Fardina Fathmiul Alam, PhD
Department of Computer Science
George Mason University
Fairfax, VA
HI I'M FARDINA FATHMIUL ALAM
I am joining the Department of Computer Science (CS), University of Maryland (UMD), College Park as a Teaching Faculty in Fall 2023.
Biography:
I have worked as a Graduate Research Assistant under the supervision of Dr. Amarda Shehu at the Volgenau School of Engineering, George Mason University (GMU), Fairfax, Virginia, USA. My research interests centered around the development and application of Deep Learning and Machine Learning in the domain of Structural Bioinformatics and Computational Biology; on the broad topic of "Representation Learning for Molecular Structure Data using potentials from Deep Learning and Machine Learning methods". My works are funded by an NSF FET Grant #1900061.
Research Interest: Computational Biology, Deep Learning, Machine Learning, NLP
View my full CV.
Degrees
Ph.D. in Computer Science (Spring 2023), George Mason University
MS in Computer Science (Fall 2018, Conferred: Spring 2022), George Mason University
BS in Computer Science and Engineering (2013), Military Institute of Science and Technology
Announcement
2023:
October 16: Serving as a Faculty Panelist for "Academic Jobs Workshop" organised by UMD CS department; Location IRB-4105 (CMNS), time: 1-3 pm.
June 06: Check out my interview for joining UMD. Thanks to CS UMD for their warm welcome and recognition.
May 05: I am thrilled to share that I will be receiving the "Outstanding Dissertation Award 2023" from the Department of CS, George Mason University, VA for my Ph.D. dissertation work on "Deep latent variable models for learning representations of protein tertiary structures". Time to celebrate!
April 29: I am excited to share that I am going to be the Program Co-Chair of the 16th Computational Structural Bioinformatics Workshop (CSBW 2023) at ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) 2023, Houston, TX. The accepted paper link can be found here.
April 28 ( Time: 10:50 am EST): I have completed my Ph.D. Public Defense successfully and became a Doctorate!
March 29 ( Time: 1:54 pm EST): I have passed my Ph.D. Pre-Defense successfully!
2022:
December 1: Excited to announce that my paper entitled "Data Size and Quality Matter: Generating Physically-realistic Distance Maps of Protein Tertiary Structures" published in Biomolecules MDPI (ISSN 2218-273X) ( IF: 6.064) Journal has been chosen as an Editor's 2022 Choice Article.
November 21: I received the IEEE BIBM/CSBW travel award to attend IEEE BIBM Conference Workshop 2022 in Las Vegas, USA.
August 1: My journal paper named "Data Size and Quality Matter: Generating Physically-realistic Distance Maps of Protein Tertiary Structures" has been selected and featured as "Title Story" of the Journal Biomolecules (ISSN 2218-273X) ( IF: 6.064) and is currently visible on their homepage.
January 14: My Advancement to Candidacy approved officially.
2021:
December 06 ( Eastern Time 4:00 pm): I have passed my Ph.D. Proposal successfully.
May 07 ( Eastern Time 2:51 pm): I have passed my Ph.D. Comprehensive Exam successfully.
2018:
August 24 ( Eastern Time 7:08 pm): I have passed all of my Ph.D. Qualifying Exams (attended Summer-2018) successfully.
Latest News & Talks
2023:
February 2: CS Talk at Yale on "Understanding K-Means Clustering Machine Learning"
2022:
December 6: Presented our paper named "Equivariant Encoding based GVAE (EqEn-GVAE) for Protein Tertiary Structure Generation" at IEEE BIBM -CSBW Workshop Conference 2022, Las Vegas, Nevada.
November 11: Our paper named "Equivariant Encoding based GVAE (EqEn-GVAE) for Protein Tertiary Structure Generation" has been accepted at IEEE Intl Conf on Bioinformatics and Biomedicine (BIBM) Workshops: Computational Structural Biology Workshop (CSBW), Las Vegas, Nevada.
June 23: My journal paper named "Data Size and Quality Matter: Generating Physically-realistic Distance Maps of Protein Tertiary Structures" has been accepted to publish in Biomolecules (ISSN 2218-273X) ( IF: 6.064)
2021:
December 11 ( Eastern Time 12:30 pm) : Presented my paper named "Generating Physically-Realistic Tertiary Protein Structures with Deep Latent Variable Models Learning Over Experimentally-available Structure" at IEEE International Conference on Bioinformatics and Biomedicine (BIBM) - CSBW Workshop.
November 09: My paper named "Generating Physically-Realistic Tertiary Protein Structures with Deep Latent Variable Models Learning Over Experimentally-available Structure" has been accepted in IEEE International Conference on Bioinformatics and Biomedicine (BIBM) - CSBW Workshop.
May 06: My paper named "Towards more equitable question answering systems: How much more data do you need?" has been accepted in the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) main conference. The paper has been supervised by Professor Antonios Anastasopoulos, NLP Lab, GMU. The pre-print is available at: https://arxiv.org/abs/2105.14115.
March 03: My paper named "Unsupervised multi-instance learning for protein structure determination" (Article No. 2140002) has been published in the Journal of Bioinformatics and Computational Biology (JBCB), Volume No. 19, Issue No. 01
2020:
November 15 ( Eastern Time 7:26 pm): My paper named "Variational Autoencoders for Protein Structure Prediction" is published and available now in ACM Digital Library. Feel free to explore. Link: https://dl.acm.org/doi/10.1145/3388440.3412471
September 22 ( Eastern Time 7:30 am): Presented my paper named "Variational Autoencoders for Protein Structure Prediction" at ACM BCB Virtual Conference 2020.
July 16: My paper named "Variational Autoencoders for Protein Structure Prediction" has been accepted as a Regular Paper at the 11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB) 2020.
March 23 - 25: The 12th International Conference on Bioinformatics and Computational Biology (BICOB), 2020 held in San Francisco, CA ( Virtual due to COVID-19). My paper named "From Unsupervised Multi-Instance Learning to Identification of Near-Native Protein Structures" has been accepted.
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