Dr. Subash Chandra Pakhrin
Dr. Subash Chandra Pakhrin
Assistant ProfessorComputer Science and Engineering TechnologyBiography
Dr. Pakhrin obtained his Ph.D. in Electrical Engineering and Computer Science (EECS) from Wichita State University, Wichita, Kansas, USA. During his Ph.D. journey, he had the privilege of working with esteemed professors, including Dr. Doina Caragea, Dr. Kiyoko Aoki-Kinoshita, Dr. Ajita Rattani, Dr. Rajiv Bagai, Dr. Moriah R. Beck, Dr. Kaushik Sinha, Dr. Terrance Figy, Dr. Dukka B. KC, Dr. Gergely V. Zaruba and Dr. Justin Mears.
Prior to this, he completed his master's degree in information and communication engineering from Tribhuvan University, Kathmandu, Nepal. Similar to his doctoral studies, he worked with Dr. Dibakar Raj Pant, Dr. Subarna Shakya, Dr. Shashidhar Ram Joshi and Dr. Surendra Shrestha. His outstanding academic performance led him to be recognized as the top student at the university in his field, earning him the prestigious Nepal Bidhya Bhusan "Kha" Gold Medal award.
His research interest lies in delving into biological datasets and seeking to derive valuable insights from them. His exploration involves a deep dive into proteins, aiming to comprehend crucial post-translational modification (PTM) mechanisms. He leverages cutting-edge protein language models (PLMs). He extracts representative features from those PLMs for subsequent PTM predictions with deep and machine learning algorithms. Presently, his focus is directed towards investigating structure-aware protein language models. Overall, he is open to exploring research in computer vision, machine learning, natural language processing, deep learning, and bioinformatics.
In addition to publishing research in esteemed journal articles, he actively participates as a peer reviewer for journals like Bioinformatics and Scientific Reports.
Degrees Earned
| University | Degree | Passed Year | Percentage/GPA |
|---|---|---|---|
| Wichita State University | Ph.D. in Electrical Engineering & Computer Science | 2022 | 4.0 |
| Tribhuvan University | M.S. in Information and Communication Engineering | 2017 | 92.47% |
| Purbanchal University | B.E. in Electronics & Communication | 2010 | 3.48 |
Courses Taught
Graduate MSAI:
- Natural Language Processing (CS 6310)
- Computer Vision & Applications (CS 6305)
Undergraduate:
- Natural Language Processing (CS 4317)
- Theory of Computations (CS 3306)
- Python Programming for Computer Science (CS 1411)
Experience Qualifications
Assistant Professor at University of Houston-Downtown, January 2023 – Present. Researching Post Translation Modification prediction in proteins using Machine and Deep Learning algorithms. As well as instructing subjects: Python programming for computer science, natural language processing, theory of computation, and computer vision and applications.
Graduate Research Assistant (Full Time) at Wichita State University (January 2020 – December 2022). Researching Protein Post Translation Modification prediction using Machine and Deep Learning Algorithms.
Lecturer at Himalayan White House International College, November 2010 – August 2012 Subject instructed: Artificial Intelligence, Signal Analysis, Microprocessor, Communication Systems, Electromagnetics and propagation, Control System, Instrumentation – II
Tenured Telecommunication Engineer at Nepal Telecom, August 2012 – Dec 2019 Work with NMS of MPLS-IP equipment
Lecturer at Institute of Engineering, Pulchowk Campus, November 2017 – April 2017 Subject Instructed: Microprocessor-Based Instrumentation
More Information
Research
- Bioinformatics
- Computer Vision
- Machine Learning
- Deep Learning
- Natural Language Processing
Training and conferences attended:
- Attended IP – CDMA BSC/BTS O&M Training, Huawei University, Shenzhen, China
- Attended JENESYS 2016 SAARC 1st Batch: Tokyo, and Nagasaki, Japan
- Attended IP/MPLS Transmission Equipment Training, Huawei University, Hangzhou, China
Extra Online Courses taken:
- Artificial Intelligence, Patrick H. Winston. MIT OPENCOURSEWARE
- CNN for Visual Recognition, Fei Fei Li, Stanford University
- Machine Learning, Andrew Ng, Stanford University
- Python Programming Tutorials, Bucky Roberts, Corey Schafer, Dr. Ana Bell
- Discrete Mathematics Structures, IIT Madras, Kamala Krithivasan
- Bioinformatics: Algorithms and Applications, IIT Madras, M. Michael Gromiha
- Applied Natural language Processing, IIT Madras, Ramaseshan Ramachandran
Areas of Expertise:
- Data Science, Artificial Intelligence, Natural Language Processing, Machine Learning, and Deep Learning, Image Analysis and Computer Vision
- Bioinformatics (Protein Structure Prediction, and Post Translation Modification Prediction)
- Python Programming, C++ programming, Discrete Structures, Data Structures, SQL
Publications:
Journals (First Author):
- Pakhrin, S.C.; Aoki-Kinoshita, K.F.; Caragea, D.; KC, D.B. DeepNGlyPred: A Deep Neural Network-Based Approach for Human N-Linked Glycosylation Site Prediction. Molecules 2021, 26, 7314. https://doi.org/10.3390/ molecules26237314 (Impact factor: 4.6)
- Pakhrin S.C. et al., LMPhosSite: A Deep Learning-Based Approach for General Protein Phosphorylation Site Prediction Using Embeddings from the Local Window Sequence and Pretrained Protein Language Model, Journal of Proteome Research 2023 22 (8), 2548-2557, DOI: 10.1021/acs.jproteome.2c00667 (Impact factor: 4.4)
- Subash C Pakhrin, Suresh Pokharel, Kiyoko F Aoki-Kinoshita, Moriah R Beck, Tarun K Dam, Doina Caragea, Dukka B KC, LMNglyPred: prediction of human N-linked glycosylation sites using embeddings from a pre-trained protein language model, Glycobiology, 2023, cwad033, https://doi.org/10.1093/glycob/cwad033 (Impact factor: 4.3)
- Pakhrin, S.C.; Shrestha, B.; Adhikari, B.; KC, D.B. Deep Learning-Based Advances in Protein Structure Prediction. Int. J. Mol. Sci. 2021, 22, 5553. https://doi.org/ 10.3390/ijms22115553 (Impact factor: 5.6)
Conference (First Author):
- S. C. Pakhrin and D. R. Pant, "Multi-Armed Bandit Learning Approach with Entropy Measures for Effective Heterogeneous Networks Handover Scheme," 2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), 2018, pp. 451-455, doi: 10.1109/ICACCCN.2018.8748593.
Book Chapter (First Author):
- S.C. Pakhrin, "Deep learning-based advances in protein post-translational modification site and protein cleavage prediction", https://link.springer.com/book/9781071623169
Journal Papers Submitted (First Author):
- SumoPred-PLM: human SUMOylation and SUMO2/3 sites Prediction using Pre-trained Protein Language Model, Submitted to NAR Genomics & Bioinformatics (First Major Revision) (Impact Factor 4.6)
- Pakhrin S.C. et al., Human O-linked Glycosylation Site Prediction Using Pretrained Protein Language Model, Submitted to Scientific Reports (On Peer Review) (Impact Factor: 4.6)
Ongoing Projects:
- Human emotion detection on largest available dataset using pretrained deep learning architecture.
- Ubiquitination PTM prediction using pretrained protein language model.
- Detecting deception in space using machine and deep learning.
Awards and Recognitions
- Nepal Vidhya Bhushan "Kha" Gold Medal, 8th September 2019
- Best Bachelor's in Engineering (BE) Student Award, 2008 AD
- Topper of the SLC examination from the Indigenous group in Sindhuli district, 2003 AD