About

Syed S.H. Rizvi is a professor of food process engineering in the Department of Food Science and holds the title of International Professor at the college. His research interests encompass the engineering and processing aspects of food science and value addition for global markets. He has made significant contributions to the understanding of physical, chemical, and engineering properties of food and related biomaterials, with a focus on international developments in the food value chain. Rizvi has published over 170 technical papers, co-authored or edited six books, and holds six patents. He is also involved with the Department of State, advising the Bureau of Economics, Energy, and Agricultural Affairs on the use of science in diplomacy. His teaching areas include engineering and processing aspects of food and related biomaterials, as well as international developments, for both undergraduate and graduate students.

Research topics

• Chemistry
• Biochemistry
• Political Science
• Materials science
• Biotechnology
• Nanotechnology
• Engineering
• Medicine
• Food science
• Biology
• Pharmacology

Selected publications

• Engineering Processes for Plant‐Based Meat Analogs: Current Status and Future Outlook

  Comprehensive Reviews in Food Science and Food Safety · 2025-10-31 · 9 citations

  reviewOpen accessSenior author

  Plant-based meat analogs (PBMAs) have emerged as a promising alternative to conventional meat, driven by growing consumer interest in sustainability, ethical considerations, and health-conscious diets. However, despite initial market enthusiasm, PBMAs struggle with declining consumer acceptance due to their inability to fully replicate the texture, juiciness, and sensory experience of animal-derived meat. Key limitations include insufficient fibrous structure, reduced tenderness, poor moisture retention during cooking, inadequate lipid distribution mimicking marbling, and unsatisfactory mouthfeel. Addressing these challenges is critical for advancing PBMA development and securing long-term market success. Unlike most reviews that broadly examine PBMA, this review specifically explores the role of processing technologies and equipment designs in enhancing meat-like properties. In this review, we have analyzed the commonly used technique for creating PBMA, the high-moisture extrusion (HME), detailing its mechanisms, equipment configurations, and processing parameters. It also briefly covers some other techniques for creating fibrous structures. Furthermore, the critical interplay between equipment parameters, ingredient properties, and final product characteristics, considering factors such as die design, shear force, moisture content, temperature control, and gas incorporation, is also covered. Moreover, we highlight major technical challenges, including scalability, cost-effective production, molecular interactions during processing, and consumer-perceived authenticity. Finally, we propose future directions for refining processing techniques, innovating equipment designs, and overcoming commercialization barriers. By bridging existing knowledge gaps and offering practical insights, this comprehensive analysis aims to support researchers and industry professionals in advancing next-generation PBMA processing technologies for widespread industrial adoption to make more consumer-acceptable products.

  PublisherOA PDFDOI

• Flash freezing of ice cream with dense phase carbon dioxide: System performance and product quality

  Journal of Food Engineering · 2025-08-09

  articleSenior author
  PublisherDOI

• Supercritical fluid extrusion of pea flour and pea protein concentrate: Effects on off‐flavor removal and sensory improvement

  Journal of Food Science · 2025-01-01 · 3 citations

  articleOpen accessSenior author

  Abstract This study was intended to provide a novel process that fills a knowledge gap in relation to the enhancement of pulses utilization. The primary goal was to develop an experimental framework for using a high‐pressure supercritical fluid extruder (SCFX) as a continuous bioreactor to produce off‐flavor reduced and functionally superior pulse flours and protein concentrates in a single step. The current study focused on using SCFX processing to remove off‐flavor from pulse flour and protein concentrates, enhancing the quality, acceptability, and marketability of pulse‐based products. Supercritical carbon dioxide (SC‐CO 2 ), a well‐known green solvent, was employed in combination with an extrusion system to achieve off‐flavor reduction at larger scale. Using various methods such as headspace solid‐phase microextraction‐gas chromatography mass‐spectroscopy (HS‐SPME‐GC‐MS) and sensory evaluation, this study demonstrated that SCFX significantly reduced the off‐flavor in pea flour (PF) and pea protein concentrate (PPC). HS‐SPME‐GC‐MS analyses identified major off‐flavor compounds in unextruded PF and PPC, including 1‐hexanol, 1‐octanol, 1‐nonanol, nonanal, and 2‐alkyl methoxypyrazines. Following SCFX treatment, all these compounds except nonanal were removed. Total off‐flavor compound concentration dropped from 923 to 126.5 ng/g in PF, and from 571.7 to 65.9 ng/g in pea protein concentrate PPC after SCFX treatment. Sensory evaluation corroborated these HS‐SPME‐GC‐MS findings, showing that over 80% of the participants could accurately distinguish the extruded samples from the unextruded ones, perceiving the treated samples as having the least beany flavor. These findings highlight the efficacy of SCFX processing in enhancing the sensory profile of pulse‐based products by removing off‐flavor compounds.

  PublisherOA PDFDOI

• Advancing malware imagery classification with explainable deep learning: A state-of-the-art approach using SHAP, LIME and Grad-CAM

  PLoS ONE · 2025-05-28 · 17 citations

  articleOpen access

  Artificial Intelligence (AI) is being integrated into increasingly more domains of everyday activities. Whereas AI has countless benefits, its convoluted and sometimes vague internal operations can establish difficulties. Nowadays, AI is significantly employed for evaluations in cybersecurity that find it challenging to justify their proceedings; this absence of accountability is alarming. Additionally, over the last ten years, the fractional elevation in malware variants has directed scholars to utilize Machine Learning (ML) and Deep Learning (DL) approaches for detection. Although these methods yield exceptional accuracy, they are also difficult to understand. Thus, the advancement of interpretable and powerful AI models is indispensable to their reliability and trustworthiness. The trust of users in the models used for cybersecurity would be undermined by the ambiguous and indefinable nature of existing AI-based methods, specifically in light of the more complicated and diverse nature of cyberattacks in modern times. The present research addresses the comparative analysis of an ensemble deep neural network (DNNW) with different ensemble techniques like RUSBoost, Random Forest, Subspace, AdaBoost, and BagTree for the best prediction against imagery malware data. It determines the best-performing model, an ensemble DNNW, for which explainability is provided. There has been relatively little study on explainability, especially when dealing with malware imagery data, irrespective of the fact that DL/ML algorithms have revolutionized malware detection. Explainability techniques such as SHAP, LIME, and Grad-CAM approaches are employed to present a complete comprehension of feature significance and local or global predictive behavior of the model over various malware categories. A comprehensive investigation of significant characteristics and their impact on the decision-making process of the model and multiple query point visualizations are some of the contributions. This strategy promotes advanced transparency and trustworthy cybersecurity applications by improving the comprehension of malware detection techniques and integrating explainable AI observations with domain-specific knowledge.

  PublisherDOI

• Effect of in-barrel CO2 saturation level on the morphology and structure development of milk protein extrudates

  International Journal of Food Science & Technology · 2025-01-01 · 2 citations

  articleOpen accessSenior author

  Abstract The combined effect of the operating pressure and supercritical carbon dioxide (SC–CO2) injection level on structure development during puffing of milk protein concentrate by supercritical fluid extrusion (SCFX) was studied. The extrudates were analysed using scanning electron microscopy, texture analyser, and electrophoresis. Extrudates obtained with SC–CO2 injection rate corresponding to the equilibrium solubility demonstrated a highly porous structure (mean pore size < 500 μm and mean pore wall thickness < 40 μm). In contrast, both undersaturated and oversaturated conditions formed extrudates having fewer large irregular pores (mean pore size > 700 μm and mean pore wall thickness > 80 μm). Reduction in interfacial tension with increasing CO2 concentration favoured homogeneous nucleation up to saturation CO2 levels, resulting in uniformly porous extrudates. SC–CO2 input rate above the saturation levels resulted in undissolved gas vacuoles in the melt, allowing dissolved CO2 to diffuse into them at die exit, favouring coalescence. These findings could have significant utility in designing novel milk protein-based puffed products of predefined structural and physicochemical properties.

  PublisherOA PDFDOI

• Correction to: Food Engineering Principles and Practices

  2025-01-01 · 1 citations

  book-chapterOpen access1st authorCorresponding

  W, BTU/h)The following abbreviation has been updated fromThe following Greek Symbol has been updated from Thermal diffusivity (k/C p ,m 2 /s .ft 2 /h), kinetic energy correction factor to Thermal diffusivity (k/C p ,m 2 /s ., or ft 2 /h), kinetic energy correction factor

  PublisherOA PDFDOI

• Clinical Activity of P-BCMA-ALLO1, an Allogeneic BCMA Targeting CAR-T, in Patients with Relapsed Refractory Multiple Myeloma (RRMM) and Extramedullary Disease

  Transplantation and Cellular Therapy · 2025-02-01

  article
  PublisherDOI

• Evaluating Forensic Log Readiness in Simulated 6G Networks

  2025-08-04

  article1st authorCorresponding

  The forensic readiness of future 6 G networks will depend not only on advanced detection systems but also on maintaining the integrity, availability, and timeliness of the system and event logs. In high-speed, ultra-low-latency environments, the risk of delayed or compromised logs is an issue for incident response and post-incident forensic analysis. This paper evaluates local and remote log collection mechanisms in a simulated 6 G network environment. Benign (low intensity) and adversarial (high intensity) traffic was generated to measure log collection performance in a Cisco router and a centralised Linux server. The results show that while log completeness is maintained in both cases, recording local logs on the router can exhibit delays up to 50s (peak delay) under high-intensity traffic, whereas remote logs are unaffected. These findings highlight the trade-off between speed and forensic reliability in high-throughput environments and show the importance of log adaptability to improve forensic readiness in the face of next-generation communication systems.

  PublisherDOI

• Supercritical Fluid Extrusion to Improve the Flavor Profile and Functional Properties of Fava Bean Protein Concentrate

  Food and Bioprocess Technology · 2025-07-21 · 1 citations

  articleSenior author
  PublisherDOI

• Technoeconomic Feasibility and Environmental Impact of Producing Milk Protein‐Rich Orally Self‐Disintegrating Puffs Using Supercritical <scp>CO₂</scp> Extrusion

  Journal of Food Process Engineering · 2025-01-01

  articleOpen accessSenior author

  ABSTRACT The present market for orally self‐disintegrating puffs designed for infants is carbohydrate‐based (over 85%), therefore lacking in protein and the capacity to induce prolonged satiety. This product category overlooks the dietary requirements of older adults afflicted with swallowing difficulties or lactose intolerance. To address this gap, a combination of milk protein concentrate (MPC), raspberry powder (2.5%RP), and lactose hydrolyzed skim milk powder (LHSMP) was used to produce nutritious puffs by supercritical fluid extrusion (SCFX). This study seeks to evaluate the technoeconomic feasibility of elderly and baby puffs using SCFX. A low‐temperature, low‐shear SCFX process with CO 2 was employed to produce orally self‐disintegrating puffs, featuring protein levels of approximately 52.1% (SCFX elderly puffs) and 49.8% (SCFX baby puffs), exhibiting similar disintegration characteristics ( p &gt; 0.05) to commercial baby puffs. Through 12 h of daily production run, the margin of safety was calculated to be 29.12% for elderly and 29.20% for baby puffs where the break‐even point was 0.76 years for both types of puffs. The costs of elderly and baby puffs were calculated to be $42.93/kg and $42.80/kg, respectively. These costs align favorably with carbohydrate‐based commercial puffs (USD 50.24–66.88/kg). The SCFX system (1.03 kW/h) consumes similar energy as conventional extrusion (0.98 kW/h) but has a lower carbon footprint per unit extractable protein (1686.11–2438.12 kg) compared to conventional extrusion (5052.78–7313.72 kg). In conclusion, the processing and marketing of SCFX elderly and SCFX baby puffs are technoeconomically feasible, potentially profitable, nutritious, and present an attractive opportunity for entry into the consumer product market.

  PublisherOA PDFDOI

Frequent coauthors

• John A. Zollweg

  17 shared

• Apratim Jash

  Cornell University

  17 shared

• Ali Ayoub

  14 shared

• Ali Ubeyitogullari

  University of Arkansas at Fayetteville

  13 shared

• Ilankovan Paraman

  New York State College of Agriculture & Life Sciences

  13 shared

• Mian Kamran Sharif

  13 shared

• John Sheppard

  South East Technological University

  12 shared

• Jimmy McGibney

  South East Technological University

  12 shared

Labs

• Novel Food Processes and EngineeringPI