Welcome to my Personal Homepage!
Last updated: May 2021.
“Being busy does not always mean real work. The object of all work is production or accomplishment and to either of these ends, there must be forethought, system, planning, intelligence, and honest purpose, as well as perspiration. Seeming to do is not doing.”
Thomas A. Edison
Neda Tavakoli is a Ph.D. student in Computer Science at Georgia Institute of Technology, advised by Prof. Srinivas Aluru, an internationally well-known leader in the area of computational biology. Neda’s main research interests include algorithmic and parallel data sciences, computational biology, and high-performance computing. In her research in High Performance/Parallel computational biology, she is interested in addressing fundamental problems on how to efficiently analyze genomic sequences. Particularly, she is most passionate about working on approximate and scalable parallel string algorithms with particular emphasis on genomics applications.
Ph.D. in Computer Science, Georgia Institute of Technology, Atlanta, GA, USA
M.Sc in Machine Learning Computer Science, Georgia Institute of Technology, Atlanta, GA, USA
M.Sc in Computer Science, Texas Tech University, Lubbock, TX, USA
Approximate Sequence Matching Algorithms to Handle Bounded Number of Errors, International Workshop on String Algorithms in Bioinformatics( StringBio) Slide, Orlando, FL, USA, 2018.
C. Jain, N. Tavakoli, S. AluruA Variant Selection Framework for Genome Graphs, Accepted to appear in ISMB 2021.
L. F. Gutirrez, N. Tavakoli, S. S. Namini, A. S. Namin, Similarity Analysis of FederalReserve Statements The Great Recession vs. COVID-19, IEEE International Conference on Big Data (Big Data) 2020.
2020.V. Nair, M. Chatterjee, N. Tavakoli, A. S. Namin, C. Snoeyink, Optimizing CNN using fast Fourier Transformation for Object Recognition, 19th IEEE International Conference on Machine Learning and Applications (ICMLA) 2020.
N. Tavakoli, S. Siami‑Namini, M. Adl Khanghah, F. Mirza Soltani, A. Siami Namin, An autoencoder‑based deep learning approach for clustering time series data, Accepted to appear in Springer Nature (SN) Applied Science, 2020. (Link) (PDF)
N. Tavakoli, D. Dai, Y. Chen, A Software-Defined QoS Provisioning Framework for HPC Applications, Accepted to appear in International Journal of Grid and High Performance Computing, 2020. (PDF)
N. Tavakoli, Modeling Genome Data Using Bidirectional LSTM, IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC), Vol. 2, (pp. 183-188), 2019. (Paper)
S. S. Namini, N. Tavakoli, A. S. Namin, The Performance of LSTM and BiLSTM in Forecasting Time Series, The 2nd Workshop on Big Data Engineering and Analytics in Cyber-Physical Systems BigEACPS’19, 2019.
N. Tavakoli, D. Dai, Y. Chen, Client-side Straggler-Aware I/O Scheduler for Object-based Parallel File Systems, Parallel Computing, Elsevier (ParCo), 2019. (Paper)
S. S. Namini, N. Tavakoli, A. S. Namin, A Comparison of ARIMA and LSTM in Forecasting Time Series, International Conference on Machine Learning Application (ICMLA), Orlando, Florida, USA, December 2018. (Link)
S. Hooshmand, N. Tavakoli, P. Abedin, Sharma V. Thankachan, On Computing Average Common Substring Over Run Length Encoded Sequence, Fundamenta Informaticae, 163(3): 267-273 (2018). (Paper)
D. Dai, R. Ross, D. Khaldi, Y. Yan, D. Matthieu, N. Tavakoli, and Y. Chen, Exploiting Locality in Scientific Workflow System: A Cross-Layer Solution, SC Extended Abstract, CoRR abs/1805.06167 (2018). (Paper)
N. Tavakoli, D. Dai, J. Jenkins, P. Carns, R. Ross and Y. Chen, A Software-Defined Approach for QoS Control in High-Performance Computing Storage Systems, SC Extended Abstract CoRR abs/1805.06161 (2018). (Paper)
N. Tavakoli, D. Dai, Y. Chen, Log-Assisted Straggler-Aware I/O Scheduler for High-End Computing, ICPP-W 2016. (Paper)
N. Tavakoli, Networked Markov Chain Influence Model for Providing Cascade-Resilient Interdependent Network, CRA-W, San Francisco, CA, USA, April 2016. [Poster]
Automatic Detection of Threats and Opportunities Using Natural Language Processing, Akbar Siami Namin, Sima Siami-Namini, and Neda Tavakoli, U.S. Provisional Patent Application Serial No. 62/781,184. (Status: Filed 2018).
Honors and Awards
Travel grant for attending SC’19 as a Student Volunteer, Awarded by SC, Denver, Colorado, USA, November 2019.
Travel grant for attending SC’18 as a SCinet, Awarded by SC, Dallas, Texas, USA, November 2018.
Travel grant for attending StringBio’18 to preset research work, Awarded by NSF/UCF, Orlando, Florida, USA, October 2018.
Travel grant for attending MUG’18, Awarded by NSF/OSU, Columbus, Ohio, USA, August 2018.
Travel grant for attending SC’16 as a student volunteer, Awarded by SC, Salt Lake City, Utah, USA, November 2016.
Grant Proposal of $3,000 in the form of NCWIT (National Center for Women and IT) Student Fund gift. The proposal was developed and submitted by Neda Tavakoli, a graduate student in Computer Science and the president of the EWoCS (Extraordinary Woman of Computer Science) association. The gift is generously sponsored by Google Inc. to a new chapter on ACM-W at Texas Tech University, Fall 2016.
Google/VMware travel grant for attending FAST’16, Awarded by Google and VMware, Santa Clara, CA, USA, February 2016.
Admitted and awarded the travel scholarship to attend the CRA-W Graduate Cohort Workshop CRA-W in San Francisco, CA, USA, 2015.
Scholarship from the Dean of the Whitacre College of Engineering for the graduate program of Texas Tech University 2015-2017.
Attending and passing successfully ITA (International Teaching Assistant) Workshop, Texas Tech University, 2015.
Among the top 1% of students; Rank 227 for Iranian Nationwide Entrance Exam to university for undergraduate students among around 1,450,000 students, Tehran, Iran.
Admitted to attend NODET high school (National Organization for Development of Exceptional Talents–designated for top 5% of the entire high school students in the country), Tehran, Iran.
CSE6220: Introduction to High-Performance Computing, Graduate Teaching Assistant, Computer Science Department, Georgia Tech University, Spring 2019.
CS1411: Programming Principles I (Python programming ), Lab Instructor, Computer Science Department, Texas Tech University, Spring 2017.
CS1412: Programming Principles II (C programming ), Instructor, Computer Science Department, Texas Tech University, Fall 2015, Spring 2016.
CS5381: Analysis of Algorithms, Teaching Assistant, Computer Science Department, Texas Tech University, Fall 2016.
CS2413: Data Structure, Teaching Assistant, Computer Science Department, Texas Tech University, Fall 2016.
|School of Computer Science||Georgia Institute of Technology|