Mahmoud Daneshmand

Teaching Professor

School: School of Business

Building: Babbio Center

Room: 303B

Phone: (201) 216-5542

Fax: (201) 216-5385

Email: mdaneshm@stevens.edu

Research

He is a Data Scientist, expert in Big Data Analytics, Machine Learning, and Artificial Intelligence with extensive industry experience including with the Bell Laboratories as well as the Info Lab of the AT&T Shannon Labs – Research.

He has published more than 250 journal and conference papers; authored/co-authored three books, three US Patents.

He is well recognized within the academia and industry and holds key leadership roles in IEEE Journal Publications, Conferences, IEEE - Industry Partnership, and IEEE Future Direction Initiatives. He is Co-Founder and Chair of Steering Committee of IEEE Internet of Things (IoT) Journal; Member of Steering Committee of IEEE Transaction on Big Data; Advisory Board of the IEEE Blockchain Newsletter; Guest Editor of several IEEE Journal publications; Guest Editor of ITU Journal Special Issue on Data for Good; Co-Founder of the IEEE Big Data Initiative; Vice Chair of the IEEE Technical Community on Big Data.

General Information

Mahmoud Daneshmand is Professor of Business Intelligence & Analytics at Howe School of Technology Management as well as Computer Science at School of Engineering and Science, Stevens Institute of Technology. He has more than 35 years of teaching, research & publications, consultation, and management experience in academia & industry including: Bell Laboratories, AT&T Shannon Labs – Research, University of California at Berkeley, University of Texas at Austin, Sharif University of Technology, University of Tehran, New York University, and Stevens Institute of Technology.

He has served as Distinguished Member of Technical Staff (DMTS) at Bell Labs as well as AT&T Shannon Labs -Research; Assistant Chief Scientist of AT&T Labs; Founder and Executive Director of the AT&T Labs university collaborations program. He is an Industry Professor at the School of Business and department of Computer Science, Co-Founder of the Business Intelligence & Analytics MS program at Stevens Institute of Technology. He is an expert in Big Data Analytics, Internet of Things (IoT)/Sensor & RFID Data Streams Analytics, Data Mining Algorithms, Machine Learning, Probability & Stochastic Processes, and Statistics. He is experienced in Risk Management, Quality and Reliability of IP-Based Services and Applications.
Mahmoud is well recognized within the academia and industry. He has published more than 95 Journal and conference papers; authored/co-authored three books; Holds two patents (2009 and 2010); Chair of New IEEE Journal of Internet of Things; Guest Editor of IEEE Communications Magazine (published in Feb 2011), Guest Editor of Journal of Networks and System Management (published September 2011); Guest Editor, IEEE Sensors Journal SI on Internet of Things (to be published September 2013); Keynote Speaker: ISITCE 2012 (South Korea), IEEE ISCC 2011 (Corfu), ICC 09 (Dresden), IEEE ISCC 2008 (Marrakesh), ICT 2008 (St. Petersburg), IMSEE 2000 (Tehran), and ICISTM 2008 (Dubai); Co-editor of three IEEE Proceedings on Computers and Communications with a total of more than 450 peer reviewed accepted technical papers (Seventh (2002), Eleventh (2006), and fifteenth (2010) ); innovated and led execution of more than 60 Bell Labs and AT&T Labs large-scale projects on computer and communications; served as analytics and statistics consultant in many research, business and operations projects; made extensive contributions to the Industry Standards and regulatory organizations including ITU, ANSI, and FCC (invented the well known standardized Networks Outage Index). He has chaired multiple international conferences including IEE 2003 (London), IEEE ISCC 2002 (Sicily), IEEE ISCC 2006 (Sardinia, Italy), WICON 2010 (Singapore), and IEEE ISCC 2010 (Riccione, Italy), and Cyber Security (China 2011). Organized and served as Keynote Chair and Panel Chair of many IEEE conference in including: ICC 2007 (Glasgow, Scotland), ICC 2009 (Dresden, Germany), GLOBECOM 2009 (Hawaii, US), NOMS 2010 (Osaka, Japan), GLOBECOM 2010 (Miami, US), GLOBECOM 2011 (Houston), NOMS 2012 (Hawaii), INFOCOM 2012 (New Orleans), and GLOBECOM 2012 (Anaheim) ; Held and chaired AT&T Labs annual Academia-Industry Joint Research Collaborations Symposiums (UC Symposiums 2005, 2006, 2007, 2008, 2009, and 2010).

He served as an expert witness in several legal industrial courts and litigations and established scientific validity of several Bell Labs studies; designed and taught many graduate and undergraduate courses in areas of Data Mining, Machine Learning, Artificial Intelligence, Sampling Techniques, Probability and Stochastic Processes, Risk Management, and Inferential Statistical Techniques; advised many master and PhD dissertations; led more than 200 Data Mining case studies of graduate students working with high technology corporations such as AT&T, Lucent, Verizon, and Merck. He served as a member of Advisory Board of Center for Networked Systems at the University California San Diego; Advisory Board of SATM (Stevens Alliance for Technology Management); Editorial Board of the JNSM (Journal of Network and Systems Management).

As professor of the Howe School of Technology Management he has developed and taught new graduate courses on emerging areas of "Risk Management", "Data Mining", and Data Streams Analytics. He has contributed to proposal and establishment of two new graduate programs at Stevens: Financial Engineering, and Business Intelligence & Analytics. He is co-founded a new MS program on Business Intelligence & Analytics.

As professor of the Department of Computer Science he teaches “Probability and Stochastic Processes" and "Data Mining & Knowledge Discovery", and advises graduate students projects and Masters and PhD thesis.
Prior to his position of DMTS, he has served as Technology Leader AT&T Labs, Technology Consultant AT&T Labs, Principal Technical Staff Member of the AT&T Labs, and a Distinguished Member of Technical Staff of the Bell Laboratories, Lucent Technologies.

Experience

Industry Experience

Assistant Chief Scientist of AT&T Laboratories; Distinguished Member of Technical Staff (DMTS) at Bell Labs as well as AT&T Shannon Labs-Research; Founding Executive Director of the AT&T Labs university collaborations program; Technology Leader, and Member of Technical Staff, AT&T Labs.

University Experience

Co-Founder and professor of the Business Intelligence & Analytics MS program at Stevens Institute of Technology; Professor of Computer Science and Financial Engineering; adjunct professor at NYU; Associate professor of Department of Statistics at UC, Berkeley; Co-founder and Dean of the School of Informatics & Management, Founding Chair of Department of Statistics, National University of Iran; and assistant professor of Mathematics at University of Texas, Austin.

Institutional Service
  • Committee Member: NJBDA Entrepreneurship Committee (representing Stevens) Member
  • Board Member: New Jersey Big Data Alliance (NJBDA) Member
  • SoB P&T Committee Member
  • BIA Bi-Weekly Faculty Meetings Committee Member
  • MIS Bi-Weekly Faculty Meetings Committee Member
Professional Service
  • Editorial Board: IEEE Blockchain Newsletter Editorial Board
  • Editorial Board: Big Data Research, ELSEVIER Editorial Board: Big Data Research, ELSEVIER
  • Chair of Steering Committee: IEEE Internet of Things Journal (IoT -J), 2014-Present Chair of Steering Committee: IEEE Internet of Things Journal (IoT -J)
  • Executive Programs Chair, IEEE GLOBECOM 2019, December 2019, Hawaii, USA: Executive Programs Chair, IEEE GLOBECOM 2019, December 2019, Hawaii, USA:
  • General Co-Chair, IEEE Technology Time Machine, October 2018 General Co-Chair, IEEE Technology Time Machine, October 2018
  • General Chair, IEEE 2019 International Conference on Smart Internet of Things, August 2019, Tianjin, China General Chair, IEEE 2019 International Conference on Smart Internet of Things
  • Executive Committee, IEEE Summit on Communications Futures, 18 January 2020 // Honolulu, Hawaii, USA Executive Committee, IEEE Summit on Communications Futures, 18 January 2020 // Honolulu, Hawaii, USA
  • Chair of Steering Committee: IEEE Transaction on Big Data Chair of Steering Committee: IEEE Transaction on Big Data
  • Guest Editor: Data for Good, Special Issues, ITU Journal: ICT Discoveries, 2018 (to be published December 2018): Guest Editor: Data for Good, Special Issues, ITU Journal: ICT Discoveries, 2018 (to be published December 2018):
  • Guest Editor: IEEE IoT Journal Special Issue: Nature-Inspired Approaches for IoT and Big Data, Guest Editor: IEEE IoT Journal Special Issue: Nature-Inspired Approaches for IoT and Big Data,
Innovation and Entrepreneurship

• The IoT week-Europe 2015
• GLOBECOM 2014
• IEEE M2M 2014
• IEEE Big Data Initiative Workshop 2014
• BLOBECOM 2013
• IEEE IoT 2013
• 4th IT Convergence Symposium 2012
• IEEE ISCC 2012, ICC 2009
• IEEE ISCC 2008
• ICT 2008



Honors and Awards

He is the recipient of several distinguished awards from Bell Labs, AT&T Labs, Standards Committee T1, and IEEE.

Professional Societies
  • IEEE Sensor – IEEE Sensor Council Senior member
  • IEEE ComSoc – IEEE Communication Society Senior member
  • ASA – American Statistical Association Senior member
  • NJBDA – New Jersey Big Data Alliance Member
  • IEEE CS – IEEE Computer Society Senior member
Patents and Inventions

M. Daneshmand, C. Wang, K. Sohraby, R. Jana, L. Ji, “System and Method for providing Network Selection in Cognitive Radio Systems,” Invention Disclosure, April 2009 (Pending).

M. Daneshmand and C. Wang, “Radio Frequency Identification Readers and Methods for Adjusting a Query Command Slot-Counter: Parameter Q,” Application No. 12/323996 (Pending).

Selected Publications
Book Chapter
  1. Li, Y.; Zhang, H.; Wang, J.; Cao, B.; Liu, Q.; Daneshmand, M.. Energy-Efficient Deployment and Adaptive Sleeping in Heterogeneous Cellular Networks. IEEE Access (vol. 7, pp. 35838–35850,).
Conference Proceeding
  1. Wang, H.; Daneshmand, M.; Fang, H.. Artificial Intelligence (AI) Driven Wireless Body Area Networks: Challenges and Directions. 2019 IEEE International Conference on Industrial Internet (ICII (pp. 428–429). Orlando, FL, USA.
  2. Hu, M.; Xu, G.; Ma, C.; Daneshmand, M.. Detecting Review Spammer Groups in Dynamic Review Networks. Proceedings of the ACM Turing Celebration Conference-China (pp. 1–6,).
  3. Guo, H.; Wu, S.; Wang, H.; Daneshmand, M.. DSIC: Deep Learning Based Self-Interference Cancellation for In-Band Full Duplex Wireless. 2019 IEEE Global Communications Conference (GLOBECOM (pp. 1–6,). Waikoloa, HI, USA.
  4. Xu, G.; Hu, M.; Ma, C.; Daneshmand, M.. GSCPM: CPM-Based Group Spamming Detection in Online Product Reviews. ICC 2019 - 2019 IEEE International Conference on Communications (ICC (pp. 1–6). Shanghai, China.
  5. Xu, G.; Jiang, P.; Ma, C.; Daneshmand, M.; Xie, S.. VRPSOFC: A Framework for Focused Crawler Using Mutation Improving Particle Swarm Optimization Algorithm. Proceedings of the ACM Turing Celebration Conference-China (pp. 1–7,).
  6. Liu, W.; Cao, B.; Zhang, L.; Peng, M.; Daneshmand, M.. A Distributed Game Theoretic Approach for Blockchain-based Offloading Strategy. ICC 2020 - 2020 IEEE International Conference on Communications (ICC (pp. 1–6). Dublin, Ireland.
Journal Article
  1. Iqbal, W.; Abbas, H.; Daneshmand, M.; Rauf, B.; Abbas, Y.. An In-Depth Analysis of IoT Security Requirements, Challenges and their Countermeasures via Software Defined Security. IEEE Internet of Things Journal, Early Access in.
  2. Xu, G.; Tang, Z.; Ma, C.; Liu, Y.; Daneshmand, M.. A Collaborative Filtering Recommendation Algorithm Based on User Confidence and Time Context". Hindawi Journal of Electrical and Computer Engineering.
  3. Li, Z.; Fang, H.; Wang, H.; Daneshmand, M.. A Data-Centric Cognitive Gateway with Distributed MIMO for Future Smart Homes. IEEE Wireless Communications (3 ed., vol. 26, pp. 40–46,).
  4. Ning, H.; Farha, F.; Mohammad, Z.; Daneshmand, M.. A Survey and Tutorial on “Connection Exploding Meets Efficient Communication” in the Internet of Things. IEEE Internet of Things Journal, Early Access in.
  5. Ning, H.; Zhen, Z.; Shi, F.; Daneshmand, M.. A Survey of Identity Modeling and Identity Addressing in Internet of Things. IEEE Internet of Things Journal (6 ed., vol. 7, pp. 4697–4710,).
  6. Mohanta, B.; Jena, D.; Ramasubbareddy, S.; Daneshmand, M.; Gandomi, A.. Addressing Security and Privacy Issues of IoT using Blockchain Technology. IEEE Internet of Things Journal, Early Access in.
  7. Ning, H.; Ye, X.; Sada, A.; Mao, L.; Daneshmand, M.. An Attention Mechanism Inspired Selective Sensing Framework for Physical-Cyber Mapping in Internet of Things. IEEE Internet of Things Journal (6 ed., vol. 6, pp. 9531–9544,).
  8. Hu, P.; Ning, H.; Chen, L.; Daneshmand, M.. An Open Internet of Things System Architecture Based on Software-Defined Device. IEEE Internet of Things Journal (2 ed., vol. 6, pp. 2583–2592,).
  9. Mukherjee, P.; Yang, L.; Yan, Z.; Daneshmand, M.. Dynamic Clustering Method based on Power Demand and Information Volume for Intelligent and Green IoT. Elsevier Computer Communications (vol. 152, pp. 119–125,).
  10. Ning, H.; Liu, X.; Ye, X.; He, J.; Zhang, W.; Daneshmand, M.. Edge Computing-Based ID and nID Combined Identification and Resolution Scheme in IoT. IEEE Internet of Things Journal (4 ed., vol. 6, pp. 6811–6821,).
  11. Jayaraman, S.; Ramachandran, M.; Patan, R.; Daneshmand, M.; Gandomi, A.. Fuzzy Deep Neural Learning Based on Goodman and Kruskal's Gamma for Search Engine Optimization. IEEE Transactions on Big Data, Early Access in.
  12. Gandomi, H.. Guest Editorial Nature-Inspired Approaches for IoT and Big Data. IEEE Internet of Things Journal (6 ed., vol. 6, pp. 9213–9216,).
  13. Behera, T.; Mohapatra, S.; Samal, U.; Khan, M.; Daneshmand, M.; Gandomi, A.. I-SEP: An Improved Routing Protocol for Heterogeneous WSN for IoT-Based Environmental Monitoring. IEEE Internet of Things Journal (1 ed., vol. 7, pp. 710–717,).
  14. Dhingra, S.; Madda, R.; Gandomi, A.; Patan, R.; Daneshmand, M.. Internet of Things Mobile–Air Pollution Monitoring System (IoT-Mobair. IEEE Internet of Things Journal (3 ed., vol. 6, pp. 5577–5584,).
  15. Li, J.; Wu, J.; Hu, B.; Wang, C.; Daneshmand, M.; Malekian, R.. Introduction to the Special Section on Big Data and Artificial Intelligence for Network Technologies. IEEE Transactions on Network Science and Engineering (1 ed., vol. 7, pp. 1–2,).
  16. Yan, S.; Jiao, M.; Zhou, Y.; Peng, M.; Daneshmand, M.. Machine Learning Approach for User Association and Content Placement in Fog Radio Access Networks. IEEE Internet of Things Journal, Early Access in.
  17. Wang, J.; Liu, X.; Peng, M.; Daneshmand, M.. Performance Analysis of D-MoSK Modulation in Mobile Diffusive-Drift Molecular Communications. IEEE Internet of Things Journal, Early Access in.
  18. Wang, J.; Peng, M.; Liu, Y.; Liu, X.; Daneshmand, M.. Performance Analysis of Signal Detection for Amplify-and-Forward Relay in Diffusion-Based Molecular Communication Systems. IEEE Internet of Things Journal (2 ed., vol. 7, pp. 1401–1412,).
  19. Piao, Z.; Peng, M.; Liu, Y.; Daneshmand, M.. Recent Advances of Edge Cache in Radio Access Networks for Internet of Things: Techniques, Performances, and Challenges. IEEE Internet of Things Journal (1 ed., vol. 6, pp. 1010–1028,).
  20. Behera, T.; Mohapatra, S.; Samal, U.; Khan, M.; Daneshmand, M.; Gandomi, A.. Residual Energy-Based Cluster-Head Selection in WSNs for IoT Application. IEEE Internet of Things Journal (3 ed., vol. 6, pp. 5132–5139,).