MALEQ KHAN

Contact Information

Address: Department of Electrical Engineering and Computer Science
Texas A&M University-Kingsville
700 University Blvd., Kingsville, TX 78363
Phone: (361)593-3304
Email: first_name dot last_name at tamuk.edu
Home page: www.maleqkhan.net

Research Interest

Big data analytics
Graph analytics
High performance computing
Parallel and distributed algorithms
Randomized algorithms
Data mining

Education

• PhD in Computer Science
  Purdue University, West Lafayette, Indiana, USA
  Thesis: Distributed Approximation Algorithms for Minimum Spanning Trees and Other Related Problems with Applications to Wireless Ad Hoc Networks.
  
• MS in Computer Science
  North Dakota State University, Fargo, North Dakota, USA
  Thesis: Fast Distance Metric Based Data Mining Techniques Using P-trees
  
• BS in Computer Science and Engineering
  Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh
  Thesis: Performance Analysis of Multiprocessor Systems with Multilevel Cache

Awards

• Best Paper Award Runner-up at the 25th High Performance Computing Symposium (HPC), Virginia Beach, VA, USA, April, 2017.
• Best Paper Award Finalist at the International Conference for High Performance Computing, Networking, Storage and Analysis (SC16), Salt Lake City, Nov. 2016.
• Best Paper Award at the 20th International Symposium on Distributed Computing (DISC), Stockholm, Sweden, 2006. Here is a web story that appeared in the front page of Purdue Computer Science home page in Sep. 2006. Also mentioned in the ACM SIGACT News -- if you don't have access to the ACM DL, here is another copy.
• Bilsland Dissertation Fellowship, Purdue University, 2006-2007.

Professional Service

Program Co-Chair:

• Third Workshop on Mining Networks and Graphs (MNG 2016), in conjunction with SIAM International Conference on Data Mining (SDM 2016).
• Second Workshop on Mining Networks and Graphs (MNG 2015), in conjunction with SIAM International Conference on Data Mining (SDM 2015).
• Co-organized two workshops on a cyberinfrastructure for network science, called CINET, at two universities: Virginia Tech (in July 2015) and University at Albany - SUNY (in August 2015).

  Program Committee Member:

• 23rd International Conference on Computer and Information Technology (ICCIT 2020)
• International Conference on Cybersecurity in Emerging Digital Era (ICCEDE 2020)
• The ACM India Joint International Conference on Data Science & Management of Data (CoDS-COMAD), January 2020
• Sixth International Conference on Networking Systems and Security (NSysS), December 2019
• 22nd International Conference on Computer and Information Technology (ICCIT 2019)
• The ACM India Joint International Conference on Data Science & Management of Data (CoDS-COMAD), January 2019
• Fifth International Conference on Networking Systems and Security (NSysS), December 2018
• 21st International Conference on Computer and Information Technology (ICCIT 2018)
• The ACM India Joint International Conference on Data Science & Management of Data (CoDS-COMAD), January 2018
• Fourth International Workshop on High Performance Big Graph Data Management, Analysis, and Mining (BigGraph), December 2017, In conjunction with IEEE BigData 2017
• Fourth International Conference on Networking Systems and Security (NSysS), December 2017
• Fourth IKDD Conference on Data Science (CODS 2017)
• 20th International Conference on Computer and Information Technology (ICCIT 2017)
• Third International Conference on Networking Systems and Security (NSysS), January 2017
• International Conference on Distributed Computing and Networking (ICDCN 2016)
• IKDD Conference on Data Science (CODS 2016)
• 9th International Conference on Computer and Information Technology (ICCIT 2016)
• International Conference on Networking Systems and Security (NSysS 2016)
• SIAM Workshop on Network Science 2015
• SDM Workshop on Mining Networks and Graphs 2014
• The 7th International Conference on Wireless Algorithms, Systems, and Applications (WASA 2012)
• The 6th International Conference on Wireless Algorithms, Systems, and Applications (WASA 2011)
• IEEE 14th International Multitopic Conference (INMIC 2011)
• International Conference on Wireless Algorithms, Systems, and Applications (WASA 2010)
  

  Reviewer of Journals:

  I served as a reviewer for various leading journals in Computer Science including
• ACM/IEEE Transactions on Networking
• IEEE Transactions on Parallel and Distributed Systems
• ACM Transactions on Algorithms
• IEEE Transactions on Knowledge and Data Engineering
• IEEE Transactions on Mobile Computing
• SIAM Journal on Scientific Computing
• Journal of Discrete Algorithms
• Theory of Computing Systems
• Distributed Computing
• Theoretical Computer Science
• Journal of Parallel and Distributed Computing
• Information Processing Letters
• Ad Hoc Networks
• Computer Communications
• Concurrency and Computation: Practice and Experience

Publications

Journal Papers

1. Generating Massive Scale-free Networks: Novel Parallel Algorithms using the Preferential Attachment Model
   Maksudul Alam, Maleq Khan, Kalyan S. Perumalla, and Madhav Marathe
   ACM Transactions on Parallel Computing, Vol. 7, No. 2, pp 1-35, May 2020.
2. Fast Parallel Algorithms for Counting and Listing Triangles in Big Graphs
   Shaikh Arifuzzaman, Maleq Khan, and Madhav Marathe
   ACM Transactions on Knowledge Discovery from Data (TKDD), Vol. 14, No. 1, Pages 1-34, Dec 2019.
3. Finding and Counting Tree-Like Subgraphs Using MapReduce
   Zhao Zhao, Chen Langshi, Mihai Avram, Meng Li, Guanying Wang, Ali Butt, Maleq Khan, Madhav Marathe, Judy Qiu, and V.S. Anil Kumar
   IEEE Transactions on Multi-Scale Computing Systems, Vol. 4, No. 3, Pages 217-230, Sep. 2018.
4. Parallel Algorithms for Switching Edges in Heterogeneous Graphs
   Hasanuzzaman Bhuiyan, Maleq Khan, Jiangzhuo Chen, and Madhav Marathe
   Journal of Parallel and Distributed Computing, Vol. 104, Pages 19-35, June 2017.
5. Parallel Algorithms for Generating Random Networks with Given Degree Sequences
   Maksudul Alam and Maleq Khan
   International Journal of Parallel Programming, Vol. 45, No. 1, Pages 109-127, Feb 2017.
6. Effect of Modeling Slum Populations on Influenza Spread in Delhi
   Jiangzhuo Chen, Shuyu Chu, Youngyun Chungbaek, Maleq Khan, Christopher Kuhlman, Achla Marathe, Henning Mortveit, Anil Vullikanti, Dawen Xie
   BMJ Open, Vol. 6, No. 9, Sep. 2016.
7. Current and Future Challenges in Mining Large Networks: Report on the Second SDM Workshop on Mining Networks and Graphs
   Lawrence B. Holder, Maleq Khan, Christine Klymko, Rajmonda Caceres, Nitesh V. Chawla, Tina Eliassi-Rad, David F. Gleich, Ravi Kumar, Aditya Prakash, Jason Riedy, Yinghui Wu
   SIGKDD Explorations, Vol. 18, No. 1, June 2016.
8. Efficient Distributed Approximation Algorithms via Probabilistic Tree Embeddings
   Maleq Khan, Fabian Kuhn, Dahlia Malkhi, Gopal Pandurangan, and Kunal Talwar.
   Distributed Computing, Vol. 25, No. 3, Pages 189-205, June 2012.
9. Energy-Optimal Distributed Algorithms for Minimum Spanning Trees
   Yongwook Choi, Maleq Khan, Anil Kumar, and Gopal Pandurangan.
   Journal of Selected Areas in Communications, Vol. 27, No. 7, Pages 1297-1304, Sep 2009.
10. Distributed Algorithms for Constructing Approximate Minimum Spanning Trees in Wireless Sensor Networks
    Maleq Khan, Gopal Pandurangan, and Anil Kumar.
    IEEE Transactions on Parallel and Distributed Systems, Pages 124-139, Vol. 20, No. 1, Jan 2009.
11. A Fast Distributed Approximation Algorithm for Minimum Spanning Trees
    Maleq Khan and Gopal Pandurangan.
    Distributed Computing. Pages 391-402, Vol. 20, No. 6, Apr 2008.
12. A Simple Randomized Scheme for Constructing Low-Weight k-Connected Spanning Subgraphs with Applications to Distributed Algorithms
    Maleq Khan, Gopal Pandurangan, and Anil Kumar.
    Theoretical Computer Science, Pages 101-114, Vol. 385, No. 1-3, Oct. 2007.
13. An Efficient Weighted Nearest Neighbor Classifier using Vertical Data Representation
    William Perrizo, Qin Ding, Maleq Khan, Anne Denton, and Qiang Ding.
    International Journal of Business Intelligence and Data Mining, Vol. 2, No. 1, 2007.
14. Multimedia Data Transmission and Control using Active Networks
    Bharat Bhargava, Sheng-Yih Wang, Maleq Khan and Ahsan Habib.
    Journal of Computer Communications. Vol. 28, No. 6, Apr. 2005.
15. Edge-to-Edge Measurement-Based Distributed Network Monitoring
    Ahsan Habib, Maleq Khan, and Bharat Bhargava.
    Journal of Computer Networks, Vol. 44, No. 2, Feb. 2004.

    Conference Papers

16. A Multi-criteria Approximation Algorithm for Influence Maximization with Probabilistic Guarantees
    Maleq Khan, Gopal Pandurangan, Nguyen Dinh Pham, Anil Vullikanti, and Qin Zhang
    Proceedings of the SIAM Symposium on Algorithm Engineering and Experiments (ALENEX), Salt Lake City, Jan 2020.
17. A Blockchain-Based Internet of Things (IoT) Network for Security-Enhanced Wireless Battery Management Systems
    Tasnimun Faika, Taesic Kim, Justin Ochoa, Maleq Khan, Sung-Won Park, and Chung Leung
    IEEE Industry Applications Society Annual Meeting , Baltimore, MD, Sep. 2019.
18. Forecasting the Flu: Designing Social Network Sensors for Epidemics
    Huijuan Shao, K.S.M. Tozammel Hossain, Hao Wu, Maleq Khan, Anil Vullikanti, B. Aditya Prakash, Madhav Marathe, and Naren Ramakrishnan
    Proceedings of the ACM SIGKDD Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK), London, UK, Aug 2018.
19. An Internet of Things (IoT)-Based Network for Dispersed and Decentralized Wireless Battery Management Systems
    Tasnimun Faika, Taesic Kim, and Maleq Khan
    IEEE Transportation Electrification Conference and Expo (ITEC), Long Beach, CA, June 2018.
20. A Parallel Algorithm for Generating a Random Graph with a Prescribed Degree Sequence
    Hasanuzzaman Bhuiyan, Maleq Khan, and Madhav Marathe
    Fourth Workshop on High Performance Big Graph Data Management, Analysis, and Mining (BigGraphs), in conjunction with the IEEE International Conference on Big Data (IEEE BigData), Boston, MA, Dec. 2017.
21. Efficient Algorithms for Assortative Edge Switch in Large Labeled Networks
    Hasanuzzaman Bhuiyan, Maleq Khan, and Madhav Marathe
    25th High Performance Computing Symposium (HPC), Virginia Beach, VA, USA, April, 2017. Best Paper Award Runner-up.
22. An Efficient and Scalable Algorithmic Method for Generating Large-Scale Random Graphs
    Maksudul Alam, Maleq Khan, Anil Vullikanti, and Madhav Marathe
    Intl. Conf. for High Performance Computing, Networking, Storage and Analysis (SC16), Salt Lake City, Nov. 2016. Best Paper Award finalist.
23. An integrated agent-based approach for modeling disease spread in large populations to support health informatics
    Keith Bissett, Jose Cadena, Maleq Khan, Chris J. Kuhlman, Bryan Lewis, and Pyrros A. Telionis
    IEEE International Conference on Biomedical and Health Informatics (BHI), Las Vegas, 2016.
24. A Fast Parallel Algorithm for Counting Triangles in Graphs using Dynamic Load Balancing
    Shaikh Arifuzzaman, Maleq Khan and Madhav Marathe
    Second Workshop on High Performance Big Graph Data Management, Analysis, and Mining (BigGraphs), in conjunction with the IEEE International Conference on Big Data (IEEE BigData), Santa Clara, CA, Oct. 2015.
25. Parallel Algorithms for Generating Random Networks with Given Degree Sequences
    Maksudul Alam and Maleq Khan
    12th IFIP International Conference on Network and Parallel Computing (NPC), New York City, Sep. 2015.
26. A Space-efficient Parallel Algorithm for Counting Exact Triangles in Massive Networks
    Shaikh Arifuzzaman, Maleq Khan and Madhav Marathe
    17th IEEE International Conference on High Performance Computing and Communications (HPCC), New York City, Aug. 2015.
27. Fast Parallel Conversion of Edge List to Adjacency List for Large-Scale Graphs
    Shaikh Arifuzzaman and Maleq Khan
    23rd High Performance Computing Symposium (HPC), Alexandria, VA, USA, April 2015.
28. CINET 2.0: A Cyberinfstructure for Network Science
    Sherif Abdelhamid, Maksudul Alam, Richard Alo, ..., Maleq Khan, ..., Anil Vullikanti and Tak-Lon Wu
    10th IEEE International Conference on eScience, Guaruja, Brazil, Oct. 2014.
29. Fast Parallel Algorithms for Edge-Switching to Achieve a Target Visit Rate in Heterogeneous Graphs
    Hasanuzzaman Bhuiyan, Jiangzhuo Chen, Maleq Khan, and Madhav V. Marathe
    International Conference on Parallel Processing (ICPP), Minneapolis, Sep. 2014.
30. Distributed-Memory Parallel Algorithms for Generating Massive Scale-free Networks Using Preferential Attachment Model
    Maksudul Alam, Maleq Khan, and Madhav V. Marathe
    Intl. Conf. for High Performance Computing, Networking, Storage and Analysis (SC13), Denver, Nov. 2013.
31. PATRIC: A Parallel Algorithm for Counting Triangles in Massive Networks
    Shaikh Arifuzzaman, Maleq Khan, and Madhav V. Marathe
    ACM Conference on Information and Knowledge Management (CIKM), San Francisco, Oct. 2013.
32. A Fast Distributed Approximation Algorithm for Minimum Spanning Trees in the SINR Model
    Maleq Khan, Gopal Pandurangan, Guanhong Pei and V.S. Anil Kumar
    26th International Symposium on Distributed Computing (DISC), Salvador, Brazil, Oct. 2012.
33. CINET: A Cyberinfstructure for Network Science
    Sherif Abdelhamid, Richard Alo, S M Arifuzzaman, ..., Maleq Khan, ..., Anil Vullikanti and Zhao Zhao.
    8th IEEE International Conference on eScience, Chicago, Oct. 2012.
34. SAHAD: Subgraph Analysis in Massive Networks Using Hadoop
    Zhao Zhao, Guanying Wang, Ali Butt, Maleq Khan, V.S. Anil Kumar, and Madhav Marathe.
    26th IEEE International Parallel & Distributed Processing Symposium (IPDPS), Shanghai, China, May 2012.
35. On Minimizing Average End-to-End Delay in P2P Live Streaming Systems
    Fei Huang, Maleq Khan, and Binoy Ravindran.
    14th International Conference On Principles Of Distributed Systems (OPODIS), Tozeur, Tunisia, Dec. 2010.
36. NAP: An Agent-based Scheme on Reducing Churn-Induced Delays for P2P Live Streaming
    Fei Huang, Binoy Ravindran, and Maleq Khan.
    The IEEE International Conference on Peer-to-Peer Computing (P2P), Delft, Netherlands, Aug. 2010.
37. Subgraph Enumeration in Large Social Contact Networks using Parallel Color Coding and Streaming
    Zhao Zhao, Maleq Khan, V.S. Anil Kumar and Madhav V. Marathe.
    39th International Conference on Parallel Processing (ICPP), San Diego, California, Sep. 2010.
38. The Effect of Demographic and Spatial Variability on Epidemics: A Comparison between Beijing, Delhi, and Los Angeles.
    Jiangzhuo Chen, Fei Huang, Maleq Khan, Madhav Marathe, Paula Stretz, and Huadong Xia.
    Fifth International Conference on Critical Infrastructures, Beijing, Sep. 2010.
39. A Study of Information Diffusion over a Realistic Social Network Model
    Andrea Apolloni, Karthik Channakeshava, Lisa Durbeck, Maleq Khan, Chris Kuhlman, Bryan Lewis, and Samarth Swarup.
    International Symposium on Social Computing Applications, Vancouver, Canada, Aug. 2009.
40. Generation and Analysis of Large Synthetic Social Contact Networks
    Christopher Barrett, Richard Beckman, Maleq Khan, V.S. Anil Kumar, Madhav Marathe, Paula Stretz, Tridib Dutta, and Bryan Lewis.
    Winter Simulation Conference (WSC), Austin, Texas, Dec. 2009.
41. Bi-Criteria Approximation Algorithms for Power-Efficient and Low-Interference Topology Control in Unreliable Ad hoc Networks
    Maleq Khan, V.S. Anil Kumar, Madhav V. Marathe, Gopal Pandurangan, and S.S. Ravi.
    28th Conference on Computer Communications (INFOCOM), Rio de Janeiro, Brazil, Apr. 2009.
42. Efficient Distributed Approximation Algorithms via Probabilistic Tree Embeddings.
    Maleq Khan, Fabian Kuhn, Dahlia Malkhi, Gopal Pandurangan, and Kunal Talwar.
    27th ACM Symposium on Principles of Distributed Computing (PODC), Toronto, Canada, Aug. 2008.
43. Energy-Optimal Distributed Algorithms for Minimum Spanning Trees.
    Yongwook Choi, Maleq Khan, Anil Kumar, and Gopal Pandurangan.
    20th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), Munich, Germany, Jun. 2008.
44. A Fast Distributed Approximation Algorithm for Minimum Spanning Trees
    Maleq Khan and Gopal Pandurangan.
    20th International Symposium on Distributed Computing (DISC), Sep. 2006, Stockholm, Sweden. Best Paper Award.
45. PINE - Podium Incremental Neighbor Evaluator for Classifying Spatial Data
    William Perrizo, Qin Ding, Anne Denton, Kirk Scott, Qiang Ding, and Maleq Khan.
    ACM Symposium on Applied Computing (ACM-SAC), Melbourne, FL, USA, March 2003.
46. Fast k-Nearest Neighbor Classification on Spatial Data Streams Using P-trees
    Maleq Khan, Qin Ding, and William Perrizo.
    6th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Taipei, Taiwan, May 2002.
47. The P-tree Algebra
    Qin Ding, Maleq Khan, Amalendu Roy and William Perrizo.
    ACM Symposium on Applied Computing (ACM-SAC), Madrid, Spain, March 2002.

    Book Chapters

48. Distributed Memory Parallel Algorithms for Massive Graphs
    Maksudul Alam, Shaikh Arifuzzaman, Hasanuzzaman Bhuiyan, Maleq Khan, V.S. Anil Kumar, and Madhav Marathe
    Parallel Graph Algorithms, CRC Press / Taylor & Francis
    Ed. David Bader
49. Algorithms for Finding Motifs in Large Labeled Networks
    Maleq Khan, V.S. Anil Kumar, Madhav Marathe, and Zhao Zhao
    Dynamics On and Of Complex Networks, Volume 2, Springer, 2013.
    Eds. Animesh Mukherjee, Monojit Choudhury, Fernando Peruani, Niloy Ganguly, Bivas Mitra
50. Social Networks
    Maleq Khan, V.S. Anil Kumar, Madhav Marathe, and Paula Stretz
    Encyclopedia of Parallel Computing, first edition, Springer, 2011.
    Ed. David Padua
51. Theory of Communication Networks
    Gopal Pandurangan and Maleq Khan
    Algorithms and Theory of Computation Handbook, second edition, CRC Press, 2009. A best-selling book.
    Eds. Mikhail Atallah and Marina Blanton

    Posters (peer-reviewed)

52. Synthetic Populations for Epidemic Modeling
    Abhijin Adiga, Richard Beckman, Keith Bisset, Jiangzhuo Chen, Youngyun Chungbaek, Stephen Eubank, Sandeep Gupta, Maleq Khan, Chris Kuhlman, Eric Lofgren, Bryan Lewis, Achla Marathe, Madhav Marathe, Henning Mortveit, Eric Nordberg, Caitlin Rivers, Paula Stretz, Samarth Swarup, Amanda Wilson and Dawen Xie.
    International Conference on Computational Social Science (IC2S2), Helsinki, Finland, Jun 2015.
53. Parallel Algorithms for Counting Triangles and Computing Clustering Coefficients.    (Extended abstract)
    S M Arifuzzaman, Maleq Khan, and Madhav Marathe
    Super Computing (SC), Salt Lake City, Nov. 2012.
54. Parallel Color Coding and Graph Partitioning Enabling Subgraph Counting for Massive Graphs
    Zhao Zhao, Maleq Khan, V.S. Anil Kumar, and Madhav Marathe
    Super Computing (SC), New Orleans, Nov. 2010.
55. Simulating Social Information Diffusion Using a Synthetic Population.     (Extended abstract)
    Andrea Apolloni, Karthik Channakeshava, Lisa Durbeck, Maleq Khan, Christopher Kuhlman, Bryan Lewis, and Samarth Swarup.
    NICO Complexity Conference, Northwestern University, Evanston, IL, Sep. 2009. Poster Winner.

    Dissertation and Theses

56. Distributed Approximation Algorithms for Minimum Spanning Trees and Other Related Problems with Application to Wireless Ad Hoc Networks
    Maleq Khan.
    Ph.D. dissertation, Department of Computer Science, Purdue University, West Lafayette, Indiana, 2007.
57. Fast Distance Metric Based Data Mining Techniques Using P-trees
    Maleq Khan.
    Masters thesis, Computer Science Department, North Dakota State University, Fargo, North Dakota, 2001.
58. Performance Analysis of Multiprocessor Systems with Multilevel Cache
    Maleq Khan and Mahmud Hasan.
    Undergraduate thesis, Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka, 1996.

Impact of My Research

Talks

1. Distributed-Memory Parallel Algorithms for Graph Analytics
   invited talk, EECS Research Colloquium Series at the Department of Electrical Engineering and Computer Science Texas A&M University-Kingsville, Feb 2020.
2. Parallel Graph Algorithms
   at The 3rd Southwest Texas Asian Symposium (SWTAS), hosted at Texas A&M University-Kingsville, Nov 2019.
3. Efficient Parallel Algorithms for Large-Scale Graph Analytics
   at The 2nd Mid-South Theory Day (MSTD), hosted at the University of Houston, Houston, Texas, March 2018.
4. Scalable Parallel Computing of Massive-Scale Graph Analytics for Big Data
   invited talk, at the College of Engineering Dean’s Leadership Board Meeting, Texas A&M University--Kingsville, Oct. 2017.
5. Efficient Parallel Algorithms for Generating Random Graphs
   invited talk, at The 1st Mid-South Theory Day, Louisiana State University, Baton Rouge, LA, Dec. 2016.
6. An Efficient and Scalable Algorithmic Method for Generating Large-Scale Random Graphs
   at the Intl. Conf. for High Performance Computing, Networking, Storage and Analysis (SC16), Salt Lake City, Nov. 2016.
7. Scalable Parallel Algorithms for Network Analysis Problems using HPC Systems
   invited talk, at the Department of Electrical Engineering and Computer Science, Texas A&M University--Kingsville, May 2016.
8. How to Use CINET: A Cyberinfrastructure for Network Science
   invited talk, at a workshop on the CINET system at the University at Albany - SUNY, Albany, Aug. 2015.
9. Parallel Graph Algorithms: Challenges and Approaches
   Invited talk, at the Department of Computer Science, University at Albany - SUNY, Albany, Aug. 2015.
10. How to Use CINET: A Cyberinfrastructure for Network Science
    invited talk, at a workshop on the CINET system at Virginia Tech, Blacksburg, VA, July 2015.
11. Demonstration of CINET: A Cyberinfrastructure for Network Science
    At the 2nd Workshop on Mining Networks and Graphs, in conjunction with SIAM International Conference on Data Mining (SDM), Vancouver, Canada, May 2015.
12. Parallel Graph Algorithms: Challenges and Approaches
    Invited talk, at NDSSL weekly seminar, Virginia Bioinformatics Institute, Virginia Tech, Feb. 2015.
13. Parallel Graph Algorithms: Challenges and Approaches with Practical Considerations
    Invited talk, At NII Shonan Meeting on Algorithms for Large-Scale Graphs, Shonan Village Center, Hayama, Kanagawa, Japan, Oct. 2014.
14. Fast Parallel Algorithms for Edge-Switching to Achieve a Target Visit Rate in Heterogeneous Graphs
    At the International Conference on Parallel Processing (ICPP), Minneapolis, Sep. 2014.
15. A Parallel Algorithm for Counting Triangles in Massive Networks
    At the ACM Conference on Information and Knowledge Management (CIKM), San Francisco, Oct. 2013.
16. Experiences and lessons learned in critical infrastructure decision informatics
    Invited talk, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh, July 2011.
17. Experiences and lessons learned in critical infrastructure decision informatics
    At NetONets (satellite to NetSci 2011), Budapest, Hungary, June 2011
18. Subgraph Enumeration in Large Social Contact Networks using Parallel Color Coding and Streaming
    At the 39th International Conference on Parallel Processing (ICPP), San Diego, California, Sep. 2010.
19. A Study of Information Diffusion over a Realistic Social Network Model
    At the International Symposium on Social Computing Applications, Vancouver, Canada, Aug. 2009.
20. Efficient Distributed Approximation Algorithms via Probabilistic Tree Embeddings
    At the 27th ACM Symposium on Principles of Distributed Computing (PODC), Toronto, Canada, Aug. 2008.
21. Distributed Approximation Algorithms for Minimum Spanning Trees and Other Related Problems
    Invited talk, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, July 2007.
22. A Fast Distributed Approximation Algorithm for Minimum Spanning Trees
    At the 20th International Symposium on Distributed Computing (DISC), Stockholm, Sweden, Sep 2006.
23. Local Distributed Algorithms via Nearest Neighbor Tree
    Invited talk, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh, Jan 2005.
24. How to Learn Math and Science
    Invited talk, for high-school students at a high school in Bangladesh, Jan 2005.
25. Local Distributed Algorithms via Nearest Neighbor Tree
    Invited talk, at the 49th Midwest Theory Day, DePaul University, Chicago, Dec 2004.
26. Energy-Efficient Local Distributed Algorithms for Wireless Ad Hoc Networks
    Invited talk, as a guest lecturer for the graduate course CS 690B: Pervasive Systems", Fall 2004, Purdue University.
27. Fast k-Nearest Neighbor Classification on Spatial Data Streams Using P-trees
    At the 6th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Taipei, Taiwan, May 2002.
28. Distributed Approximation Algorithms for Minimum Spanning Trees and Other Related Problems with Applications to Wireless Ad Hoc Networks
    PhD dissertation defense, Purdue University, Apr. 2007.
29. Energy-Efficient Local Distributed Algorithms for Wireless Ad Hoc Networks
    PhD preliminary examination, Purdue University, July 2004.
30. Work-Efficient Distributed Algorithms
    as a part of PhD qualifying examination, Purdue University, Jan. 2004.
31. Fast Distance Metric Based Data Mining Techniques Using P-trees
    MS thesis defense, North Dakota State University, Dec. 2001.

Teaching

Texas A&M University-Kingsville, TX

1. Data Mining (graduate), Fall 2020, Summer 2020, Fall 2019, Summer 2019, Fall 2018
2. Massive Parallel Computing (graduate), Summer 2020, Spring 2020, Summer 2019, Spring 2019, Summer 2019, Spring 2018, Spring 2017
3. Database Systems (graduate), Spring 2020, Spring 2019
4. Operating Systems (graduate), Spring 2020
5. Data Structures and Algorithms (undergraduate), Spring 2019, Spring 2018, Spring 2017
6. Data Mining (undergraduate), Fall 2019, Fall 2018, Fall 2017, Fall 2016
7. Computer Networks (undergraduate), Fall 2019, Fall 2018, Fall 2017, Fall 2016

   Purdue University, West Lafayette, IN

8. Introduction to Organizational Computing (undergradaute), Summer 2005
9. Teaching assistant for graduate course Algorithm Design, Analysis, and Implementation, Fall 2004

   American International University Bangladesh, Dhaka, Bangladesh

10. Introduction to Programming, Fall 1998
11. Discrete Mathematics, Fall 1998

    East West University, Dhaka, Bangladesh

12. Structural Programming, Summer 1998, Fall 1997
13. Discrete Mathematics, Summer 1998, Fall 1997
14. Programming with C and C++, Spring 1998
15. Mathematics for Computer Science, Spring 1997, Summer 1997

Professional Experience

• Texas A&M Univeristy-Kingsville, Department of Electrical Engineering and Computer Science, Kingsville, TX 78363
  Assistant Professor, Aug. 2016 - date
  
• Biocomplexity Institute, Virginia Tech, Blacksburg, VA 24060
  Research Scientist, July 2010 - Aug 2016
  Postdoctoral Fellow, Sep 2007 - June 2010
  
• Purdue University, Department of Computer Sciences, West Lafayette, IN 47907
  -- Bilsland Dissertation Fellowship for research, Aug 2006 - July 2007
  -- Research Assistant, Jan 2002 - May 2006 (except Fall 2004 & Summer 2005) and Aug - Sep 2007.
  Research areas are distributed algorithms, algorithms for wireless ad hoc and sensor networks.
  -- Instructor, CS 235: Introduction to Organizational Computing, Summer 2005
  -- Teaching Assistant, CS 580: Algorithm Design, Analysis, and Implementation, Fall 2004
• ExaGrid Systems Inc., Westborough, MA 01581
  Summer Intern, May 2006 - Aug 2006
  I worked on their existing delta compression algorithm and code. I did research on this algorithm, improved the performance significantly and rewrote the code completely using C language in about 1600 lines. I worked under supervision of Dave Therrien, the Chief Technical Officer and Founder of the company.
• North Dakota State University, Computer Science Department, Fargo, ND 58105
  Research Assistant, Jan 2000 - Dec 2001
  The research work involved Data Mining of Remotely Sensed Image Data. Also worked on a development team of a web-based data mining software tool using Java.
• National University of Singapore, School of Computing, Singapore
  Research Assistant (full time job), Dec 1998 - Dec 1999
  The primary concern was using neural networks in data mining: using neural networks for classification, prediction, feature extraction, etc. Also developed a data-mining tool using Visual C++.
• American Int. University Bangladesh, Dept. of Computer Sc. & Engg., Dhaka, Bangladesh
  Lecturer, Sep 1998 - Nov 1998
  Courses taught: Discrete Mathematics, Introduction to Programming.
• East West University, Department of Computer Science, Dhaka, Bangladesh
  Lecturer, Mar 1997 - Aug 1998
  Courses taught: Discrete Mathematics, Mathematics for Computer Science, Structural Programming (Pascal), Programming with C and C++.
  Other responsibilities: creating class schedules, processing final grades of the students.
• North South University, Department of Computer Science, Dhaka, Bangladesh
  Teaching Assistant, Jun 1996 - Feb 1997

Recent Major Software Projects

• I led the development of a graph algorithm library called Galib. Currently Galib contains implementations of at least 40 different, both parallel and sequential, efficient network and graph analysis algorithms. Some examples of the network analysis measures are diameter, shortest path, clustering coefficient, BFS, subgraphs, triangles, cliques, and various random graph generators. I wrote about one third of the codes myself and guided three graduate student in developing the rest.
• I am also part of a team that developed a cyberinfrastructure for network science, called CINET. CINET provides a middleware and a web-based user interface for graph analysis. CINET contains over 200 networks and over 100 graph algorithms and generators. Among the networks, there are real-world, synthetic, and random networks. A user can also upload his own networks to the CINET system to analyze them using the provided graph analysis algorithms. CINET includes network analysis algorithms from Galib and two other such libraries: SNAP (developed at Stanford University) and NetworkX (developed at Los Alamos National Laboratory).
• I have implemented a simulation software for simulating epidemic and contagious diseases. This simulator is designed to simulate contagious diseases for the entire US population that takes into account the long distance travel by various modes such as air travel and ground travel. Various statistical long distance travel data are used in the simulation model. This simulator has been used in an study of disaster response and an study of ebola outbreak done by our group for Defense Threat Reduction Agency (DTRA).
• I have also played a significant role in another project at Virginia Tech: construction of synthetic populations and social contact networks for various countries of the world. This work uses land scan data, census data, and various commercial and open source survey data to construct synthetic populations and contact networks. These contact networks can be used to study contagious diseases in different countries.