جامعة الملك عبدالعزيز

KING ABDULAZIZ UNIVERSITY

Turki Talal Salem Turki


  
 

Turki Talal Salem Turki
 Assistant Professor
Department of  Computer Sciences
Faculty of Computing and Information Technology
King Abdulaziz University
Phone: 6400000 Ext. 67528
Email: tturki@kau.edu.sa

 
   
  
 

Profile:

*******News*******


- I am co-organizing with Dr. Jason T. L. Wang and Dr. Zhi Wei the special session (Machine Learning for Complex Data Mining Applications) at IEEE ICMLA 2018: http://www.icmla-conference.org/icmla18/index.php. I highly recommend to submit your work (by selecting the track “Special Session on Machine Learning for Complex Data Mining Applications”) and attend the conference.

- I am teaching next Semester CS 681 Selected Topics: Machine Learning and Data Mining.

- I am co-organizing with Dr. Jie Zhang the special session (Emerging Machine Learning Methods and Applications for Smart Systems: http://icnsc2018.autom.hk/EMLMASS.html) at IEEE ICNSC 2018. I highly recommend to submit your work at https://easychair.org/conferences/?conf=icnsc2018(deadline: Nov. 15, 2017) and attend the conference.

Journal Editorial Board:

-Computers in Biology and Medicine (https://www.journals.elsevier.com/computers-in-biology-and-medicine/editorial-board). Impact Factor: 2.115
-Sustainable Computing: Informatics and Systems (https://www.journals.elsevier.com/sustainable-computing/editorial-board). Impact Factor: 1.196

Program Committee:

- The 11th Mexican Conference on Pattern Recognition (MCPR 2019) (http://www.mcpr18.com.mx/scicomitee.html).
- ICDIS 2019 (the 2nd International Conference on Data Intelligence and Security) (https://www.icdis.org/program-committee). Full Paper Submission (Phase 1): November 15, 2018
- PACBB'19 (PC member of the 13th International Conference on Practical Applications of Computational Biology & Bioinformatics). (https://www.pacbb.net/organization/program-committee). Main Track - Paper submission deadline: 4th February, 2019
- 15th International Conference on Machine Learning and Data Mining (MLDM 2019) (http://www.mldm.de/call_for_papers.php). Paper Submission Deadline: January 15, 2019
- The 23rd Iberoamerican Congress on Pattern Recognition (CIARP 2018)(https://atvs.ii.uam.es/ciarp2018/committee.html).
- The 5th International Conference on Information Management and Big Data (SIMBig 2018) (https://simbig.org/SIMBig2018/en/prgcomitte.html).
- The Third Workshop on MIning DAta for financial applicationS (MIDAS), co-located with ECML-PKDD 2018 (https://sites.google.com/a/imtlucca.it/networks---imt-unit-for-the-study-of-networks/conferences/midas2018).
-19th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2018) (http://aida.ii.uam.es/ideal2018/#!/main).
- The 14th International Conference on Artificial Intelligence Applications and Innovations (AIAI 2018) (http://easyconferences.eu/aiai2018/pcomm.html).
- PACBB'18 (PC member of the 12th International Conference on Practical Applications of Computational Biology & Bioinformatics).
- International Symposium on Big Data Management and Analytics (BIDMA 2018) (https://bidma.cpsc.ucalgary.ca/2018/index.php). Paper Submission at https://easychair.org/conferences/?conf=bidma2018.
- The 16th Australasian Data Mining Conference (AusDM 2018) (http://ausdm18.ausdm.org/program-committee/).
- The First International Workshop on Big Data Analysis for Smart Energy (BigData4SmartEnergy 2018) (http://sigai.or.kr/workshop/bigcomp/2018/big-data-for-smart-energy/). 
- The 10th Mexican Conference on Pattern Recognition (MCPR 2018) (http://ccc.inaoep.mx/~mcpr2018/com.html).
- The 10th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2018) (PC member of DSCI 2018: Special Session on Data Science and Computational Intelligence).
- The Fifth International Conference on Mining Intelligence and Knowledge Exploration (MIKE 2017)(http://www.mike.org.in/2017/#l-start).

Journal Reviewer:

-Computers in Biology and Medicine (Elsevier).
-Scientific Reports (Nature).
-PLOS ONE (PLOS).
-Tumor Biology (SAGE).
-Journal of Bioinformatics and Computational Biology (Imperial College Press).
-Applied Soft Computing (Elsevier).
-Informatics in Medicine Unlocked (Elsevier).

Conference Reviewer:

- MLDM 2018 (The 14th International Conference on Machine Learning and Data Mining).

Session Chair:

-Special session for Biomedical Systems at the 2016 Annual IEEE Systems Conference (SysCon 2016).

Publications:

  • Turki Turki and Y-h. Taguchi, "Machine Learning Algorithms for Predicting Drugs-Tissues Relationships," Accepted at Expert Systems with Applications, 2019. Impact Factor: 3.768.
  • Turki Turki and Jason T. L. Wang, "Clinical intelligence: New machine learning techniques for predicting clinical drug response," Computers in Biology and Medicine, 2019. Impact Factor: 2.115.
  • Haodi Jiang, Turki Turki and Jason T. L. Wang, "DLGraph: Malware Detection Using Deep Learning and Graph Embedding," Accepted at the 17th ICMLA, 2018.
  • Turki Turki and Zhi Wei, "Boosting Support Vector Machines for Cancer Discrimination Tasks," Accepted at Computers in Biology and Medicine, 2018. Impact Factor: 2.115.
  • Z. Hu, T. Turki, N. Phan and J. T. L. Wang, "A 3D Atrous Convolutional Long Short-Term Memory Network for Background Subtraction," in IEEE Access, 2018. Impact Factor: 3.557.
  • Liulin Yang, Yun Li, Turki Turki, Huizi Tan, Zhi Wei and Xiao Chang, "Weighted Gene Co-Expression Network Analysis Reveals Dysregulation of Mitochondrial Oxidative Phosphorylation in Eating Disorders," Genes, 2018. Impact Factor: 3.191.
  • Haodi Jiang, Turki Turki, Sen Zhang and Jason T. L. Wang, "Reverse Engineering Gene Regulatory Networks Using Graph Mining," Accepted at the 14th International Conference on Machine Learning and Data Mining (MLDM 2018), July 13 - 18, 2018, New York, USA.
  • Turki Turki, Zhi Wei, Jason T. L. Wang, "A Transfer Learning Approach via Procrustes Analysis and Mean Shift for Cancer Drug Sensitivity Prediction," Accepted at the Journal of Bioinformatics and Computational Biology (JBCB). Impact Factor: 0.800.
  • Turki Turki, "An Empirical Study of Machine Learning Algorithms for Cancer Identification," Accepted at the 15th IEEE International Conference on Networking, Sensing and Control (ICNSC 2018), Zhuhai, China, March 27-29, 2018.
  • Haodi Jiang, Turki Turki, and Jason T. L. Wang, ”Reverse Engineering Regulatory Networks in Cells Using a Dynamic Bayesian Network and Mutual Information Scoring Function,” Accepted at the 16th IEEE International Conference on Machine Learning and Applications, Cancun, Mexico, December 18-21, 2017.
  • Turki Turki, Zhi Wei, and Jason T. L. Wang, "A Transfer Learning Approach via Procrustes Analysis and Mean Shift for Cancer Drug Sensitivity Prediction," Accepted at the 28th International Conference on Genome Informatics Workshop (GIW) / BIOINFO 2017, Seoul, Korea, Oct 31-Nov 3, 2017.
  • Turki Turki, Zhi Wei, and Jason T. L. Wang, “Transfer Learning Approaches to Improve Drug Sensitivity Prediction in Multiple Myeloma Patients,” Accepted at IEEE Access. Impact Factor: 3.224
  • Turki Turki and Jason T. L. Wang, “Reverse Engineering Gene Regulatory Networks Using Sampling and Boosting Techniques,” Accepted at the 13th International Conference on Machine Learning and Data Mining, New York, NY, 2017.
  • Yasser Abduallah, Turki Turki, Kevin Byron, Zongxuan Du, Miguel Cervantes-Cervantes, and Jason T. L. Wang, “MapReduce Algorithms for Inferring Gene Regulatory Networks from Time-Series Microarray Data Using an Information-Theoretic Approach,” BioMed Research International, vol. 2017, Article ID 6261802, 8 pages, 2017. Impact Factor: 2.467
  • Turki Turki and Zhi Wei, “A Noise-Filtering Approach for Cancer Drug Sensitivity Prediction,” in the Proceedings of the Neural Information Processing Systems Workshop on Machine Learning for Health (NIPS ML4HC), Barcelona, Spain, 2016.
  • Turki Turki and Zhi Wei, “A Link Prediction Approach to Cancer Drug Sensitivity Prediction,” International Conference on Intelligent Biology and Medicine (ICIBM), Houston, Texas, USA, 2016. Accepted for inclusion as a special issue in BioMed Central (BMC) Systems Biology. Impact Factor: 2.303
  • Turki Turki, Jason T. L. Wang, and Ibrahim Rajikhan, “Inferring Gene Regulatory Networks by Combining Supervised and Unsupervised Methods,” in the Proceedings of the 15th International Conference on Machine Learning and Applications (ICMLA), Anaheim, California, 2016.
  • Turki Turki and Zhi Wei, “Learning Approaches to Improve Prediction of Drug Sensitivity in Breast Cancer Patients,” in the Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Orlando, FL, 2016.
  • Turki Turki and Jason T. L. Wang, “A Learning Framework to Improve Unsupervised Gene Network Inference,” in the Proceedings of the 12th International Conference on Machine Learning and Data Mining, New York, NY, pp. 28-42, 2016.
  • Turki Turki and Zhi Wei, “A Greedy-Based Oversampling Approach to Improve the Prediction of Mortality in MERS Patients,” in the Proceedings of the 10th Annual IEEE International Systems Conference, Orlando, FL, 2016.
  • Turki Turki and Jason T. L. Wang, "A New Approach to Link Prediction in Gene Regulatory Networks," in the Proceedings of the 16th International Conference on Intelligent Data Engineering and Automated Learning, Wroclaw, Poland, 2015.
  • Turki Turki and Zhi Wei, “IPRed: Instance Reduction Algorithm Based on the Percentile of the Partitions,” in the Proceedings of the 26th Modern AI and Cognitive Science Conference, Greensboro, NC, 2015.
  • Turki Turki and Usman Roshan, "MaxSSmap: A GPU program for divergent short read mapping to genomes with the maximum scoring subsequence," BioMed Central Genomics (BMC Genomics), 2014. Impact Factor: 3.729.
  • Turki Turki, Muhammad Amimul Ihsan, Nouf Turki, Jie Zhang, Usman Roshan and Zhi Wei, “Top-k Parametrized Boost,” in the Proceedings of the Second International Conference on Mining Intelligence and Knowledge Exploration, Cork, Ireland, 2014.
  • Turki and Usman Roshan, “Weighted Maximum Variance Dimensionality Reduction,” in the Proceedings of the 6th Mexican Conference on Pattern Recognition, Cancun, Mexico, 2014.

I'm looking for students with strong analytical and programming skills to work in the following areas:

1) Deep Learning for healthcare analytics.
2) Statistical Data Mining/Machine Learning methods for problems related to post-trancriptional regulation and other biological problems.

Please email me your CV if you are interested


 
   
  
 

Education:
  • 2008 : Bachelor degree from Computer Science, computing and Information tec, King AbdulAziz university, جده, المملكة العربية السعودية
  • 2012 : Master degree from Computer Science and Engineering, Computer Science and Engineering, NYU.POLY, New York, امــريــكـا
  • 2017 : Doctorate degree from Computer Science, Ying Wu College of Computing, New Jersey Institute of Technology, Newark, امــريــكـا

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    Research Interests:

    Algorithms; Machine Learning; Deep Learning; Data Science; Data Mining; Big Data Analytics; Sustainable Computing; Health Informatics; Bioinformatics; Computational Biology; Social Networks; Smart Cities, Smart Transportation; Real Estate; and Security.


     
       
      
     

    Teaching Interests:
    Software Development; Algorithms; Learning; Big Data Analytics; Bioinformatics; Health Informatics; and Social Networks.

     
       
      
     

    Courses:
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    CPIT 100 : Computer Skills
    CPCS 212 : Applied Math Lab
    CPCS 222 : Discrete Structure Lab
    CPCS 223 : Intro to Design and Analysis of Algorithms Lab
    CPCS 214 : Computer organization and architecture Lab (Summer 217)
    CPCS 202 : Programming I (Summer 2017)
    CPCS 202 : Programming I Lab (Summer 2017)
    CPCS 202 : Programming I (Fall 2018)
    CPCS 222 : Discrete Structures (Fall 2018)

     
       
      
     

    Contact Info:
    • Office Phone: 6400000 Ext. 67528
    • Email : tturki@kau.edu.sa
    • URL : http://tturki.kau.edu.sa