Logan Howell Email & Phone Number

Hobart, Tas, Au

Hobart, Tasmania, Australia

Responsible for the real-time trading, dispatch, optimisation and monitoring of more than 2.5GW of hydro and gas generation within the National Electricity Market. I also coordinate contracted gas supplies and trade in the DWGM and STTM to support the physical hedging of our retail position, fuel our gas units and execute short-term arbitrage trades.

Hobart, Tasmania, Australia

Trading spot electricity in the NEM and gas in the DWGM and STTM as part of a 24-hour roster. The Hydro Tasmania Spot Desk manages a complex portfolio of thirty-two power stations and more than fifty key storages in its role as the primary generator in the state of Tasmania and the largest single producer of renewable energy in Australia.

Hobart, Tasmania, Australia

Developed hydropower optimisation models, automation solutions and emergency energy market analyses within the Portfolio Optimisation Group. • Co-developed a stochastic hydropower optimisation model, providing robust and actionable information to support operation of the Tasmanian energy system, and substantially reducing the business’ dependence on heuristics when making commercial decisions. • Identified the need for and proactively initiated the development of an R package to perform automated data handling and reporting for model runs, saving analysts between twenty minutes and one hour per model run. • Undertook ad-hoc energy market analysis during periods of heightened uncertainty whilst managing regular modelling responsibilities, presenting Hydro Tasmania’s Board with a range of options that the business could pursue to limit risk and maximise profitability.• Gained exposure to contract trading via Hydro Tasmania’s Front Office team and successfully co-led the development of an interactive mark-to-market report, enabling energy traders to gain insights into how Hydro Tasmania’s trading position changes on a day-to-day basis – a step-change improvement over previous spreadsheet-based practices. • Negotiated with management to recruit two interns, providing them with technical support and professional mentorship as they analysed the long-term effect of electric vehicles and climate change on Hydro Tasmania’s generation activities.

Hobart, Tasmania, Australia

Providing academic tutoring and support for 3rd year (Advanced Level) University of Tasmania subjects in applied mathematics and statistics:• KMA305 - Probability Models• KMA353 - Data Handling and Statistics 3• KMA355 - Operations Research 3• KMA356 - Principles of Statistics

Hobart, Tasmania, Australia

Created innovative interactive data visualisations, developed algorithms and produced reports for executive management within the Commercial Wholesale Portfolio group. • Initiated the development and use of interactive data visualisations within the wholesale portfolio group. These visualisations enabled a hands-on style of executive briefings and project updates, focussing on stories told by the data, rather than viewing static charts as a supplement to traditional corporate presentations. I was commended by management for taking the initiative to jointly lead this advancement.• Undertook short-notice market analysis and long-term forecasting, providing executive management with concise written updates on how announcements from battery manufacturers would affect Hydro Tasmania’s future storage strategies. • Simultaneously handled multiple market analysis and portfolio optimisation tasks. I rapidly reprioritised my workload as additional tasking arrived, allowing me to deliver key software and analysis to external partners, ensuring the portfolio optimisation project remained on schedule. • Designed and implemented highly efficient algorithms to process company data used within forecasting models and portfolio optimisation tools, reducing processing runtime by approximately 75%.

Hobart, Australia

Awarded a highly-competitive scholarship to develop an evaluation framework for ensemble-based numerical simulation of physical and biogeochemical processes in Australia’s oceans. • Developed highly efficient R and Python code to evaluate the performance of cutting-edge meteorological reanalysis products in high spatial-resolution settings. • Utilised the National Computational Infrastructure (NCI) to merge a number of massive pre-existing data sets, addressing challenges arising from temporally infrequent data within my research and advancing other CLEX research projects. • Produced novel climate and oceanic data visualisations, simplifying comparisons between climate models and their long-term behaviour. • Provided advice to junior summer research students on data visualisation and code performance.

Hobart, Australia

Specialising in the development of commercial machine learning and data analytics products within the Oceans and Atmosphere Unit. • Designed and implemented management and transfer protocols for commercially sensitive data streams and developed Python software to automate image extraction, maximising workflow efficiency and reducing the projected lead-time by two months. • Led the processing, labelling and analysis of images extracted from source footage, ensuring that all data is stored securely and complies with the standards I developed. • Adapted pre-existing knowledge bases and models to increase the efficiency of convolutional neural networks. • Constructed and presented project updates to clients and stakeholders, confidently and effectively conveying relevant data in a clear and succinct manner, working closely with the client to integrate our products seamlessly into their current business model.• Independently collaborated with world-leading researchers in relevant fields to increase product performance using cutting-edge multi-view and transfer learning techniques.• Produced and presented an extended abstract for the 2019 International Modelling and Simulation Conference (MODSIM) in Canberra. As a second year undergraduate, I was the youngest presenter at the conference and was commended by organisers for my presentation.

Hobart, Australia

Assisted in the development of a portable analytical separation device to detect trace amounts of PFOS and PFOA contaminants within soil on RAAF bases and civilian airfields.• Proposed and implemented a novel detection approach that addressed a recurrent issue within our experimental process.• Displayed a high level of attention to detail in order to comply with stringent international standards associated with laboratory procedures.• Established a strong and respectful rapport with superiors, creating a positive and enjoyable working environment.• Worked productively as a member of a diverse research and development team, and made positive contributions to group meetings.

Bachelor Of Science (First Class Honours), Mathematics

Thesis Title: AIC-Based Model Selection in Higher-Dimensional Parameter Space GPA: 7.0/7 Honours Weighted Average Mark: 89.8/100.

Bachelor Of Science - Catalyst Program, Applied Mathematics And Statistics

Major: Applied Mathematics and Statistics Minors: Computer Science and Econometrics GPA: 7.0/7 Weighted Average Mark (WAM): 93.4/100

Tasmanian Certificate Of Education, Australian Tertiary Admission Rank (Atar): 99.70

Major Awards: Tasmanian Outstanding Academic Achievement Award (Awarded to Tasmania’s Top 25 Year 12 Students) Don College Principal’s.