On-roll employmentAugust 2022 – Present
Grok Digital
Data Scientist · Formal designation: Consultant
Work in data science and analytics, including time-series telemetry, cloud data platforms, forecasting and application-facing data services.
Data systems · Applied AI · Computer Science
Dr. Alka Gupta
Data Scientist · AI Consultant · Computer Science Researcher
My work spans data engineering, analytics and applied AI, informed by doctoral research in network security. I am interested in building and evaluating dependable data-driven systems, and in connecting practical computing experience with teaching and research.
Professional experience
Data science and AI consulting
My current work combines a full-time data-science role with a separate, more recent AI consultancy engagement.
Additional consultancySeptember 2026 – Present
XRISE AI Systems India
AI Consultant
Engaged as an AI Consultant with XRISE AI Systems India, an organisation working on applied AI systems, strategy and automation. This is a consultancy engagement alongside my work at Grok Digital.
Selected industrial work
Engineering problems and implementations
Examples of my work in data platforms, operational analytics, forecasting and API-based access to information.
01Cloud data engineering
Hybrid-cloud pipeline for IoT telemetry
Designed data movement from a TimescaleDB time-series store through AWS Lambda and S3 into Google Cloud Storage, with Dataflow preparing analytics tables in BigQuery. Incremental loads use timestamp checkpoints rather than repeatedly processing the complete dataset.
Engineering focus · Data movement across platforms, incremental processing and repeatable configuration.
02Operational analytics
Temperature-excursion risk analysis
Combined sensor readings and logistics information in BigQuery to examine shipment temperature excursions. Configurable 15-, 30- and 60-minute windows support severity assessment, with downstream notifications through Cloud Functions and messaging services.
Engineering focus · Joining event and business data, defining time windows and generating actionable alerts.
03Predictive analytics
Time-series forecasting workflows
Worked with ARIMA statistical baselines and LSTM/CNN-LSTM neural forecasting methods to analyse temperature trends and possible excursions. Forecast outputs were integrated with API services and operational dashboards.
Engineering focus · Model alternatives, time-series preparation and delivering forecast information to applications.
04Data services
API access to curated cloud data
Developed serverless data-access endpoints for curated BigQuery shipment information, using API-key authentication, parameterised reporting windows and consistent UTC handling for time-based queries.
Engineering focus · Data access controls, query interfaces and consistent interpretation of time windows.
Scholarly work
Research & selected publications
My doctoral research examined intrusion detection, scalability and network-system performance. My current interests also include dependable data pipelines, edge–cloud analytics and evaluation of applied machine-learning systems.
- Detecting attacks in high-speed networks: Issues and solutionsAlka Gupta and Lalit Sen Sharma · Information Security Journal: A Global Perspective, 29(2), 51–61 (2020)DOI ↗
- A categorical survey of state-of-the-art intrusion detection system—SnortAlka Gupta and Lalit Sen Sharma · International Journal of Information and Computer Security, 13(3/4), 337–356 (2020)DOI ↗
- Performance Evaluation of Snort and Suricata Intrusion Detection Systems on Ubuntu ServerAlka Gupta and Lalit Sen Sharma · Proceedings of ICRIC 2019, Springer, 811–821 (2019)DOI ↗
- Performance Analysis and Comparison of Snort on Various PlatformsAlka Gupta and Lalit Sen Sharma · International Journal of Computer Information Systems and Industrial Management Applications, 12, 23–32 (2020)Journal ↗
- Mitigation of DoS and Port Scan Attacks Using SnortAlka Gupta and Lalit Sen Sharma · International Journal of Computer Sciences and Engineering, 7(4), 248–258 (2019)DOI ↗
Researcher identifier: ORCID 0000-0003-3087-4617.
Academic record
Education & distinctions
Doctoral and engineering qualifications, national examinations and academic awards.
Doctorate
Ph.D. — Computer Science
University of Jammu. Thesis: “To Study the Performance, Scalability and Reliability of Snort and the Contemporary Intrusion Detection Systems.”
Postgraduate
M.Tech. — Computer Science & Engineering
Shri Mata Vaishno Devi University (2011–2013). Gold Medalist; Chancellor's Award for Distinction; Infosys Foundation Prize.
Undergraduate
B.E. — Computer Science & Engineering
Government College of Engineering and Technology, Jammu (2006–2010). Gold Medalist.
National examinations
UGC-NET / JRF & GATE
Qualified UGC-NET (June 2014) and was awarded a UGC Junior Research Fellowship. Qualified GATE in 2011.
Academic engagement
Teaching & future research interests
Teaching interests
Computer networks, databases, data engineering, introductory machine learning and applied cybersecurity. I favour teaching that relates technical principles to experiments and working systems.
Research interests
Dependable IoT data pipelines, edge–cloud integration, evaluation of analytics workflows and applied machine learning for operational data. I am interested in testable, application-grounded questions in these areas.
Research, teaching and technical collaboration
For research collaboration, teaching opportunities or discussion of applied AI and data-engineering work, please get in touch.