similarity in histological images using graph-theoretic description and matching methods for content-based image retrieval in medical diagnostics. Diagnostic Pathology.

DOI Link BibTeX

Akash Tayal, Harshita Sharma, Twinkle Bansal (2010). A Novel Technique Combining Euclidian Distance Measure and DHMM For Automatic Speaker Recognition. IEEE INDIACom 2010.

PDF BibTeX

Akash Tayal, Harshita Sharma, Twinkle Bansal (2010). A Content-Based Medical Image Mining System for Knowledge Discovery in Medical Images. National Conference on Information Management in Knowledge Economy 2010.

Akash Tayal, Harshita Sharma, Twinkle Bansal (2010). Enhancement of Medical Images Using a Novel Frobenius Norm Filtering Method. The 4th International Conference on Computer Applications in Electrical Engineering Recent Advances (CERA 2009).

Research Experience

 
 
 
 
 

Senior Researcher

Microsoft

Apr 2022 – Present Cambridge, United Kingdom
  • Exploring machine learning and image analysis solutions aimed to improve patient outcomes and transform clinical workflows in healthcare.
 
 
 
 
 

Researcher

Microsoft

Aug 2021 – Mar 2022 Cambridge, United Kingdom
  • Explored machine learning and image analysis solutions aimed to improve patient outcomes and transform clinical workflows in healthcare.
 
 
 
 
 

Visiting Researcher

University of Oxford

Aug 2021 – Dec 2021 Oxford, United Kingdom
 
 
 
 
 

Postdoctoral Researcher

University of Oxford

May 2017 – Jun 2021 Oxford, United Kingdom
  • Analyzed multimodal big data consisting of videos, images, and sensory data to develop novel methods for medical ultrasound.
  • Performed independent research and collaborations with project team members, including Nuffield Department of Women’s & Reproductive Health at the John Radcliffe Hospital.
 
 
 
 
 

PhD Research Scholar

TU Berlin (DAAD Full-Time Scholarship)

Oct 2013 – May 2017 Berlin, Germany
  • Ph.D. thesis was titled Medical Image Analysis of Gastric Cancer in Digital Histopathology: Methods, Applications and Challenges.
  • The research was performed between TU Berlin, Charité University Hospital Berlin and UKSH Kiel.
 
 
 
 
 

DAAD-IIT Masters Exchange Scholar

TU Berlin (DAAD-IIT MSP Scholarship)

Sep 2011 – May 2012 Berlin, Germany
  • Master’s thesis was titled Determining Similarity in Histological Images using Graph-Theoretic Description and Matching Methods for Content-Based Image Retrieval in Medical Diagnostics.
  • Was a part of the collaborative research project Virtual Specimen Scout of Charité University Hospital Berlin, TU Berlin, VMscope GmbH Berlin and NEXUS AG Villingen-Schwenningen.
 
 
 
 
 

Research Trainee

Defence Research and Development Organisation

Jul 2009 – Jun 2009 Delhi, India
  • Secured Grade-A (Excellent) at DRDO.
  • Signal processing research on the project called VANI: Automatic Speaker Recognition System.

Teaching Experience

 
 
 
 
 

Teaching Assistant in Engineering Science

University of Oxford

Oct 2018 – Sep 2020 Oxford, United Kingdom
  • Received SEDA PDF Supporting Learning Award, a portable accredited qualification in Higher Education teaching. The award is aligned to the UK Professional Standards Framework (UKPSF) for Teaching and Supporting Learning in Higher Education, at Descriptor 1.
  • Lead Tutor with tutorials and exam setting in B-13 paper Circuits and Communications.
  • Lecture and lab demonstration in coursework module Biomedical Engineering: Introduction to Biomedical Image Analysis.
  • Lectures and practical in Advanced Image Analysis module at the DTC-ONBI Programme.
  • Tutorials and independent studies on Mathematical Modelling for Teach First Futures Easter School and Headstart Programme.
 
 
 
 
 

Lecturer

Jaypee Institute of Information Technology

Jul 2012 – Apr 2013 Noida, India
  • Course Coordinator-Lectures, Tutorials and Exam Paper-Setting: Electrical Machines and Instruments
  • Lab Instructor: Electrical Machines and Instruments
  • Course Instructor-Lectures and Tutorials: Basic Electronic Devices and Circuits
  • Lab Instructor: Basic Electronic Devices and Circuits
  • Project Supervisor: Undergraduate 3rd year and 4th year projects

Service and Administration

Journal Reviewer

IEEE TPAMI, IEEE TMI - Distinguished Reviewer Bronze, NPJ Oncology, Nature Communications, PLOS ONE, IEEE JBHI, IEEE RA-L, IEEE Access, CMIG (Elsevier), AIIM (Elsevier), CPMB (Elsevier), IJCARS (Springer), PeerJ, Ultrasonic Imaging, Journal of Pathology, MDPI J Imaging, MDPI Applied Science, Biomedical Optics Express, Heliyon, International Journal of Imaging Systems and Technology (IMA)-Editorial Board Member, Oxford Initiatives.

Conference Reviewer

ISBI 2024, ISBI 2023, MICCAI 2022 (Networking Session Panelist), ISBI 2022, MICCAI-ASMUS 2021 (Programme Committee Member), MIUA 2021 (Session Chair), MICCAI 2021, ETRA 2021, IPMI 2021, IEEE ISBI 2021, ECDP 2021 (Scientific Committee Member and Moderator), MICCAI-ASMUS 2020, MICCAI 2020, MIUA 2020, MIDL 2020, ISBI 2020, MICCAI 2019, MIDL 2019, IEEE ISBI 2019, IEEE ISBI 2018, BioRob 2018, IEEE BIBE 2017 (Programme Committee Member).

Memberships

Associate Alumni at the University of Oxford, Future Medicine AI Editorial Board Member, UKRI ECR Forum, International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), ACM, ESDIP Scientific Committee Member, TU Berlin-Alumni Network (International Contact- GB) and Manager of the LinkedIn TU Berlin Alumni Club UK, MedIAN-Medical Image Analysis Network, Lindau Alumni Network, Heidelberg Laureate Forum - Alumni Network, DAAD Alumni Network, Durtti-The Artificial Intelligence Group, Cancer Epigenetics Society, Science Advisory Board

Accomplish­ments

SEDA PDF Supporting Learning Award

University of Oxford Sep 2019
A portable accredited qualification in Higher Education teaching in the UK. The award is aligned to the UK Professional Standards Framework (UKPSF) for Teaching and Supporting Learning in Higher Education, at Descriptor 1.

Selection and Grant to participate in 68th Lindau Nobel Laureate Meeting in Lindau, Germany

Council for the Lindau Nobel Laureate Meetings/Foundation Lindau Nobel Laureate Meetings Jun 2018
Only 600 most qualified young scientists can be given the opportunity to enrich and share the unique atmosphere of the LNLMs. Selected as one of 15 Mars Fellows under the Mars Fellows Programme.

Best Poster Award Cum Laude (Digital Pathology)

SPIE society for optics and photonics Mar 2016
Awarded at SPIE Medical Imaging, San Diego, California, USA (2016).

Robert F. Wagner All-Conference Best Student Paper Award Conference Finalist

SPIE society for optics and photonics Mar 2016
In recognition of the professional excellence of scientific paper at SPIE Medical Imaging, San Diego, California, USA (2016).

Selection and Grant to participate in 3rd Heidelberg Laureate Forum (HLF) in Heidelberg, Germany

Heidelberg Laureate Forum Foundation Aug 2015
Only 200 most qualified young researchers are granted the opportunity to experience unique atmosphere of HLF.

DAAD PhD Scholarship

DAAD: German Academic Exchange Service Jun 2013 – Mar 2017
Full-time scholarship for Ph.D. research in Computer Vision at TU Berlin.

Late Smt. Uma Goyal Memorial Cash Prize Award for highest CGPA in M.Tech.

IIT Roorkee Oct 2012
1st Position in the Department of Electrical Engineering at IIT Roorkee.

DAAD-IIT Master Sandwich Scholarship

DAAD: German Academic Exchange Service Sep 2011 – May 2012
M.Tech. research and dissertation in Computer Vision at TU Berlin.

M.Tech Scholarship (PG Scholarship)

Ministry of Human Resource Development (MHRD), Government of India Jul 2010 – Jun 2012
Secured after qualifying Graduate Aptitude Test in Engineering (GATE) with 98.82 Percentile.

Selection in ISRO Recruitment for Engineer-Scientist

Indian Space Research Organization (ISRO) Jul 2010
Merit Rank 27 in All-India ISRO Recruitment for Engineer-Scientist.

Grade-A Excellent in research training project

Defense Research and Development Organization (DRDO) Jul 2009
Research project on speaker recognition.

Cash Prize Awards for being the topper on the basis of Cumulative Performance Index

Guru Gobind Singh Indraprastha University Jul 2008 – Jun 2010
Topper (overall 1st Position) at IGIT, GGSIPU Delhi.

Gold Medal

Delhi Public School, Vasant Kunj Apr 1999 – Mar 2005
Excellence in Academics for seven successive years.

Rashtriya Kavita Award-National poetry writing competition

Balkan-ji-Bari International Mar 1998
3rd position in national poetry writing competition.

News and Events

  • December 2023 Harshita presented an invited talk at the AI Trailblazers’ Seminar at the University of Bern.

  • May 2023 | Harshita wrote an article in the Future Medicine AI Hub. Read full article here. Social media posts: LinkedIn, Twitter.

  • October 2022 | Harshita was an industry panelist at the networking session at MICCAI 2022.

  • July 2022 | Harshita attended the Medical Image Understanding and Analysis (MIUA) 2022 conference held at Cambridge, United Kingdom.

  • March 2022 | Harshita was invited for a Pathbreakers interview at The Interview Portal. Read full interview here.

  • July 2021 | Harshita attended and chaired a session at the Medical Image Understanding and Analysis (MIUA) 2021 conference.

  • April 2021 | Harshita gave an invited talk “Artificial Intelligence in Medical Imaging - Methods, Applications, and Challenges” at Microsoft Research India.

  • April 2021 | Harshita presented her research paper “Multi-modal Learning from Video, Eye Tracking, and Pupillometry for Operator Skill Characterization in Clinical Fetal Ultrasound” as oral presentation at IEEE ISBI 2021.

  • October 2020 | Harshita presented a hot abstract in ultrasound imaging “Task‐evoked pupillary response as an index of cognitive workload of sonologists undertaking fetal ultrasound”, and equally contributed to the abstract “The data science of obstetric ultrasound: automatic analysis of full‐length anomaly scans using machine learning algorithms” at the ISUOG Virtual World Congress 2020.

  • October 2020 | A co-authored paper from the PULSE project “A Curriculum Learning Based Approach to Captioning Ultrasound Images” is the Best Presentation Winner at Advances in Simplifying Medical UltraSound-ASMUS 2020 Workshop at MICCAI 2020.

  • April 2020 | A co-authored paper from the PULSE project “Discovering Salient Anatomical Landmarks by Predicting Human Gaze” has won the 2nd runner up for Best Paper Award at ISBI 2020. News items can be found here and here.

  • July 2019 | A co-authored paper from the PULSE project “Towards Capturing Sonographic Experience: Cognition-Inspired Ultrasound Video Saliency Prediction” has won the Best Paper Award at MIUA 2019.

  • April 2019 | Harshita presented her Postdoctoral research paper “Spatio-temporal partitioning and description of full-length routine fetal anomaly ultrasound scans” as an oral presentation in IEEE ISBI 2019 at Venice, Italy.

  • March 2018 | Harshita presented her research at the Oxbridge Women in Computer Science Conference 2018 at Cambridge, UK.

  • July 2018 | Harshita’s PhD research on gastric cancer was mentioned in the blog article Tackling the Silent Crisis in Cancer Care and at Lindau Alumni Network.

  • June 2018 | Harshita participated in the 68th Lindau Nobel Laureate Meeting 2018 as a Mars Fellow at Lindau, Germany. She has shared her experience here!

  • April 2018 | Harshita featured in the Women in Research Blog by Lindau Nobel Laureate Meeting. Can also be viewed here.

  • May 2018 | Hashita has a feature in the TU Berlin Newsletter TU Intern!

  • April 2018 | Harshita attended the TU Berlin Alumni Workshop in Berlin, Germany! Watch the glimpses of her TU Berlin Alumni Memories on Youtube here, here and here!

  • March 2018 | Harshita’s interview (invited feature) by Durtti.com-The Artificial Intelligence Group: Research Scientist Dr. Harshita Sharma Talks To Durtti About The Future Of Biomedical Imaging.

  • April 2017 | Harshita defended her PhD thesis at TU Berlin and received the Dr.-Ing. degree 😄.

  • March 2017 | Harshita gave an invited talk Medical Image Analysis using Modern Description and Learning Techniques at NIEC, Delhi.

  • October 2016 | Harshita presented her PhD research at the workshop Computational Life Sciences @ Bayer in Berlin, Germany.

  • May 2016 | Harshita’s deep learning in digital pathology talk at ECDP 2016 in Berlin was mentioned in the MicroDimensions Blog Article.

  • March 2016 | Harshita received student paper and poster awards at the SPIE Medical Imaging Symposium 2016 in San Diego, United States. Find out more here!

  • January 2016 | Harshita’s PhD research is featured in the Computer Vision & Remote Sensing Group Activities of the TU Berlin.

  • August 2015 | Harshita presented her PhD research and participated in the 3rd Heidelberg Laureate Forum at Heidelberg, Germany!

  • June 2014 | Harshita gave an invited talk Histopathogical Image Analysis for Content-Based Image Retrieval and Classification at the DAAD WISE scholarship holders’ meeting at the Frei Universität in Berlin, Germany.

Contact

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