Baljeet Malhotra

Baljeet Malhotra

Greater Vancouver Metropolitan Area
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About

Founder & CEO at TeejLab Inc. Previously, Research Director at SAP; Vice President of Research at Black Duck Software and Founder of Black Duck Software Canada, an R&D division of Black Duck. Concurrently holding Adjunct Professor positions at UBC Sauder School of Business, University of Victoria, and University of Northern British Columbia.

Computer scientist with 15+ years of research & innovation experience working with various public and private sector organizations and customers like SAP, Synopsys, HSBC, IBM, HP, etc. Lead several industry projects in the areas of Open Source security and compliance, governance, IoT, database management, analytics, and networks. Constantly evaluate Open Source trends and related security/compliance issues, research/industry problems to plan growth opportunities for various industries. Specialization in managing projects from the idea/need identification phase through to completion and go-to-market strategies. Implement strategic plans and high performing teams for research/startup-up projects by building relationships with academia, industries, and across organizations and teams.

Received PhD in Computing Science from the University of Alberta, Canada, a post-doctrate from the National University of Singapore, and a management certificate from Singapore Management Institute in Singapore. Published numerous patents and research work at various international journals and conferences. Provide thought leadership and give lectures at various international venues. PhD thesis nominated for CAGS/UMI distinguished dissertation award. Chosen Global Young Scientist by the Government of Singapore in 2012 and 2013. Received Industrial R&D Fellowship, Visiting Fellowship, Doctoral Scholarship (all from NSERC Canada); iCORE Postgraduate Scholarship; Walter H Johns Graduate Fellowship; Queen Elizabeth II Graduate Scholarship; ASI Graduate Scholarship from the Advanced System Institute of BC, Canada. Received the best Paper Presentation Award at the National Institute of Technology, India in 1998 for the research work on mobile (cellular) networks.

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Activity

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Experience

  • TeejLab Inc. Graphic

    TeejLab Inc.

    Vancouver, Canada Area

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    Victoria, Canada

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    Prince George, BC, Canada

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    Vancouver, Canada Area

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    Vancouver, Canada Area

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    Vancouver, Canada Area

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    Walldorf, Germany

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    Vancouver, Canada Area

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    Singapore

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Education

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    Activities and Societies: Centre for Maritime Studies

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    Activities and Societies: Database and Networks research group in the Department of Computing Science at the University of Alberta.

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Publications

  • A Biclustering-based Classification Framework for Microarray Analysis

    Pacific-Asia Knowledge Discovery and Data Mining (PAKDD), Workshop on Scalable Data Analytics (SDA@PAKDD 2014)

    In recent years, microarrays have been shown to be an effective method for studying various biological processes, e.g., to improve our understanding of diseases such as cancer. In a typical situation, microarrays can be seen as large matrices in which rows and columns represent expression values of thousands of genes and tens of conditions such as samples from various patients. Several statistical techniques have been proposed in the literature to analyze the gene expression matrices. Towards…

    In recent years, microarrays have been shown to be an effective method for studying various biological processes, e.g., to improve our understanding of diseases such as cancer. In a typical situation, microarrays can be seen as large matrices in which rows and columns represent expression values of thousands of genes and tens of conditions such as samples from various patients. Several statistical techniques have been proposed in the literature to analyze the gene expression matrices. Towards that end, biclustering has been demonstrated to be one of the most effective methods for discovering gene expression patterns under various conditions. In this paper, we present a methodology to take advantage of the homogeneously expressed genes in biclusters to construct a classifier for sample class membership prediction. Our extensive experiments on 8 real cancer microarray datasets (4 diagnostic and 4 prognostic) show that our proposed classifier performed superior in both cancer diagnosis and prognosis, the latter of which was regarded quite difficult previously. Additionally, our results demonstrate that sample classification accuracy can serve as a good subjective quality measure for different types of biclusters, and hence as a tool to extrinsically evaluate the performance of various biclustering algorithms that produce those biclusters.

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  • sRADAR: A Complex Event Processing and Visual Analytics System for Maritime Intelligence

    11th Australasian Data Mining Conference

    Maritime Intelligence is about empowering users in a port ecosystem with data and visual analytics to increase the e?ciency and e?ectiveness of maritime operations. In this context, discovery and visualization of ship domain violations based on the analysis of trajectories generated by ships could serve important navigational and business purposes. Finding patterns of domain violations in a large trajectory database, however, is a non-trivial task, primarily due to the combinatorial nature of…

    Maritime Intelligence is about empowering users in a port ecosystem with data and visual analytics to increase the e?ciency and e?ectiveness of maritime operations. In this context, discovery and visualization of ship domain violations based on the analysis of trajectories generated by ships could serve important navigational and business purposes. Finding patterns of domain violations in a large trajectory database, however, is a non-trivial task, primarily due to the combinatorial nature of the problem. In this paper, we present a system, sRADAR, which models such trajectories, applies complex event processing on the data streams to identify such domain violations, performs analytics to derive useful insights into the recorded data, and helps visualizing the result of such geo-spatial analytics. To evaluate our proposal, we setup an Automatic Identi?cation System for collecting real trajectories of ships arriving at the port of Singapore. We discuss some preliminary results on domain violations and the e?ciency of our system using the real-time data collected by our system.

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  • RFID Based Vehicular Networks for Smart Cities

    ICDE Workshop on Mobile Data Analytics (MoDA 2013)

    Monitoring the activities of vehicles in modern cities and urban areas has become imperative for solving the traffic related problems. Latest information about mobile vehicles, such as their identification (number plate), position, speed, and so on, are very important for smart traffic management solutions and business analytics. To that end, vehicles are now equipped
    with various kinds of sensors such as GPS and accelerometers that constantly generate data streams, which must be captured…

    Monitoring the activities of vehicles in modern cities and urban areas has become imperative for solving the traffic related problems. Latest information about mobile vehicles, such as their identification (number plate), position, speed, and so on, are very important for smart traffic management solutions and business analytics. To that end, vehicles are now equipped
    with various kinds of sensors such as GPS and accelerometers that constantly generate data streams, which must be captured, processed and analyzed in an efficient way. In recent time, the use of RFID has become very popular because of their cost effective solutions for vehicular monitoring in urban logistics. With the RFID tags (passive) placed inside the vehicles and the RFID
    readers placed alongside the roads, the traffic data from the vehicles can be obtained efficiently. Since the RFID readers are much costlier than the RFID tags, there is always a constraint
    on the number of RFID readers that can be deployed.

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  • Mining Maritime Schedules for Analyzing Global Shipping Networks

    Int. J. of Business Intelligence and Data Mining

    Other authors
    • Deepen Doshi
    • Stephane Bressan
    • Jasmine Lam

  • Distributed Classification of Acoustic Targets in Wireless Audio-Sensor Networks

    Computer Networks (Elsevier)

    Other authors
    • Ioanis Nikolaidis
    • Janelle Harms
    See publication

Patents

  • Software Nomenclature System for Security Vulnerability Management

    Filed US 140828US01

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Projects

  • Automatic Monitoring of Vulnerabilities in Software Systems

    Monitoring security vulnerabilities (weaknesses in software systems) is very important for organizations. Third parties such as National Institute of Standards and Technology (NIST) regularly publish vulnerability reports to secure national networks as well as to help the organizations in protecting their business interests. The main challenge in this context is that the software systems against which the vulnerabilities are published are typically known differently to various stake holders…

    Monitoring security vulnerabilities (weaknesses in software systems) is very important for organizations. Third parties such as National Institute of Standards and Technology (NIST) regularly publish vulnerability reports to secure national networks as well as to help the organizations in protecting their business interests. The main challenge in this context is that the software systems against which the vulnerabilities are published are typically known differently to various stake holders that consume those vulnerable software systems.The heart of the proposed system is a text mining technique that is capable of searching vulnerabilities from large volumes of data regardless of how the software systems are named.

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  • CityApp

    - Present

    This project aims to address the missing gap between the citizens, government bodies, and service operators of a modern city. We have developed an end to end solution addressing the needs and requirement for all three entities. It has been demonstrated at CeBIT and Best Run Cities. The goal was to provide the connection between the citizens, government authorities, and the enterprises serving the city.

    Technologies Used: Java, Javascript, SAP XS Engine, SAP HANA

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  • CityLogistics

    - Present

    Primarily due to the pressing challenges of modern cities and their growing populations; city logistics have become an important area of research in recent times. At SAP Research we are studying all aspects of city logistics. In this particular project, we are primarily focused on how existing methodologies and technologies that govern logistics and mobile delivery services in urban areas can further be improved to increase efficiency and profitability while maintaining the long term…

    Primarily due to the pressing challenges of modern cities and their growing populations; city logistics have become an important area of research in recent times. At SAP Research we are studying all aspects of city logistics. In this particular project, we are primarily focused on how existing methodologies and technologies that govern logistics and mobile delivery services in urban areas can further be improved to increase efficiency and profitability while maintaining the long term sustainability of businesses and environment. Some of the topics in the context of city logistics that we are exploring are:

    • Home delivery methods and technologies
    • Regulation of urban freight transport
    • Cooperative freight transport systems
    • Public freight terminals
    • Social and economic impacts
    • Environmental impacts
    • Routing and scheduling in urban transportation
    • Innovative freight technology
    • Public/private partnerships
    • Network pricing/ road pricing/ value pricing
    • Monitoring mechanisms and technologies

    Other creators

  • sRADAR

    - Present

    In this project we are primarily focused on the management, processing and analysis of live data streams produced by the moving objects. As a case study we consider the two prime scenarios in our research that are: (1) maritime traffic, and (2) urban ground transportation; both of which are important to Singapore for being an island nation as well one of the world’s busiest trans-shipment-port. Consider first the scenario of maritime vessels (ships) that carry 90% of the world trade, which make…

    In this project we are primarily focused on the management, processing and analysis of live data streams produced by the moving objects. As a case study we consider the two prime scenarios in our research that are: (1) maritime traffic, and (2) urban ground transportation; both of which are important to Singapore for being an island nation as well one of the world’s busiest trans-shipment-port. Consider first the scenario of maritime vessels (ships) that carry 90% of the world trade, which make them the bloodline of the global economy. Stakes are very high as thousands of people and ships with billions of dollars of goods and assets navigate through the Singapore port waters connecting hundreds of ports around the world. Maritime sector also (indirectly) operates several large scale transportation and logistics systems on a global scale while using tens or even hundreds of vehicles that are on constant move. Safety and security of personnel, ships, logistics infrastructure and goods are of great concern to port authorities, shipping, insurance and logistics companies, freight forwarders and other stake holders. To that end various types of sensors such as GPS, AIS, Radars and many others are used (on board moving assets or in command and control centers) to constantly collect information about the moving objects such as their position, speed, environmental condition around them, and so on.

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Languages

  • Hindi

    Native or bilingual proficiency

  • Punjabi

    Native or bilingual proficiency

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