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Bilal Khan

Bilal Khan

Assistant Professor


Assistant Professor
Computer Science and Engineering, School of
Office Phone(909) 537-5428
Office LocationJB-340

Office Hours

Monday: 12:00-13:00
Wednesday: 12:00-13:00


Dr. Bilal M. Khan holds a Ph.D. in computer science (artificial intelligence) with the thesis title "Game theoretic coalitional routing in cooperative vehicular ad hoc networks", MSc in pervasive computing and Master of science in computer science. While serving as an assistant researcher at UCLA from 2013 to 2020, Dr. Khan developed the most robust and comprehensive decision support system as an online nanoinformatics platform to assist regulatory bodies for the management of nanotechnology. The nanoinformatics platform consists of machine learning and data mining models that are supported by the largest database of nanomaterials. Bilal maintained the platform via a high performance computing cluster that was designed from scratch (with 24 compute nodes and 115TB of storage space for high performance computations and simulations). At UCLA, Dr. Khan also led the development of a cyber-infrastructure for a virtual water district for efficient use and consumption of water in small rural agricultural communities. Additionally, Dr. Khan developed data-driven approaches (using machine and deep learning techniques) for water use patterns in the small communities as online applications.

In 2018, Dr. Khan also co-founded a technology startup in the water treatment industry and served as the chief analytics officer where he developed the cyber-infrastructure and operator decision support system for real-time monitoring of membrane health in membrane-based water treatment plants. At the startup, he co-developed a patent pending real-time membrane monitoring technology with a combination of hardware and software using advanced computer vision and pattern recognition techniques. 

Dr. Khan received his Ph.D. at the age of 25 years from the University of Bradford (UK) and was named among the 13 young professionals by water and waste digest in 2019 for his contributions in the water treatment technology. His contributions in various disciplines, particularly in nanotechnology, environmental risk assessment and water treatment have already produced over 20 high impact publications (Nature nanotechnology, Small, Beilstein Journal of Nanotechnology, Desalination, Journals of Nanoparticle research, Applied surface sciences, Applied geophysics, membrane sciences, environmental science and technology, and nanotoxicology). Dr. Khan has also delivered over 30 presentations at international conferences/workshops (American Water Works Association, American Chemical Society, American Institute of Chemical Engineers, US-EU Nanotechnology Roadmap, US Nano Working Group) and supervised Ph.D. and graduate students in cross-disciplinary areas. Dr. Bilal is also an active reviewer of reputed journals (including Nature Scientific Data, Environmental Science and Technology, Nanoscale, Nanotoxicology, ACS Nano, Remote Sensing) and has chaired technical sessions in the fields of Nanotechnology and Water treatment.


Ph.D. Artificial Intelligence, University of Bradford (UK) | Thesis Title: Game Theoretic Coalitional Routing in Cooperative Vehicular Ad Hoc Networks (2008–2012)

PG Cert in Higher Education Practice, University of Bradford (UK) (2012)

M.Sc. Computer Science, Birmingham City University (UK) (2006)

M.Sc. Computer Science, COMSATS University of IT (Pakistan) (2003–2006)



  1. Spring 2021 - Spring 2023 CSE 5120 Introduction to Artificial Intelligence - CSUSB
  2. Fall 2020/Fall 2022 CSE 4600 Operating systems - CSUSB
  3. Fall 2020/Spring 2023 CSE 4550 Software engineering - CSUSB
  4. 2012 COS7025-B Mobile Application Development - University of Bradford (UK)
  5. 2011 COS7023-B Internet Security & Protocols - University of Bradford (UK)
  6. 2010 COS7024-B Networks & Protocols - University of Bradford (UK)
  7. 2009 ENB3001-B Computer Communications - University of Bradford (UK)

Teaching assistant

  1. 2010 COS7023-B, Internet Security & Protocols - University of Bradford (UK)
  2. 2010 COS7024-B Networks & Protocols - University of Bradford (UK)
  3. 2009 COS7024-B Networks & Protocols - University of Bradford (UK)
  4. 2009 COS7023-B, Internet Security & Protocols - University of Bradford (UK)
  5. 2008 ENB3001-B, Computer Communications - University of Bradford (UK)
  6. 2008 ENG1010M, Circuits and Systems - University of Bradford (UK)


Interested in the application of artificial intelligence techniques (including machine/deep learning, data mining and computer vision) in cross-disciplinary areas. Developed and maintained an online nanoinformatics platform for environmental impact assessment of engineered nanomaterials (ENMs). Nanoinformatics platform supports the environmental impact assessment of ENMs with a central database of ENMs safety data and a toolkit for various exploration/analysis methods based on machine learning and data mining approaches. These methods include the estimation of ENMs environmental exposure levels (MendNano), evaluation of ENMs environmental releases (LearNano), analysis of EMNs high throughput toxicity data (HDAT), predictive toxicity models (e.g. QSARs), analysis of ENMs environmental impact via Bayesian inference (NanoEIA).

Working on developing analytical and advanced machine/deep learning approaches for autonomous and smart water treatment systems. The approaches for optimzation water treatment system control are based on deep reinforcement learning, unsupervised learning, anomaly/fault detection and prediction and time-series prediction models (long short term memory (LSTM)) for the prediction and decision support for real time monitoring and optimization of water treatment systems.

Developed the largest online database of nanomaterials (NanoDatabank) in the field of nanotechnology that consists of the studies on ENM toxicity, characterization and exposure analysis

Developed data-driven models and cloud-based cyber-infrastructure for water use patterns of small agricultural communities and the development of virtual water district (California). 

Co-developed a patent pending technology for membrane-based reverse-osmosis (RO) water treatment that utilizes software engineering principles and deep learning approaches for real-time detection and identification of membrane fouling and scaling.

Research and Teaching Interests

Research interests

  1. Develop analytical and advanced machine/deep learning approaches for causal analysis and decision support modeling for autonomous and smart water treatment
  2. Human behavioral analysis using computer vision
  3. Real-time embedded systems (sensor networks and IoT) for resource management
  4. Data science (big/time-series data) for water consumption/supply and water use prediction for small disadvantaged communities
  5. Safer design and use of nanotechnology (nanotoxicology & nanomaterial exposure assessment) using machine learning, predictive modeling and data mining approaches
  6. Mobile and web application development
  7. Water treatment technology - cyber-infrastructure for virtual water treatment systems

Currently teaching

  1. Fall 2022 CSE 5120 Introduction to Artificial Intelligence - CSUSB
  2. Fall 2022 CSE 4600 Operating systems - CSUSB

Spring 2023 teaching schedule

  1. CSE 5120 Introduction to Artificial Intelligence - CSUSB


    CSE 4550 Software Engineering - CSUSB

Teaching interests

  1. Artificial intelligence (machine learning, deep reinforcement learning, computer science) 
  2. Data science
  3. Mobile and web application development
  4. Software engineering
  5. Operating systems