Arka N. Mallela, MD

  • PGY-4 Resident

Arka N. Mallela, MD, joined the University of Pittsburgh Department of Neurological Surgery residency program in July 2018 after graduating from the University of Pennsylvania School of Medicine, earning his MD and MS in translational research. He received his undergraduate degrees from the Vagelos Scholars Program at the University of Pennsylvania, completing a BA in biophysics, biochemistry, and philosophy and an MS in biological chemistry.

Dr. Mallela has a strong interest in the intersection of neurophysiology, neuroimaging, network theory and deep learning. He is currently interested in utilizing these tools to study a variety of neurological diseases, including fetal brain folding, epilepsy, and brain tumors. For his work, Dr. Mallela has received the 2017 American Brain Tumor Association Young Investigator Award. He was recently selected for the Burroughs Wellcome Foundation Physician Scientist Incubator Program at the University of Pittsburgh to further his research in these areas.

In his free time, Dr. Mallela enjoys hiking, movie making, and spending time with his family, wife, and friends.

Dr. Mallela’s publications can be reviewed through the National Library of Medicine’s publication database.

Specialized Areas of Interest

Epilepsy surgery; neuro-oncology; pediatric neurosurgery.

Professional Organization Membership

American Association of Neurological Surgeons
Association for Clinical and Translational Sciences
Congress of Neurological Surgeons

Education & Training

  • BS, Biophysics, Biochemistry, Philosophy, University of Pennsylvania, 2013
  • MS, Biological Chemistry, University of Pennsylvania, 2013
  • MS, Translational Research, University fo Pennsylvania, 2018
  • MD, University of Pennsylvania Perelman School of Medicine, 2018

Honors & Awards

  • Physician Scientist Incubator Program, Burroughs Wellcome Foundation, 2021
  • Walter L. Copeland Grant, Copeland Foundation, 2020
  • American Brain Tumor Association Young Investigator Award, 2017

Selected Publications

Mallela AN, Abdullah KG, Brandon C, Richardson AG, Lucas TH. Topical vancomycin reduces surgical-site infections after craniotomy: a prospective, controlled study. Neurosurgery [in press], 2017.

Weinstein J, Mallela AN, Chandler J, Kofke WA, Kumar M, Levine J, Sandsmark D, Balu R. Excellent neurologic recovery after prolonged coma in a cardiac arrest patient with multiple poor prognostic indicators. Resuscitation 113: e11, 2017.

Ramayya AG, Abdullah KG, Mallela AN, Thawani J, Petrov D, Pierce J, Baltuch GH. Thirty-day readmission rates following deep brain stimulation surgery. Neurosurgery 81(2):259-267, 2017.

Lou W, Peck KK, Petrovich-Brennan NM, Mallela A, Holodny AI. Left-Lateralization of Resting State Functional Connectivity Between the pre-SMA and Primary Language Areas. NeuroReport 28(10):545-550, 2017. 

Mallela AN, Peck KK, Petrovich-Brennan NM, Zhang Z, Lou W, Holodny AI. Altered resting state functional connectivity in the hand motor network of glioma patients. Brain Connectivity 6(8):587-595, 2017.

Research Activities

Networks and Mapping in Language and Epilepsy
Dr. Mallela is exploring the role of the supplementary motor area in language dysfunction and recovery through multimodal advanced neuroimaging, MEG, awake mapping during craniotomy, and stereo EEG.

Understanding Fetal Brain Folding
Dr. Mallela is investigating the fetal development of the insula and Sylvian fissure to propose a novel mechanism of insular formation and telencephalic folding through advanced fetal neuroimaging and data analysis.

Augmented and Virtual Reality in Neurosurgery
Dr. Mallela and Edward Andrews, MD, are developing intraoperative augmented reality solutions for cranial and spinal navigation, to integrate multiple monitoring modalities, and to streamline operative workflow.

Deep Learning in Clinical Neurosurgery
Dr. Mallela is interested in utilizing deep learning techniques to probe clinical datasets in epilepsy and neuro-oncology to develop predictive tools and to analyze intraoperative data and events.