Assistant Professor

Dr Sudhakar Tummala

Department of Electronics and Communication Engineering

Interests

  1. Machine Learning & Deep Learning
  2. Medical Image Analysis
  3. Multimodal Big Data MRI

Education

2006

Acharya Nagarjuna University, Guntur
India
BTech

2008

IIT Madras, Chennai
India
MTech

2012

University of Copenhagen, Copenhagen
Denmark
PhD

Experience

  • 2021-Present – Assistant Professor – SRM University-AP, Andhra Pradesh
  • 2020-2021 – Associate Professor – VRSEC, Vijayawada
  • 2020-2020 – Researcher – University Medical Centre Göttingen, Göttingen, Germany
  • 2017-2020 – Assistant Professor – SRM University AP, Andhra Pradesh
  • 2014-2016 – Postdoctoral Researcher – UCLA, Los Angeles, USA
  • 2012-2013 – Postdoctoral Researcher – Western University, London, Ontario, Canada

Research Interest

  • Magnetic resonance imaging (MRI) based marker development for several neurological disease diagnosis and prognosis from Machine Learning and Deep Learning methods. Interpretability of deep learning models.
  • Multimodal big data MRI processing. Fully automatic quality control mechanisms in big data. Artificial MRI data synthesis using deep generative models.

Awards & Fellowships

  • 2008 – Shushrutha Award – IIT Madras, Chennai, India
  • 2007-2008 – DAAD Scholar – Karlsruhe Institute of Technology, Karlsruhe, Germany

Memberships

  • IEEE Senior Member
  • Member in IEEE Engineering in Medicine and Biology Society
  • Member in IEEE Computational Intelligence Society

Publications

JOURNAL PAPERS
  • Tummala, S.; Kim, J.; Kadry, S. BreaST-Net: Multi-Class Classification of Breast Cancer from Histopathological Images Using Ensemble of Swin Transformers. Mathematics 2022, 10, 4109. https://doi.org/10.3390/math10214109
PATENTS
  • Li S, Tummala S, Tay K, W Romano, Ho D, Osman S, Predictive Intervertebral Disc Degeneration Detection Engine. US 9526457 B2, 2016.
  • Thadikemalla VSG, Tummala S, “A System and A Method for Automated Quality Control of Affine Registrations in Big Data Brain MRI”. Indian Patent, 202241065452.
MEDIA HIGHLIGHTS
  • The paper on Blood-Brain-Barrier in Obstructive Sleep Apnea was published on UCLA media: http://newsroom.ucla.edu/releases/ucla-researchers-provide-first-evidence-of-how-obstructive-sleep-apnea-damages-the-brain, 2015.
PEER REVIEWED JOURNALS AND CONFERENCE PROCEEDINGS
  • Tummala S, Focke NK, Machine Learning Framework for Fully Automatic Quality Checking of Rigid and Affine Registrations in Big Data Brain MRI. IEEE International Symposium on Biomedical Imaging (ISBI), 2021.
  • Tummala S, Deep Learning Framework using Siamese Neural Network for Diagnosis of Autism from Brain Magnetic Resonance Imaging. 6th IEEE sponsored International Conference on Convergence in Technology (I2CT), 2021.
  • Tummala S, Brain Tissue Entropy Changes in Patients with Autism Spectrum Disorder. Lecture Notes on Computational Vision and Biomechanics, Springer Nature AG, vol. 31, 2019, 1-10.
  • Tummala S, Schiphof D, Byrjalsen I, Dam EB, Validation of Gender Differences in Knee Joint Congruity quantified from MRI: A Validation Study with Data from Center for Clinical and Basic Research and Osteoarthritis Initiative. Cartilage, 9(1), 2018, 38-45.(IF 3.9, issue cover page)
  • Tummala S, Roy B, Vig R, Park B, Kang DW,Woo MA, Harper RM, Kumar R, Non-Gaussian Diffusion Imaging Shows Brain Myelin and Axonal Changes in Obstructive Sleep Apnea.J of Computer Assisted Tomography, 41 (2), 2017, 181-189.(IF 1.3)
  • Tummala S, Roy B,Park B, Kang DW,Woo MA, Harper RM, Kumar R, Associations between Brain White Matter Integrity and Disease Severity in Obstructive Sleep Apnea.J of Neuroscience Research, 94(10), 2016, 915-923. (IF 4.1)
  • Tummala S, Palomares JA, Kang DW, Park B, Woo MA, Harper RM, Kumar R, Global and Regional Brain Non-Gaussian Diffusion changes in Obstructive Sleep Apnea. SLEEP, 39(1), 2016, 51-57. (IF 5.6)
  • Palomares JA#, Tummala S#, Wang DJJ, Park B, Woo MA, et. al., Water Exchange across the Blood-Brain Barrier in Obstructive Sleep Apnea: An MRI diffusion-weighted pseudo-continuous arterial spin labelling study. J of Neuroimaging, 26(6), 2015, 900-905. (# co-first authors, IF 2.1)
  • Max Law WK, Garvin G, Tummala S, Tay KY, Leung A, Li S, Gradient Competition Anisotropy for Centerline Extraction and Segmentation of Spinal Cords. Information Processing in Medical Imaging, 2013.
  • Tummala S, Nielsen M, Lillholm M, Christiansen C, Dam EB, Automatic Quantification of Tibio-Femoral Contact Area and Congruity. IEEE Trans. Med. Imag., 31(7), 2012, 1404-1412. (IF 7.8)
  • Tummala S, Nielsen M, Dam EB, Automatic Quantification of Congruity from knee MRI. MICCAI Computational Biomechanics for Medicine, 2011, Toronto, Canada.
  • Tummala S, Bay-Jensen AC, Karsdal MA, Dam EB, Diagnosis of Osteoarthritis by Cartilage Surface Smoothness Quantified Automatically from knee MRI. Cartilage, 2(1), 2011, 50-59. (IF 3.9)
  • Tummala S, Dam EB, Surface Smoothness: Cartilage Biomarkers for knee OA beyond the Radiologist. SPIE medical imaging 2010, 762323, San Diego, US

Contact Details

TOP