I am a Ph.D. candidate at Brown University, where I primarily work with Ritambhara Singh, Ph.D. and Sorin Istrail, Ph.D. My research is at the intersection of computer science, molecular biology, and statistics. My dissertation focuses on developing probabilistic and statistical algorithms for integrated analysis of single-cell multi-omics data, with an overall goal to understand gene expression regulation dynamics in health and disease. I am honored to be recognized as part of the Rising Stars in EECS 2022 cohort by The University of Texas at Austin.

Before joining Brown, I received my bachelor’s degree in bioengineering from Olin College of Engineering. There, I worked with Jean J. Huang, Ph.D. and John Geddes, Ph.D. on bioinformatic analyses and dynamical modeling of microbial communities under various perturbations. Later, I worked in the Quantitative Biology Lab, led by Gene-Wei Li, Ph.D. at the Massachusetts Institute of Technology (MIT), as a research support associate and lab manager, exploring gene regulatory network rewiring in bacteria. In the summers of 2020 and 2022, I interned with two Health Futures groups at Microsoft Research.

Apart from computational biology, I have had the opportunity to work on various projects that can be found here. Outside of research, I enjoy holding boardgame events with friends, swimming, bird feeding, volunteering with Ten Lives Cat Rescue, and pretending I can properly play the ukulele and violin. Feel free to e-mail me if you’d like to talk.

Research Interests

Methodology
Application areas
  • Representation learning
  • Optimal transport
  • Manifold learning
  • Bayesian statistics and inference
  • Variable selection
  • Causal inference
  • Machine learning & deep learning
  • Graph algorithms
  • Combinatorial optimization
  • Regulatory genomics
  • Functional genomics
  • Single-cell sequencing & imaging
  • Multi-omics
  • 3D genome
  • Precision medicine
  • Structural biology & proteomics

Education

2018 - 2023 (Expected) Ph.D. in Computer Science and Computational Biology (3.90/4.00)
Brown University (Providence, RI)
2018 - 2020 (Expected) M.Sc. in Computer Science (4.00/4.00)
Brown University (Providence, RI)
2013 - 2017 B.Sc. in Bioengineering (3.67/4.00)
Olin College of Engineering (Needham, MA)
2008 - 2013 TEVITOL High School with IB Diploma (Gebze, Turkey)

Professional Experience

June 2022 - Aug 2022 Microsoft Research, Research Intern (Redmond, WA)
June 2020 - Sep 2020 Microsoft Research, Research Intern: Genomics (Redmond, WA)
June 2017 - August 2018 Massachusetts Institute of Technology, Research Support Associate (Cambridge, MA)
Jan 2016 - Oct 2016 Design That Matters, Student Engineer (Salem, MA)
Jan 2015 - Dec 2015 Daktari Diagnostics, Student Engineer (Cambridge, MA)

Research Projects and Publications Google Scholar

2022

Unsupervised Integration of Single-Cell Multi-omics Datasets with Disproportionate Cell-Type Representation
P. Demetci, R. Santorella, B. Sandstede, R. Singh
Proceedings of the 26th Annual International Conference on Research in Computational Molecular Biology (RECOMB 2022)
Springer Nature Lecture Notes in Bioinformatics (2022) pp 3-19
[9] [abstract] [paper] [code]
Unbalanced CO-Optimal Transport
Q.H. Tran, H. Janati, N. Courty, R. Flamary, I. Redko P. Demetci R Singh
arXiv:2205.14923 (under review for NeurIPS 2022)
[8] [abstract] [paper] [code]

2021

SCOT: Single-cell multi-omics integration with optimal transport
P. Demetci*, R. Santorella*, B. Sandstede, W. Stafford Noble and Ritambhara Singh#
*Equal Contribution, #Corresponding Author
Journal of Computational Biology (in press)
[7] [abstract] [paper] [code] [tutorial]
Gromov-Wasserstein Optimal Transport to Align Single-Cell Multi-Omics Data
P. Demetci*, R. Santorella*, B. Sandstede, W. Stafford Noble and Ritambhara Singh#
*Equal Contribution, #Corresponding Author
International Conference on Research in Computational Molecular Biology (RECOMB) 2021
[6] [abstract] [paper] [code] [tutorial]
Multi-scale Inference of Genetic Trait Architecture using Biologically Annotated Neural Networks
P. Demetci,W. Cheng,Gregory Darnell, Xiang Zhou, Sohini Ramachandran, Lorin Crawford#
PLOS Genetics(in press)
[5] [abstract] [paper]

2020

Unsupervised Manifold Alignment for Single-Cell Multi-Omics Data
R. Singh#, P. Demetci, G. Bonora, V. Ramani, C. Lee, H. Fang, Z. Duan, X. Deng, J. Shendure, C. Disteche and W. Stafford Noble#
#Corresponding Authors
Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB 2020)
[4] [abstract] [paper] [code]
Combinatorial and statistical prediction of gene expression from haplotype sequence
B. Alpay*, P. Demetci* Sorin Istrail, and Derek Aguiar#
*Equal Contribution, #Corresponding Author
Bioinformatics (Oxford Press) vol.36, Supplement_1, p:i194-i202. 2020
Proceedings of the 27th International Conference on Intelligent Systems for Molecular Biology (ISMB 2020)
[3] [abstract] [paper] [code]

2019

Rapid accumulation of motility-activating mutations in resting liquid culture of Escherichia coli
D. Parker*, P.Demetci*, and G.W. Li#
*Equal Contribution, #Corresponding Author
Journal of Bacteriology, 2019
[2] [abstract] [paper]

2016

Internalization and externalization in the classroom: How do they emerge and why is it important?
P.Demetci, C. Nichols, Y. V. Zastavker, J. D. Stolk, A. Dillon, M. D. Gross.
IEEE, 2016
FIE Conference, 2016
[1] [abstract] [paper]

Awards

2022 Selected as part of the "Rising Stars in EECS" 2022 cohort (UT Austin)
2022 RECOMB Travel Fellowship
2020 ICML WCB Fellowship
2016 Meritorius Winner: 2016 MCM/ICM Interdisciplinary Contest in Mathematical Modeling
2015-2017 Olin Alumni Scholarship
2013-2017 Sunlin Chou International Scholarship (50% tuition)
2013-2017 Olin Merit Scholarship (50% tuition)
2013 Honorable Mention (Instrumentation): First Step to Nobel Prize in Physics

Invited Talks, and Conferences Presentations













2022 Stanford University (Invited Talk)
Biologically Annotated Neural Networks for Multi-scale Genomic Association Discovery
2022 RECOMB Proceedings (Oral Presentation)
Unsupervised integration of single-cell multi-omics datasets with disparities in cell-type representation
2021 NeurIPS Workshop on Optimal Transport in Machine Learning (Invited Keynote)
Enabling integrated analysis of single-cell multi-omics with optimal transport
2021 Machine Learning in Computational Biology (Oral Presentation)
Unsupervised integration of single-cell multi-omics datasets with disparities in cell-type representation
2021 RECOMB Proceedings (Oral Presentation)
Gromov-Wasserstein Optimal Transport to Align Single-Cell Multi-Omics Data
2020 ICML Workshop on Computational Biology (Poster & Spotlight Presentation) [Acceptance Rate: 21%]
Gromov-Wasserstein Optimal Transport to Align Single-Cell Multi-Omics Data
2020 Machine Learning in Computational Biology (MLCB) Conference (Oral Presentation) [Acceptance Rate: 15%]
Gromov-Wasserstein Optimal Transport to Align Single-Cell Multi-Omics Data
2020 ISMB Proceedings (Oral Presentation) [Acceptance Rate: 19%]
Combinatorial and statistical prediction of gene expression from haplotype sequence
2020 ISMB (Oral & Poster Presentation) [Acceptance Rate: 25%]
Gromov-Wasserstein Optimal Transport to Align Single-Cell Multi-Omics Data
2020 Brown Unconference on Computational Intelligence and Applications (Invited Talk)
Gromov-Wasserstein Optimal Transport to Align Single-Cell Multi-Omics Data
2019 CCV-Con (Invited Talk @ Brown University)
Biologically Annotated Neural Networks for Multi-scale Genomic Association Discovery
2016 FIE (Oral Presentation) [Acceptance Rate: 48%]
Internalization and externalization: How do they emerge and why is it important?
2016 NEMPET (Poster Presentation)
Bioinformatic Comparison of Phototrophic Communitiesthat Degrade Cellulose and Fix Nitrogen
P Demetci, M Sheets, A Knapp, Linda Amaral-Zettler, Jean Huang
2015 Closing the Gap (Oral Presentation)
Project EyeHelper: Assistive Navigation for Blind Shopping
P Demetci, A Johnnson, M Ruehle, P Ruvolo

Teaching Experience

Spring 2019 & 2021 Advanced Algorithms in Computational Biology and Medical Bioinformatics (CSCI 2820 @ Brown U.)
Teaching Assistant: wrote and graded assignments, held recitations and office hours, lectured a few times.
Fall 2016 Designing Better Drugs (SCI1240 @ Olin College)
Teaching and Laboratory Assistant: graded assignments, assisted students in the laboratory.

Professional Service and Community Memberships

2020 - Present Society for Industrial and Applied Mathematics (SIAM)
2019 - 2021 Brown University Computational Biology Ph.D. Program Admissions Committee
2018 - Present International Society for Computational Biology (ISCB)
2018 - Present Models, Inference, and Algorithms (MIA) at Broad Institute
2018 - Present Member @ Graduate Women in Science and Engineering @ Brown University

Skills

Programming Languages Python, R, MATLAB, Java, C++, SQL, noSQL
Frameworks NumPy, Pandas, SciPy, PyTorch, Pyro, TensorFlow, Tensorflow-Probability, HDF5, Bioconductor, Seurat
Systems Linux, OSX, High Performance Cluster Computing, slurm, Google Cloud Computing, Microsoft Azure
Bioinformatics Tools GATK, VCFtools, BCFtools, BEDtools, PLINK, Cromwell, Cytoscape, QIIME, VAMPS, JGI
Laboratory DNA & RNA Extraction, PCR & RT-qPCR, Electrophoresis & PAGE, Western blotting, Molecular transformation, Transfection, HPLC, Rheology, Scanning Electron Microscopy
Engineering & Teamwork User-oriented collaborative design, Rapid prototyping, Scrum
Natural Languages English (Proficient), Turkish (Native Language), French (A2-Level proficiency)

Last updated on 2021-07-24